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<title>whataifound.org: What AI Has Actually Contributed</title>
<link>https://whataifound.org/</link>
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<description>New and updated entries in the whataifound.org registry of AI contributions to science and mathematics, graded on verification and autonomy.</description>
<language>en</language>
<lastBuildDate>Wed, 07 Oct 2026 22:43:43 +0000</lastBuildDate>
<image><url>https://whataifound.org/assets/brand/og.png</url><title>whataifound.org</title><link>https://whataifound.org/</link></image>
<item><title>722 manuscripts in 372 result families from an unreleased OpenAI model</title><link>https://whataifound.org/finding/2026-10-06-openai-math-collection</link><guid isPermaLink="false">https://whataifound.org/finding/2026-10-06-openai-math-collection</guid><pubDate>Wed, 07 Oct 2026 00:00:00 +0000</pubDate><description>OpenAI published 722 manuscripts grouped into 372 claimed results across number theory, algebraic geometry, analysis, combinatorics, theoretical computer science and mathematical physics, all produced by an unreleased internal model, with Lean formalizations attached to 235 of the families and none yet checked by anyone outside the company.  The repository's README says the model was posed about 4,000 open problems during an evaluation, that each result used on average three hours of ChatGPT Pro thinking compute, and that the output was aggregated into families and filtered for significance; a family groups a principal result with companions, consequences or alternative proofs. The families claimed include the full Birch-Swinnerton-Dyer formula in Selmer corank at most one, the quasi-Riemann hypothesis, a negative answer to Hilbert's tenth problem over the rationals, the Unique Games Conjecture, L = RL = BPL, matrix multiplication with exponent at most 9/4, Kakeya in three and four dimensions, nonamenability of Thompson's group F, isomorphism of the free group factors and Kadison's similarity conjecture, alongside dozens of counterexamples to named conjectures. Lean 4 formalizations are linked from 235 families; the formalization catalogue lists 162 papers whose main result is formalized and Comparator challenge files for checking the statements against permitted axioms. Ten families also come with abridged summaries of the model's reasoning. The README names two exceptions to the fixed procedure, the work on a zero-free region for the Riemann zeta function and the Hodge conjecture for CM abelian varieties, and says the write-up of the ℜs &gt; 11/12 zero-free region was edited by humans for readability.  Lab: OpenAI. Model: Unreleased internal OpenAI model, not named in the release. Verification: Claimed. Autonomy: AI-led.</description><category>lean</category><category>formalization</category><category>argument</category><category>number-theory</category><category>complexity-theory</category></item>
<item><title>Quasi-Riemann hypothesis: no zeros of zeta or any Dirichlet L-function with real part above 7/8</title><link>https://whataifound.org/finding/2026-10-06-quasi-riemann-hypothesis</link><guid isPermaLink="false">https://whataifound.org/finding/2026-10-06-quasi-riemann-hypothesis</guid><pubDate>Wed, 07 Oct 2026 00:00:00 +0000</pubDate><description>A Lean-formalized proof that neither the Riemann zeta function nor any Dirichlet L-function has a zero with real part greater than 7/8, the first fixed zero-free half-plane short of the line where real part equals 1, which also rules out Landau-Siegel zeros but leaves the Riemann hypothesis itself open.  The main theorem states that every finite-order Hecke L-function over ℚ(√(−3)) and every Dirichlet L-function, including ζ(s), is zero-free in ℜs &gt; 7/8, the principal pole at s = 1 excepted. The quasi-Riemann hypothesis asks for any fixed σ₀ &lt; 1 with no zeros to the right of it; the classical zero-free regions of de la Vallée Poussin and Vinogradov-Korobov shrink toward ℜs = 1 with height, and zero-density estimates such as Guth and Maynard's bound how many zeros there are rather than excluding them. A fixed half-plane gives the prime number theorem with error O(x^(7/8 + ε)). The paper works through Kubota's metaplectic theory and Patterson's cubic theta series, with sextic large-sieve estimates extending Goldmakher, Louvel and Blomer, using Dunn and Radziwiłł's unconditional cusp expansions. A companion manuscript reaches the weaker half-plane ℜs &gt; 11/12 by a different proof, and a third proves (1 − β)log q ≥ c for every real zero β of every primitive real character of conductor q ≥ 3. The Lean statement for zeta is a single line against Mathlib's own definition, OAI.riemannZeta_ne_zero_of_seven_eighths_lt_re, with separate Comparator challenges for the Dirichlet and Hecke versions and for the Siegel-zero bound, each permitting only propext, Quot.sound and Classical.choice.  Lab: OpenAI. Model: Unreleased internal OpenAI model, not named in the release. Verification: Claimed. Autonomy: Collaborative.</description><category>number-theory</category><category>riemann-zeta</category><category>l-functions</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Kakeya maximal conjecture in three dimensions and the Kakeya set conjecture in four</title><link>https://whataifound.org/finding/2026-10-06-kakeya-3d-maximal-4d</link><guid isPermaLink="false">https://whataifound.org/finding/2026-10-06-kakeya-3d-maximal-4d</guid><pubDate>Wed, 07 Oct 2026 00:00:00 +0000</pubDate><description>Two manuscripts claim that every set in four-dimensional space containing a unit segment in every direction has full Hausdorff dimension, and that the Kakeya maximal function estimate holds in three dimensions, extending Wang and Zahl's 2025 resolution of the three-dimensional set conjecture.  The four-dimensional paper proves that every K ⊂ ℝ⁴ containing a unit segment in every direction has dim_H K = 4, with no measurability assumed on the set or on the choice of segments. Its introduction gives the best earlier lower bound as 3.059, from Katz and Zahl's planebrush argument, against Wolff's 3 from 1995; Rai Choudhuri's 13/4 covers only sticky sets. The three-dimensional paper proves the stronger maximal form: for every ε &gt; 0 the radius-δ tube maximal operator maps L³(ℝ³) to L³(S²) with norm O_ε(δ^(−ε)). It builds on the streamlined Guth, Wang and Zahl proof of the set estimate and addresses the gap Wang and Zahl state after their own theorem, replacing a density loss λ^(K(ε)) by λ³. Scientific American's report names only the four-dimensional result.  Lab: OpenAI. Model: Unreleased internal OpenAI model, not named in the release. Verification: Claimed. Autonomy: AI-led.</description><category>harmonic-analysis</category><category>kakeya</category><category>geometric-measure-theory</category><category>argument</category></item>
<item><title>Optimal packings of one to seven unit squares in a circle, proved in Lean</title><link>https://whataifound.org/finding/2026-10-02-squares-in-circle-packings</link><guid isPermaLink="false">https://whataifound.org/finding/2026-10-02-squares-in-circle-packings</guid><pubDate>Tue, 06 Oct 2026 00:00:00 +0000</pubDate><description>Machine-checked proofs of the smallest circle that holds n unit squares, and of every packing that attains it, for n = 1 to 7; for five, six and seven squares no earlier proof of optimality was known.  The question is the least radius of a disk that holds n non-overlapping unit squares, each free to move and rotate. The library proves the radii √2/2, √5/2, 5√17/16, √2, √(5/2), √(q^*) with q^* a quartic irrational near 2.851, and √13/2. The optimal packing is unique up to rotation and relabelling for n ≤ 6; for n = 7 the optimal packings form a family in which the three middle squares slide along their column. For three to seven squares the proofs place a small circle about the disk centre and count how much of it each square avoiding the centre must hold; for seven squares a pair theorem on the directions of neighbouring squares is by far the longest part. The repository reports that the arc idea came from Claude, that ChatGPT first applied it to five squares, and that the models wrote the proofs and all of the Lean code, with the owner directing and reviewing.  Lab: Independent. Model: ChatGPT (GPT-6 Pro) and Claude Opus 5 and 5.5. Verification: Formally verified. Autonomy: AI-led.</description><category>discrete-geometry</category><category>packing</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Closed form for the anisotropic Watson integral of the cubic lattice</title><link>https://whataifound.org/finding/2026-10-01-anisotropic-watson-integral</link><guid isPermaLink="false">https://whataifound.org/finding/2026-10-01-anisotropic-watson-integral</guid><pubDate>Tue, 06 Oct 2026 00:00:00 +0000</pubDate><description>The return probability of a random walk on the cubic lattice with three unequal hopping rates, open since Watson's 1939 solution of the symmetric case, is given in closed form through periods of a genus-two curve, with a proof that no formula in elliptic integrals exists for generic rates.  The lattice Green's function W(α₁, α₂, α₃;w) = 1/π³∫_([0, π]³)d³k/(w − α₁cos k₁ − α₂cos k₂ − α₃cos k₃) gives the return probability R = 1 − 1/(w^(⋆)W) at the band edge w^(⋆) = α₁ + α₂ + α₃. Closed forms were known when one rate vanishes or when two or three are equal (Watson 1939, Joyce 1973, Delves and Joyce 2001), each an algebraic function times at most two complete elliptic integrals. The authors' summary states that for generic rates wW satisfies a fifth-order differential equation whose group has connected part SO(5), so no such elliptic formula exists, and gives W instead through a minor of the period matrix of a genus-two curve built from the rates. At rates in the ratio 1:5:7 the walker returns with probability about 0.4394, against 0.3405 at equal rates. The result is one of roughly fourteen in a guest essay by Schwartz on Anthropic's blog describing work with Claude through his BootLoops harness.  Lab: Independent. Model: Claude (the announcement names Claude Fable 5). Verification: Claimed. Autonomy: AI-assisted.</description><category>lattice-green-functions</category><category>random-walks</category><category>algebraic-geometry</category><category>argument</category></item>
<item><title>Six-task counterexample to the Kernel Conjecture of pinwheel scheduling</title><link>https://whataifound.org/finding/2026-09-30-pinwheel-kernel-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-30-pinwheel-kernel-conjecture</guid><pubDate>Tue, 06 Oct 2026 00:00:00 +0000</pubDate><description>A six-task pinwheel scheduling instance with periods (3, 4, 5, 20, 22, 36) can be scheduled, but not once its longest period is cut to 32, which refutes the Kernel Conjecture and the equivalent 2ᵏ Conjecture of Gąsieniec, Smith and Wild.  In pinwheel scheduling one task is performed per day, and a task with period aᵢ must be performed at least once in every aᵢ consecutive days. Gąsieniec, Smith and Wild conjectured that every schedulable instance with k tasks is dominated by a schedulable one, with no period longer, whose largest period is at most 2^(k − 1), and proved this equivalent to the claim that a loosely schedulable instance always has a schedule with a free day at least every 2ᵏ days. For six tasks the cap is 32. A 36-day repeating word schedules (3, 4, 5, 20, 22, 36), while finite certificates show that (3, 4, 5, 20, 22, b) cannot be scheduled for b = 32 or b = 35, so the threshold for the sixth period is exactly 36 and every dominated instance capped at 32 fails by monotonicity. Each certificate lists every reachable state with a rank that strictly decreases along every legal move, which rules out non-periodic schedules too. The repository carries a Lean 4 formalization of the certificate argument and of both endpoints, built against the standard library alone.  Lab: Independent. Model: GPT-6 Astra (in OpenAI Codex). Verification: Formally verified. Autonomy: AI-led.</description><category>scheduling</category><category>algorithms</category><category>counterexample</category><category>lean</category><category>formalization</category><category>construction</category></item>
<item><title>Six-particle MHV amplitude in planar N=4 super Yang-Mills computed at nine loops</title><link>https://whataifound.org/finding/2026-09-25-nine-loop-hexagon-amplitude</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-25-nine-loop-hexagon-amplitude</guid><pubDate>Thu, 01 Oct 2026 00:00:00 +0000</pubDate><description>Claude computed the six-particle maximally-helicity-violating amplitude in planar N = 4 super Yang-Mills theory at nine loops, one loop beyond the previous record, from a single prompt naming the problem.  Two Anthropic physicists gave Claude one prompt, "The problem is to compute the Six-particle (hexagon) amplitude in planar N=4 SYM at nine loops", and afterwards only told it to keep working. It did the calculation two ways: the original hexagon bootstrap, and the indirect route of bootstrapping the three-point form factor of the chiral stress-tensor multiplet, mapping it to the amplitude by antipodal duality and lifting it with pentagon operator product expansion data. The bootstrap ran in Python with SymPy on about $100 of compute, 96 CPUs for a week. The data page records the checks Claude ran before handing the result over: rational reconstruction at three 31-bit primes, agreement between independent prime computations, a reproduction of the published eight-loop amplitude on 1,000 random words, and symmetry and vanishing tests. Lance Dixon, who set the eight-loop record, then validated the result, mostly by mapping the amplitude back to the form factor. The symbol and function files are public on Zenodo under CC BY 4.0.  Lab: Anthropic. Model: Claude Fable 5.1 (in Claude Science). Verification: Author verified. Autonomy: AI-led.</description><category>scattering-amplitudes</category><category>quantum-field-theory</category><category>agents</category><category>computation</category></item>
<item><title>Erdős Problem #1220 formalized as not provable in ZFC, from a 1987 Shelah-Stanley consistency result</title><link>https://whataifound.org/finding/2026-09-26-erdos-1220-not-provable</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-26-erdos-1220-not-provable</guid><pubDate>Mon, 28 Sep 2026 00:00:00 +0000</pubDate><description>A Lean 4 formalization shows that ZFC cannot prove a positive answer to Erdős Problem #1220 on partition relations for singular cardinals, by formalizing Shelah and Stanley's 1987 forcing construction, with AI models assisting on the Lean code.  Erdős Problem #1220, from Erdős and Hajnal in 1971, asks whether λ → (λ, ℵ₁)² holds for every singular cardinal λ with λ and cf(λ) both ℵ₀-inaccessible. The repository proves, inside Mathlib's first-order logic, that ZFC does not prove the affirmative sentence, and a second target certifies that the sentence is equivalent in Mathlib's ZFSet to a Mathlib-level statement of the problem as posed on erdosproblems.com. The construction follows Shelah and Stanley (Sh:258, section 3) with the ground-model witness λ = ℶ_(c⁺), and builds a Boolean-valued model using the Lean 4 port of Flypitch vendored through Elliot Glazer's Erdős #501 development. Only non-provability is formalized: consistency of the positive answer, and so full independence, is outside its scope.  Lab: Independent. Model: Claude Opus 5.5 (Claude Code); Astra (OpenAI Codex). Verification: Author verified. Autonomy: AI-assisted.</description><category>set-theory</category><category>erdos</category><category>lean</category><category>formalization</category><category>forcing</category></item>
<item><title>Hamilton cycles in connected Cayley graphs of polylogarithmic degree, toward the Lovász conjecture</title><link>https://whataifound.org/finding/2026-09-26-lovasz-cayley-polylog-degree</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-26-lovasz-cayley-polylog-degree</guid><pubDate>Mon, 28 Sep 2026 00:00:00 +0000</pubDate><description>Every connected Cayley graph on n vertices with degree at least C(log n)¹³/log log n has a Hamilton cycle, lowering the degree threshold in the Cayley-graph form of the Lovász conjecture from a power of n to a power of log n; the manuscript was drafted by GPT 6 Pro and the proof formalized in Lean by Claude agents.  Lovász asked in 1969 whether every connected vertex-transitive graph has a Hamilton path; the Cayley-graph form asks whether every connected Cayley graph on at least three vertices is Hamiltonian. For arbitrary connected Cayley graphs this was known for linear degree (Christofides, Hladký and Máthé, 2014) and for degree at least n^(1 − c) (Bedert, Draganić, Müyesser and Pavez-Signé, arXiv:2603.08675). The research draft dated 25 September 2026 lowers the threshold to C(log n)¹³/log log n through local absorption, signed rounding, a weighted partition and a connecting system. The repository formalizes the whole draft as a DAG of about 55 lemmas in roughly 36,500 lines, including classical inputs the paper uses without proof, and states the theorem in a Mathlib-only Challenge.lean using Mathlib's own Cayley graph and Hamiltonicity definitions.  Lab: Independent. Model: GPT 6 Pro (manuscript draft); Claude Opus 5.5 agents in Grok Build (Lean formalization). Verification: Claimed. Autonomy: Collaborative.</description><category>graph-theory</category><category>combinatorics</category><category>lovasz-conjecture</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Four Color Theorem formalized in Lean 4 by AI agents, in two independent developments</title><link>https://whataifound.org/finding/2026-09-16-four-color-theorem-lean</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-16-four-color-theorem-lean</guid><pubDate>Mon, 28 Sep 2026 00:00:00 +0000</pubDate><description>Two independent Lean 4 proofs of the Four Color Theorem, each following Gonthier and Werner's Coq proof and each written almost entirely by a Claude model under one person's direction, resting only on Lean's three standard axioms.  Chris Emery's corun1024/4ct, public on 2026-09-16, proves FourColor.fourColorTheorem from a 195-line statement file that transcribes Gonthier's real-plane statement and proves its elementary topological notions equal to Mathlib's IsOpen, closure and IsPreconnected. Its README reports 115,342 declarations checked with no sorry and no extra axiom; its reducibility certificates are produced by C and Python tools and then checked by the Lean kernel. Robert D. Barish's port, public on 2026-09-26, transcribes Coq's realplane.v one for one in a 220-line Challenge.lean and computes all 633 reducibility certificates inside Lean during the build, so the Lean toolchain alone checks it. Its README reports a local rehearsal of Palomar's pipeline in which leanchecker, nanoda and con-ron accept the proof, and it carries a Palomar registration. Neither development uses native_decide.  Lab: Independent. Model: Claude Fable 5.1 and Claude Opus 5 (Emery); Claude Opus 5.5 (Barish). Verification: Claimed. Autonomy: AI-led.</description><category>graph-theory</category><category>four-color-theorem</category><category>lean</category><category>formalization</category></item>
<item><title>Exponential lower bound for the bit pigeonhole principle in unrestricted resolution over parities</title><link>https://whataifound.org/finding/2026-09-15-bit-php-resolution-over-parities</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-15-bit-php-resolution-over-parities</guid><pubDate>Mon, 28 Sep 2026 00:00:00 +0000</pubDate><description>Any refutation of the bit pigeonhole principle in resolution over parities, a proof system whose lines are disjunctions of linear equations mod 2, must be exponentially long even with no restriction on its depth or regularity; the mathematics was produced by AI models and the main theorem is checked in Lean.  Resolution over parities, Res(⊕), extends resolution by letting clauses be disjunctions of affine equations over 𝔽₂. Superpolynomial size lower bounds were previously known only for restricted refutations: tree-like, regular, or of bounded depth. The paper claims that every DAG-like Res(⊕) refutation of the bit pigeonhole principle with n + 1 pigeons and n = 2ˡ holes has more than exp(n/(32768 l²)) clauses for every l of at least 32. The argument translates a refutation into a low-degree polynomial calculus refutation over extension variables in the style of Buss, Impagliazzo, Krajicek, Pudlak, Razborov and Sgall, removes the extension variables with one substitution, and closes with a Razborov-style degree lower bound proved through the homology of chessboard complexes. The main theorem, a general sufficient condition for Res(⊕) size lower bounds, and their dependencies are formalized in Lean 4 in the author's repository.  Lab: Independent. Model: GPT-6 Astra (mathematics, version 1 formalization and drafting); Claude Fable 5.1 and Claude Opus 5 (revision 1 formalization). Verification: Claimed. Autonomy: AI-led.</description><category>proof-complexity</category><category>pigeonhole-principle</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Norm-variation of multiple ergodic averages, including Tao's norm-convergence theorem, autoformalized in Lean in one week</title><link>https://whataifound.org/finding/2026-08-27-norm-variation-ergodic-averages-lean</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-27-norm-variation-ergodic-averages-lean</guid><pubDate>Mon, 28 Sep 2026 00:00:00 +0000</pubDate><description>A Lean 4 proof of about 107,000 lines of a new norm-variation estimate for multiple ergodic averages of commuting transformations, which strengthens Tao's 2008 norm-convergence theorem, was produced by coding agents in one week from a human-written blueprint and hand-formalized statements.  The companion arXiv paper (2608.27321) is a blueprint for a forthcoming traditional paper by the same authors. It proves r-variation bounds in L² for multiple ergodic averages of n commuting measure-preserving transformations, strengthening Tao's norm-convergence theorem and, per its abstract, resolving an open question, through an explicit real-variable estimate for twisted multilinear averages tied to singular Brascamp-Lieb inequalities. In the repository the statements of the three main theorems, nCT.main_ergodic_theorem, nCT.tao_norm_convergence and nCT.main_twisted_theorem, were formalized by hand, and the proofs were autoformalized over one week by coding agents under human supervision, about 107,000 lines excluding comments and blank lines. That includes prerequisites not in Mathlib: multilinear complex interpolation, the Calderón transference principle and properties of Wiener space functions.  Lab: Independent. Model: Coding agents, models not stated. Verification: Author verified. Autonomy: AI-led.</description><category>ergodic-theory</category><category>harmonic-analysis</category><category>lean</category><category>formalization</category></item>
<item><title>Agent-run genome survey identifies array-associated reverse transcriptases in jumbo phages</title><link>https://whataifound.org/finding/2026-09-23-array-associated-reverse-transcriptases</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-23-array-associated-reverse-transcriptases</guid><pubDate>Thu, 24 Sep 2026 00:00:00 +0000</pubDate><description>Claude agents surveying reverse transcriptase genes across 1.9 billion metagenomic protein clusters flagged a family of jumbo-phage reverse transcriptases paired with an array of repeated non-coding DNA units and a dedicated partner gene, an arrangement the authors say fits no described reverse transcriptase class.  A harness of Claude Code agents, each task split between a worker and a reviewing supervisor, ran from a human-written brief asking for new partner-gene associations of reverse transcriptases. Over 119 tasks, 949 agent sessions and 21.5 hours without human intervention, the agents built their own profile models, recovered about 200,000 reverse transcriptase clusters and filed 19 reports. The defining observation was off-brief: a worker reading the raw DNA upstream of a phage reverse transcriptase noticed a tandem repeat array, checked it against known elements including CRISPR arrays, and reported it. The authors then characterized the family in interactive sessions, finding 95 related clusters, 28 with arrays of 3 to 21 repeats of 15 to 49 nucleotides separated by 120 to 220 nucleotide spacers, a clade beside retrons, and no nearby cas genes. Published infection RNA-seq for Staphylococcus phage SA1 shows the arrays highly expressed, and the authors' own small-RNA sequencing of the SA1 array expressed in E. coli shows it processed into discrete unit RNAs.  Lab: Anthropic. Model: Claude Mythos 5. Verification: Claimed. Autonomy: Collaborative.</description><category>genomics</category><category>bacteriophage</category><category>multi-agent</category><category>autonomous-discovery</category></item>
<item><title>A 3-generator 9-relator group with unsolvable word problem, and smaller Adian-Rabin families</title><link>https://whataifound.org/finding/2026-09-09-small-undecidable-groups</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-09-small-undecidable-groups</guid><pubDate>Thu, 24 Sep 2026 00:00:00 +0000</pubDate><description>A group given by 3 generators and 9 relations has an unsolvable word problem, beating the 12-relation record Borisov set in 1969, and it yields families of 4-generator 11-relator and 2-generator 10-relator presentations for which no algorithm can decide whether the group is trivial.  How small a finite presentation can be while still being algorithmically undecidable is a quantitative question that runs from Boone's 32-relator group through Collins to Borisov's 12. Starting from Borisov's group, the construction adds two HNN extensions and then removes seven redundant relators and six generator-relator pairs by Tietze transformations, leaving 3 generators and 9 relators. Feeding that group into Tancer's and Gordon's reductions, with two further Tietze eliminations in Tancer's case, gives the two Adian-Rabin families, improving Tancer's deficiency-9 family and Gordon's 13-relator family. By Markov's argument these give Corollary 1.5, that a connected sum of n copies of S2 x S2 is topologically unrecognizable for n at least 7 and smoothly unrecognizable for n at least 9. The three algebraic theorems, with every dependency down to Post's machine-to-Thue construction and Matiyasevich's three-rule Thue system, are formalized in about 28,000 lines of Lean.  Lab: Independent. Model: GPT-5.6 Sol Pro (construction); GPT-5.6 Sol in Codex (Lean formalization). Verification: Author verified. Autonomy: AI-led.</description><category>group-theory</category><category>logic</category><category>construction</category><category>lean</category><category>formalization</category></item>
<item><title>Counterexample to Talagrand's operator cotype problem</title><link>https://whataifound.org/finding/2026-09-17-talagrand-operator-cotype</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-17-talagrand-operator-cotype</guid><pubDate>Tue, 22 Sep 2026 00:00:00 +0000</pubDate><description>An operator is exhibited whose Rademacher cotype is not controlled by the maximum of its Gaussian cotype and its (q,1)-summing norm, answering Talagrand's question in the negative already at q equals 2.  Talagrand asked whether the Rademacher cotype of an operator is universally controlled by the maximum of two quantities: its Gaussian cotype and its (q,1)-summing norm. The paper answers no, and does so at the smallest interesting parameter, q equals 2, rather than only for large q. The AI disclosure is a single sentence and it is the last line of the abstract: the counterexample was discovered by ChatGPT (GPT-5.6). That places the decisive step, producing the object itself, with the model, and leaves the write-up with the author.  Lab: Independent. Model: ChatGPT (GPT-5.6). Verification: Claimed. Autonomy: AI-led.</description><category>functional-analysis</category><category>probability</category><category>counterexample</category><category>construction</category></item>
<item><title>Huang-Jiang-Oblomkov conjecture proved for every torus-knot singularity, with a Lean formalization conditional on two literature inputs</title><link>https://whataifound.org/finding/2026-09-17-rogers-ramanujan-torus-knot</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-17-rogers-ramanujan-torus-knot</guid><pubDate>Tue, 22 Sep 2026 00:00:00 +0000</pubDate><description>The geometric extension of the Rogers-Ramanujan and Andrews-Gordon identities conjectured by Huang, Jiang and Oblomkov is proved for every torus-knot singularity with coprime exponents, via a stronger finite identity.  The conjecture of Huang, Jiang and Oblomkov gives a geometric extension of the Rogers-Ramanujan and Andrews-Gordon identities for the torus-knot singularity Xᵃ = Yᵇ with coprime exponents. The paper establishes a threefold equality between a normalized count of pairs of commuting nilpotent matrices over a finite field satisfying Aᵃ = Bᵇ, the HJO q-series, and an explicit infinite product. The main result is stated as a stronger finite identity, that the rank N HJO sum equals a q-Pochhammer factor times the generating function for balanced cylindric partitions with entries bounded by N, with the conjecture following in the limit. The proof is human mathematics: it combines the compositional rational shuffle theorem of Bergeron, Garsia, Leven and Xin and of Mellit with a multiplicativity theorem for slope operators and a determinantal model, linked by a common q-difference equation. The abstract's AI disclosure covers the formalization only: the finite identity and the HJO conjecture have been formalized in Lean by AxiomProver, conditional on two stated literature inputs.  Lab: Axiom Math. Model: AxiomProver. Verification: Claimed. Autonomy: AI-assisted.</description><category>number-theory</category><category>combinatorics</category><category>q-series</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Browning-Sawin conjecture on random sign-coefficient hypersurfaces proved, with a Lean formalization assuming existing literature</title><link>https://whataifound.org/finding/2026-09-16-browning-sawin-hypersurfaces</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-16-browning-sawin-hypersurfaces</guid><pubDate>Tue, 22 Sep 2026 00:00:00 +0000</pubDate><description>Random hypersurfaces with coefficients drawn uniformly from plus and minus one are shown to be smooth with probability tending to one as the degree grows, with a quantitative rate.  Browning and Sawin conjectured that random hypersurfaces with sign coefficients are smooth with probability tending to one as the degree grows. The paper proves this and adds a rate: for each n at least 1, a degree d form in n + 1 variables with independent uniform coefficients in plus and minus one defines a singular complex hypersurface with probability Oₙ(d^(−1/2)). Positive-dimensional singular loci are shown to occur with exponentially small probability, and for n at least 3 the same exponential bound is given for failure of absolute irreducibility. The abstract's AI disclosure is one sentence and covers the formalization: these results have been formalized in Lean by AxiomProver assuming existing literature.  Lab: Axiom Math. Model: AxiomProver. Verification: Claimed. Autonomy: AI-assisted.</description><category>algebraic-geometry</category><category>probability</category><category>arithmetic-statistics</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Finite-time blowup for the IPM equation with uniformly space-time smooth forcing</title><link>https://whataifound.org/finding/2026-09-15-ipm-forced-blowup</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-15-ipm-forced-blowup</guid><pubDate>Tue, 22 Sep 2026 00:00:00 +0000</pubDate><description>The incompressible porous medium equation on the two-dimensional torus is shown to develop a finite-time singularity under a force that is smooth in space and time together, extending a result previously available only for spatially smooth forcing.  Cordoba and Martinez-Zoroa proved finite-time blowup for the incompressible porous medium equation with a spatially smooth force. This paper adapts their technique to a force that is uniformly smooth in space and time together, which is the stronger requirement. It exhibits a smooth odd initial density, a smooth odd force on the unit time interval crossed with the two-dimensional torus, and a classical solution on the half-open interval whose density gradient and spatial velocity gradient both diverge in the supremum norm as time approaches one, while the density itself still converges in every Holder class below Lipschitz. It is one of three companion forced-blowup results from the same group covering IPM, Boussinesq and three-dimensional Euler; the other two are not yet in this registry.  Lab: Independent. Model: Not named; the arXiv comment field states only that the proof is LLM-assisted. Verification: Claimed. Autonomy: AI-assisted.</description><category>pde</category><category>fluid-dynamics</category><category>singularity</category><category>argument</category></item>
<item><title>Existence of the core in approval-based committee elections</title><link>https://whataifound.org/finding/2026-09-10-approval-committee-core</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-10-approval-committee-core</guid><pubDate>Tue, 22 Sep 2026 00:00:00 +0000</pubDate><description>Every approval-based multi-winner election is shown to admit a committee in the core, settling the main open question in the area, and one can be found in polynomial time.  The core is a stability and group-fairness notion for multi-winner elections: a committee is in the core when no group of voters large enough to deserve a different outcome all prefer one. Whether a core committee always exists was the main open question in the theory of approval-based multi-winner elections. The paper shows one always does. The proof introduces a voting rule that optimizes an entropy-like objective over committees and payment systems together, and shows every local optimum of that objective lies in the core, which also yields a polynomial-time algorithm. The arXiv comment field carries the AI disclosure in one line: the proof was obtained with GPT-6 Astra.  Lab: Independent. Model: GPT-6 Astra. Verification: Claimed. Autonomy: Collaborative.</description><category>social-choice</category><category>combinatorics</category><category>algorithms</category><category>argument</category></item>
<item><title>Improved lower bound for the complex Grothendieck constant</title><link>https://whataifound.org/finding/2026-09-07-complex-grothendieck-constant</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-07-complex-grothendieck-constant</guid><pubDate>Tue, 22 Sep 2026 00:00:00 +0000</pubDate><description>The complex Grothendieck constant is shown to exceed 1.35584631827168, closing more than a quarter of the gap between the long-standing Davie lower bound and the Haagerup upper bound.  The classical complex Grothendieck constant is bracketed between Davie's lower bound and Haagerup's upper bound, and the interval has been stubborn. This paper reports a new lower bound of 1.35584631827168 and states that it closes more than one quarter of that gap. The abstract records two separate facts about how it was produced: the numerical part of the proof is rigorously verified by interval arithmetic, and the lower bound and the proof were discovered by the Odin Automatic AI Research Agent.  Lab: Independent. Model: Odin Automatic AI Research Agent. Verification: Author verified. Autonomy: AI-led.</description><category>functional-analysis</category><category>optimization</category><category>interval-arithmetic</category><category>construction</category></item>
<item><title>Nivat's conjecture claimed in its sharp form, with the submitter stating he cannot check it</title><link>https://whataifound.org/finding/2026-09-14-nivat-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-14-nivat-conjecture</guid><pubDate>Tue, 15 Sep 2026 00:00:00 +0000</pubDate><description>A Lean development claims Nivat's 1997 conjecture in full: if a two-dimensional configuration has at most mn distinct patterns on some m by n rectangle, it has a nonzero period.  Nivat conjectured in 1997 that low rectangular pattern complexity forces periodicity in a two-dimensional configuration. Partial results are known under stronger complexity bounds; the sharp mn form has stood. The repository separates Challenge.lean, which states the result in mathlib terms alone, from Solution.lean, which proves it, and carries a Palomar registration. The submitter's disclaimer is the unusual part and is quoted in the caveats: he says the proof is entirely the model's and that he is not qualified to check it.  Lab: Independent. Model: GPT-6 Pro (proof); GPT-6 Astra Ultra through Codex (Lean formalization). Verification: Claimed. Autonomy: AI-led.</description><category>symbolic-dynamics</category><category>combinatorics</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Bollobas-Nikiforov conjecture claimed in full, in a weighted form</title><link>https://whataifound.org/finding/2026-09-06-bollobas-nikiforov</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-06-bollobas-nikiforov</guid><pubDate>Tue, 15 Sep 2026 00:00:00 +0000</pubDate><description>Five named mathematicians with AI assistance claim the 2007 Bollobas-Nikiforov conjecture for every noncomplete graph, bounding the sum of the squares of the two largest adjacency eigenvalues, with a Lean formalization.  Bollobas and Nikiforov conjectured in 2007 that every noncomplete graph on at least two vertices satisfies a bound on the sum of the squares of its two largest adjacency eigenvalues, in terms of its edge count and clique number. The repository formalizes the conjecture together with a weighted spectral inequality and a completely positive matrix theorem that prove it, and carries a Palomar registration. The AI roles are split and disclosed individually: ideation and the manuscript from GPT-6 Astra, the Lean development completed by Grok 4.6 with minimal direction, and submission packaging by a Claude agent.  Lab: Independent. Model: GPT-6 Astra (ideation and manuscript); Grok 4.6 (Lean formalization); Claude Fable 5.1 (submission packaging). Verification: Claimed. Autonomy: Collaborative.</description><category>graph-theory</category><category>spectral-graph-theory</category><category>combinatorics</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Disproof of the Ibragimov-Iosifescu conjecture for phi-mixing sequences</title><link>https://whataifound.org/finding/2026-09-05-ibragimov-iosifescu</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-05-ibragimov-iosifescu</guid><pubDate>Tue, 15 Sep 2026 00:00:00 +0000</pubDate><description>A Lean development constructs a stationary phi-mixing sequence with finite second moments whose normalized partial sums fail to satisfy the central limit theorem, disproving a 1971 conjecture.  Ibragimov conjectured that a strictly stationary phi-mixing sequence with finite second moments and diverging partial-sum variance satisfies the central limit theorem; Iosifescu's stronger form asks for convergence of the rescaled partial-sum process to Brownian motion. The construction uses bounded causal feedback to suppress ordinary fluctuations while rare large spikes retain the variance, giving variance divergence together with collapse of the normalized sums along a subsequence. Disproving Ibragimov's form rules out Iosifescu's, since that convergence would give the central limit theorem at time one. The recorded verification reports the standard three axioms only.  Lab: OpenAI / Epoch AI. Model: GPT-6 Astra (pre-release). Verification: Claimed. Autonomy: AI-led.</description><category>probability</category><category>central-limit-theorem</category><category>lean</category><category>formalization</category><category>construction</category></item>
<item><title>Counterexample to Smale's mean value conjecture at K = 1</title><link>https://whataifound.org/finding/2026-09-03-smale-mean-value-k1</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-03-smale-mean-value-k1</guid><pubDate>Tue, 15 Sep 2026 00:00:00 +0000</pubDate><description>A Lean proof produced in an unsteered benchmark run disproves the K = 1 form of Smale's 1981 mean value conjecture, exhibiting a polynomial for which no critical point meets the bound.  Smale proved in 1981 that for every complex polynomial f of degree at least two and every point z there is a critical point c with |f(z) − f(c)|/|z − c| ≤ K|f′(z)| for K = 4, and asked whether K can be lowered to 1. The constant has since been lowered to four minus order one over the degree, and the conjecture is known for small degrees and for polynomials whose roots are all real or all of one modulus. This development proves the negation of the Formal Conjectures statement. It came out of the same Epoch AI LeanOpenProblems evaluation run as the Koethe and Erdos-Sos entries already in the registry, and Comparator checks the compared statement against the challenge file under the three standard axioms.  Lab: OpenAI / Epoch AI. Model: GPT-6 Astra (pre-release). Verification: Formally verified. Autonomy: Autonomous.</description><category>complex-analysis</category><category>polynomials</category><category>lean</category><category>formalization</category><category>construction</category></item>
<item><title>Bounded prime gaps improved to 212, with a Lean certificate of the deduction</title><link>https://whataifound.org/finding/2026-09-03-prime-gaps-212</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-03-prime-gaps-212</guid><pubDate>Tue, 15 Sep 2026 00:00:00 +0000</pubDate><description>Nine authors prove that infinitely many pairs of primes differ by at most 212, improving Stadlmann's 240, with the deduction certified in Lean by the group's own prover.  The bounded-gaps line runs from Zhang in 2013 through Maynard's sieve to the Polymath8b bound of 246, which this registry already carries as a formalization entry, and then to Stadlmann's 240. This paper builds on Stadlmann's work to reach 212. The authors are explicit about the division of labour: the mathematics is theirs, and AxiomProver generated the Lean certificate of the deduction from natural-language specifications rather than finding the argument.  Lab: Axiom Math. Model: AxiomProver. Verification: Claimed. Autonomy: Collaborative.</description><category>number-theory</category><category>prime-gaps</category><category>sieve-methods</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Prime gaps at most 186, conditional on three unproved Lean axioms</title><link>https://whataifound.org/finding/2026-09-02-prime-gaps-186</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-02-prime-gaps-186</guid><pubDate>Tue, 15 Sep 2026 00:00:00 +0000</pubDate><description>An OpenAI repository derives a bound of 186 on infinitely many prime gaps in Lean, from three inputs it states as axioms rather than proving.  This is numerically the strongest of three bounded prime-gap claims from the same window, ahead of the Axiom Math 212 recorded separately here and the 246 already in the registry, and it is the weakest evidentially. The development derives DHL[40,2], and so the bound, from three stated inputs. Those inputs are not proved in Lean: the repository's own README says the results remain conditional on three explicit input axioms and that the cited estimates and numerical computations have not been turned into Lean proofs.  Lab: OpenAI. Model: GPT-6 Astra. Verification: Claimed. Autonomy: AI-led.</description><category>number-theory</category><category>prime-gaps</category><category>sieve-methods</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Finite-time blowup for Navier-Stokes with smooth forcing, Clay alternatives C and D</title><link>https://whataifound.org/finding/2026-09-08-navier-stokes-forced-blowup</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-08-navier-stokes-forced-blowup</guid><pubDate>Thu, 10 Sep 2026 00:00:00 +0000</pubDate><description>A Lean development proves that three-dimensional Navier-Stokes with a smooth forcing term breaks down in finite time, at every positive viscosity, on both Euclidean space and the periodic torus, which is two of the four statements the Clay problem description asks for a proof of, though not the unforced regularity question the phrase usually brings to mind.  Fefferman's Clay problem description asks for a proof of one of four statements, offered as leeway to solvers while, in his words, retaining the heart of the problem. This work settles (C) and (D), the two breakdown alternatives, both of which permit a smooth external force meeting the decay conditions the description imposes: for every positive viscosity there exist smooth initial data and forcing admitting no global smooth solution of uniformly bounded kinetic energy on ℝ³, and smooth periodic data and forcing admitting no global smooth solution on ℝ³/ℤ³. The repository carries Lean 4 proofs of both, declared as navier_stokes_breakdown_R3 and navier_stokes_breakdown_periodic, each recorded with no sorry and depending on exactly propext, Classical.choice and Quot.sound. The Comparator reference statements were adapted from Google DeepMind's Formal Conjectures formalization of the Clay problem rather than written for this repository, and the challenge config enables the independent nanoda kernel. The same repository also carries two theorems on unforced Euler blowup, which are a separate result and are not covered by this entry.  Lab: OpenAI. Model: Unnamed OpenAI model described as more capable than GPT-6 Astra for the proof; GPT-6 Astra through Codex for the Lean formalization. Verification: Claimed. Autonomy: AI-led.</description><category>pde</category><category>fluid-dynamics</category><category>navier-stokes</category><category>singularity</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Finite-time blowup for the unforced Euler equations from smooth compactly supported data</title><link>https://whataifound.org/finding/2026-09-08-euler-unforced-blowup</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-08-euler-unforced-blowup</guid><pubDate>Thu, 10 Sep 2026 00:00:00 +0000</pubDate><description>A Lean development proves that the three-dimensional incompressible Euler equations, with no forcing term, develop a singularity in finite time from smooth, compactly supported, divergence-free initial velocity on all of space.  Whether the three-dimensional incompressible Euler equations can produce a singularity in finite time from smooth finite-energy data, with no forcing and no boundary, is one of the long-standing questions in mathematical fluid dynamics. The repository states the result twice: euler_breakdown_R3, that no global smooth unforced solution of uniformly bounded kinetic energy exists on ℝ³, and exists_compact_smooth_euler_singularity, which gives compactly supported smooth initial data with a positive finite maximal lifespan in the all-order Sobolev class, an unbounded limsup of the velocity's C¹ norm, and a divergent time integral of the vorticity's sup norm. That last condition is the Beale-Kato-Majda quantity, so the blowup is certified in the classical criterion rather than only as a loss of regularity. Both theorems are recorded with no sorry and dependence on exactly propext, Classical.choice and Quot.sound, and the Comparator config enables the independent nanoda kernel. OpenAI's account describes roughly 100 agents working about 50 hours on this result, against roughly 10,000 over 88 hours for the companion Navier-Stokes work. Euler is not one of the Clay Millennium problems; that list carries Navier-Stokes only.  Lab: OpenAI. Model: Unnamed OpenAI model described as more capable than GPT-6 Astra for the proof; GPT-6 Astra through Codex for the Lean formalization. Verification: Claimed. Autonomy: AI-led.</description><category>pde</category><category>fluid-dynamics</category><category>euler-equations</category><category>singularity</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Fermat's Last Theorem formalized end to end in Lean 4</title><link>https://whataifound.org/finding/2026-09-04-fermat-last-theorem-lean</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-04-fermat-last-theorem-lean</guid><pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate><description>A complete machine-checked proof of Fermat's Last Theorem in Lean 4, written by AI agents in eleven days, resting on Lean's three standard axioms and accepted by two independent kernels.  The repository states the theorem over Lean's built-in naturals as fermat_last_theorem, and its default build target FinalCheck.lean derives Mathlib's own FermatLastTheorem from it, so the statement is not a bespoke restatement. The build fails unless the proof depends on exactly propext, Classical.choice and Quot.sound: no sorry, no added axiom, no native_decide. Three checks are recorded. A from-scratch build compiled all 60,475 modules; leanprover/comparator v4.33.0 checked the result against a Mathlib-only Challenge.lean and returned 'Your solution is okay!'; and nanoda 0.4.13, an independent Lean kernel written in Rust, accepted an export of the same environment with 1,052,234 declarations and no errors. The argument formalized is the classical one of Frey, Serre, Ribet, Wiles and Taylor-Wiles, and the development builds on the Imperial College London FLT project, flt-regular and Mathlib, with 106 files containing material from the first two.  Lab: Anthropic. Model: Internal Anthropic research model, described in the announcement as roughly comparable to Claude Fable 5.1. Verification: Formally verified. Autonomy: AI-led.</description><category>number-theory</category><category>lean</category><category>formalization</category><category>fermat</category></item>
<item><title>Lean disproof of Krempa's matrix form of the Koethe conjecture</title><link>https://whataifound.org/finding/2026-09-03-koethe-conjecture-matrix-form</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-03-koethe-conjecture-matrix-form</guid><pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate><description>A machine-checked Lean proof refutes the matrix formulation that Krempa showed equivalent to the Koethe conjecture, found by a pre-release model with no human steering of the proof search.  Koethe asked in 1930 whether every ring has a largest nil left ideal. Krempa showed in 1972 that this is equivalent to several other statements, among them a statement about matrix ideals, and it is that matrix form which is disproved here. The proof was produced in Epoch AI's LeanOpenProblems harness, in an evaluation run over the 222 research-open statements of the Wikipedia collection of Google DeepMind's Formal Conjectures, at a pinned benchmark commit. The benchmark file states the conjecture and its negation, both with sorry, and the model fills in exactly one. The construction builds a nil algebra from three weighted backward shifts over the algebraic closure of the two-element field. The compared theorem depends on no sorry and on no axioms beyond propext, Quot.sound and Classical.choice.  Lab: OpenAI / Epoch AI. Model: GPT-6 Astra (pre-release). Verification: Formally verified. Autonomy: Autonomous.</description><category>algebra</category><category>ring-theory</category><category>lean</category><category>formalization</category><category>counterexample</category><category>construction</category></item>
<item><title>Erdos-Sos conjecture proved in Lean, in a form marginally weaker than the classical statement</title><link>https://whataifound.org/finding/2026-09-03-erdos-sos-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-03-erdos-sos-conjecture</guid><pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate><description>A machine-checked Lean proof establishes the Erdos-Sos conjecture in the benchmark's formalization, which in one parity case assumes one more edge than the classical statement requires.  Erdos and Sos conjectured in 1962 that a graph on n vertices with more than (k − 1)n/2 edges contains every tree on k + 1 vertices. The Lean development proves the benchmark's direct formalization, which states the hypothesis as at least (k − 1)n/2 + 1 edges. The proof uses a permutation-word counting argument over ordered host-vertex configurations. It was produced in the same Epoch AI LeanOpenProblems evaluation run as the Koethe disproof, one autonomous attempt per statement, and the compared theorem carries no sorry outside the statement stubs and no axioms beyond the three standard ones.  Lab: OpenAI / Epoch AI. Model: GPT-6 Astra (pre-release). Verification: Formally verified. Autonomy: Autonomous.</description><category>graph-theory</category><category>combinatorics</category><category>erdos</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Disputed claim that Catalan's constant is irrational</title><link>https://whataifound.org/finding/2026-09-03-catalan-constant-irrationality</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-03-catalan-constant-irrationality</guid><pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate><description>A preprint claims a proof that Catalan's constant is irrational, using weighted tails in the Calegari-Dimitrov-Tang framework; a specific technical objection to the argument has been raised publicly and is unresolved.  The irrationality of Catalan's constant is a long-standing open problem. The preprint adapts the method Calegari, Dimitrov and Tang used for the linear independence of 1, zeta(2) and L(2, chi_-3), replacing part of the arithmetic input with a construction of suitable weights and weighted tails. The acknowledgements set out an unusually specific division of labour: repeated attempts by the model failed, the author then supplied the weighting idea that made the approach work, and the model produced the numerical data. The paper states that 'the whole proof has passed the verification of Chatgpt 5.6 Solar', which is a machine reading rather than a human check.  Lab: Nanjing University. Model: ChatGPT 5.6 Solar, named in the paper as the verifier; the model consulted during the work is named only as AI. Verification: Disputed. Autonomy: AI-assisted.</description><category>number-theory</category><category>irrationality</category><category>disputed</category><category>argument</category></item>
<item><title>A quantum oracle separating QMA(2) from QMA</title><link>https://whataifound.org/finding/2026-09-02-qma2-oracle-separation</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-02-qma2-oracle-separation</guid><pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate><description>A quantum oracle is constructed relative to which QMA(2) differs from QMA, resolving Watrous's no-disentanglers conjecture, from a proof idea the authors state was generated by a language model.  The paper exhibits a quantum oracle relative to which QMA is not equal to QMA(2), and derives the no-disentanglers conjecture of Watrous: for every choice of error parameters summing to less than one, any disentangler requires input size exponential in the number of output qubits. The proof combines the unitarily invariant polynomial method of She and Yuen with a construction based on the symmetric and antisymmetric subspace projectors, reducing the QMA lower bound to the approximate degree of OR. The paper carries a section headed 'Tool and computational resource disclosure' which argues that AI-assisted research should record how findings were obtained, and then discloses the model's role.  Lab: MIT / Columbia / University of Washington. Model: ChatGPT 5.6 Sol. Verification: Author verified. Autonomy: AI-assisted.</description><category>quantum-computing</category><category>complexity-theory</category><category>oracle-separation</category><category>argument</category></item>
<item><title>Confirmation of the Daykin-Frankl conjecture from a language-model proof</title><link>https://whataifound.org/finding/2026-09-02-daykin-frankl-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-02-daykin-frankl-conjecture</guid><pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate><description>A four-page note verifies and communicates a language-model-generated proof of the 1983 Daykin-Frankl conjecture on incomparable elements in convex subsets of the Boolean lattice.  Daykin and Frankl conjectured in 1983 that a convex subset P of the n-dimensional Boolean lattice contains at least |P| times the central binomial coefficient divided by 2 to the n pairwise incomparable elements. The note's abstract states its provenance in one sentence: 'We verify and communicate an LLM-generated proof of this conjecture.' The argument proves a stronger product inequality for convex subsets and recovers the original conjecture as a special case, by an induction on dimension resting on a convexity lemma.  Lab: Independent. Model: GPT-5.6 Sol Pro. Verification: Author verified. Autonomy: AI-led.</description><category>combinatorics</category><category>boolean-lattice</category><category>order-theory</category><category>argument</category></item>
<item><title>A smooth counterexample to the Trautman conjecture</title><link>https://whataifound.org/finding/2026-09-02-trautman-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-02-trautman-conjecture</guid><pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate><description>A strongly pseudoconvex CR three-manifold is constructed that carries a nowhere-zero closed section of its canonical bundle yet is not locally embeddable, disproving the Trautman conjecture.  The Trautman conjecture asserted that a smooth three-dimensional CR manifold admitting a nowhere-zero closed section of its canonical bundle must be locally embeddable in complex two-space. The paper modifies a standard construction of nonembeddable smooth strongly pseudoconvex CR three-manifolds so that the closed-section condition is preserved, producing a strongly pseudoconvex counterexample. The construction proceeds through Hamiltonian perturbations of the Heisenberg CR structure, bump functions on shrinking solid tori and weighted moment identities, and is then globalized to the three-sphere.  Lab: Oklahoma State University. Model: ChatGPT Plus, version not named. Verification: Author verified. Autonomy: AI-assisted.</description><category>differential-geometry</category><category>cr-geometry</category><category>counterexample</category><category>construction</category></item>
<item><title>Lean proof that the percolation probability vanishes at the critical point in every dimension</title><link>https://whataifound.org/finding/2026-08-28-percolation-critical-point</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-28-percolation-critical-point</guid><pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate><description>A Lean development proves that nearest-neighbour Bernoulli bond percolation on the integer lattice has no infinite cluster at its critical parameter in every dimension at least two, which would settle the dimensions 3 to 10 that were open.  The development proves Kozma and Nitzan's Conjecture 3 (arXiv:2401.12397), which by their Theorem 6 gives that the percolation probability vanishes at the critical point on the d-dimensional integer lattice for every d at least 2. The route is a new conditioned slack hierarchy, a family of conditioned covariance inequalities for increasing functions of a single open cluster whose level-zero case is the Harris inequality, from which a stronger additive gluing inequality is derived. The classical inputs, including Harris, van den Berg, Haggstrom and Kahn, the four functions theorem, Gladkov's decision-tree Harris-Kleitman inequality, the Barsky, Grimmett and Newman half-space theorem and Kesten's critical value for the square lattice, are re-proved from Mathlib, so the statement carries no hypothesis beyond the dimension. The recorded audit reports a clean build, two sorry placeholders confined to the statement file by design, no added axioms, all seven compared theorems depending on exactly the three standard axioms, and a passing comparator run.  Lab: Anthropic. Model: Anthropic Claude models, versions not stated. Verification: Claimed. Autonomy: AI-led.</description><category>probability</category><category>percolation</category><category>lean</category><category>formalization</category><category>argument</category></item>
<item><title>Entropy production of the Boltzmann equation is not always monotone</title><link>https://whataifound.org/finding/2026-09-01-mckean-entropy-production</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-01-mckean-entropy-production</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Explicit radially symmetric mixtures of Maxwellians show the entropy production of the Boltzmann equation need not decrease monotonically, answering a question McKean asked in 1966.  In 1966 McKean asked whether the entropy production of the Boltzmann equation must be monotone decreasing in time. The paper shows it need not be, even in the space-homogeneous setting, for the Boltzmann collision operator with a constant angular cross section and kinetic parameter γ in the interval from 0 to 1. That range recovers the classical case of hard spheres and the simplest case of Maxwell molecules, so the counterexample reaches the two physically standard models rather than an exotic corner. The examples are radially symmetric mixtures of Maxwellians.  Lab: Independent. Model: GPT-5.6 Sol; Claude. Verification: Author verified. Autonomy: AI-led.</description><category>analysis</category><category>pde</category><category>mathematical-physics</category><category>counterexample</category></item>
<item><title>Common neighbour conjectures for Saxl graphs fail at every base size</title><link>https://whataifound.org/finding/2026-09-01-saxl-common-neighbour</link><guid isPermaLink="false">https://whataifound.org/finding/2026-09-01-saxl-common-neighbour</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Primitive permutation groups are constructed whose generalised Saxl graphs contain two nonadjacent vertices with no common neighbour, disproving the Burness-Giudici conjecture and its extension at every base size.  For a finite permutation group a base is a set of points with trivial pointwise stabiliser, and the generalised Saxl graph records which pairs of points lie together in a base of minimum size. Burness and Giudici conjectured that any two vertices of the Saxl graph of a primitive group of base size two have a common neighbour, and Freedman, Huang, Lee and Rekvényi extended this to arbitrary base size. Both are disproved: for each integer B at least 2 the paper constructs infinitely many primitive groups of base size B whose generalised Saxl graphs contain two nonadjacent vertices with no common neighbour. At base size two there are three further infinite families, one each of affine, product and twisted wreath type, so the conjecture fails in three of the five O'Nan-Scott types, and in the affine and product families the Saxl graphs have diameter exactly three. The result also answers Problem 21.29 of the Kourovka Notebook.  Lab: Independent. Model: Codex; ChatGPT Pro; Claude. Verification: Formally verified. Autonomy: Collaborative.</description><category>group-theory</category><category>combinatorics</category><category>counterexample</category><category>lean</category><category>formalization</category></item>
<item><title>Counterexample to the stable forking conjecture</title><link>https://whataifound.org/finding/2026-08-31-stable-forking</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-31-stable-forking</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>A simple first-order theory is constructed in which forking cannot always be witnessed by a stable formula, answering a question of Hart, Kim and Pillay open since 1996.  The stable forking conjecture asserts that in a simple theory, whenever a does not fork with b over C, there is a formula in the type of a over Cb that forks over C and whose parameter-free form is stable. The counterexample is an infinite-dimensional vector space over the division ring of fractions of the quantum graph algebra of the random graph. Forking is characterised through an abstract independence relation using the Kim-Pillay criteria, and the random graph is encoded into that relation so that it has the order property, which is what breaks stability.  Lab: Independent. Model: GPT-5.6 Sol. Verification: Author verified. Autonomy: Collaborative.</description><category>model-theory</category><category>logic</category><category>counterexample</category><category>construction</category></item>
<item><title>Unrestricted Boolean multiplicative complexity of four-term binary polynomial multiplication</title><link>https://whataifound.org/finding/2026-08-31-boolean-multiplicative-complexity-mul4</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-31-boolean-multiplicative-complexity-mul4</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Multiplying two four-term binary polynomials needs exactly nine AND gates even when nonlinear intermediate wires may be reused, with the whole result formalized in Lean 4.  Classical lower bounds show that multiplying two degree-three polynomials over the field with two elements needs nine scalar products in bilinear or quadratic models, but they leave open the unrestricted Boolean case, where an XOR-AND circuit may reuse nonlinear intermediate wires and equality is taken modulo the idempotence relations, so a multiplication can lower algebraic degree. The paper proves that the map producing the seven coefficients of the product of two four-term binary polynomials has unrestricted XOR-AND multiplicative complexity exactly nine. This resolves, for a natural vector-valued quadratic function, the Boyar-Find question of whether a quadratic-circuit lower bound survives unrestricted nonlinear reuse. The proof is structural rather than exhaustive, and the same argument gives multiplicative complexity six for three-term multiplication.  Lab: Independent. Model: GPT-5.6 Sol; Claude Opus 5. Verification: Formally verified. Autonomy: AI-assisted.</description><category>circuit-complexity</category><category>algorithms</category><category>lean</category><category>formalization</category></item>
<item><title>Criteria and two quadratic instances for Bugeaud's Problem 10.61</title><link>https://whataifound.org/finding/2026-08-31-pisot-cantor-equidistribution</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-31-pisot-cantor-equidistribution</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Covering criteria for a 1967 equidistribution problem of Mendès France are proved and applied to two quadratic Pisot cases, with Lean checking; the general problem stays open.  Bugeaud's Problem 10.61, due to Mendès France in 1967, asks whether for a Pisot number α and the associated Cantor set of base-α expansions with digits 0 and 1, no point of that Cantor set makes the sequence of its multiples by powers of α uniformly distributed modulo one. What the repository establishes is narrower than the problem: covering criteria for it, proved only for quadratic setups where α is a real root of a quadratic whose conjugate has modulus below one, together with two instances of that kind. Material for arbitrary degree is present but conditional, showing for one family that the large real root is Pisot with a conjugate-modulus bound.  Lab: Independent. Model: Claude Fable 5; Claude Opus 5. Verification: Claimed. Autonomy: AI-led.</description><category>number-theory</category><category>equidistribution</category><category>lean</category><category>partial-result</category></item>
<item><title>Dean's conjecture for k = 5, cycles of length divisible by five</title><link>https://whataifound.org/finding/2026-08-29-dean-conjecture-k5</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-29-dean-conjecture-k5</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>A preprint claims every finite simple graph of minimum degree at least five contains a cycle whose length is divisible by five, the last open case of Dean's 1988 conjecture.  Dean's conjecture asserts that every finite simple graph of minimum degree at least k contains a cycle of length divisible by k. The cases k = 3 and k = 4 were known, and Luo, Ma and Zhao proved every k at least 6, which left k = 5 as the single open case; if this proof stands, the conjecture holds for all k at least 3. Nine finite configuration propositions in the bipartite and triangle-free branches are computer-assisted, with verifier sources and certificate data archived in a separate computational supplement.  Lab: Independent. Model: GPT-5.6 Sol; Claude Opus 5; GLM 5.3 Flash. Verification: Claimed. Autonomy: AI-led.</description><category>graph-theory</category><category>combinatorics</category><category>computer-assisted</category><category>argument</category></item>
<item><title>Randomized metric distortion improved to 2.3282</title><link>https://whataifound.org/finding/2026-08-29-metric-distortion-23282</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-29-metric-distortion-23282</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>A randomized voting rule built on a new random-size stable lottery achieves metric distortion 2.3282, past a 2.5 barrier that existing arguments could not cross.  In metric social choice each voter ranks candidates by distance in an unknown metric space, a candidate's cost is its average distance to voters, and a randomized rule's distortion is the worst-case ratio between the expected cost of its lottery and that of the best candidate. Charikar, Ramakrishnan, Wang and Wu proved an upper bound of 2.753, and Frank and Ye independently improved it to 2.5 using an equal mixture of maximal lottery and Integrated Veto; existing arguments yield nothing better from any mixture of those two rules. The paper breaks that barrier with a new ingredient, a random-size stable lottery, reaching 2.3282.  Lab: Independent. Model: GPT-5.6 Sol; Claude Opus 5.0. Verification: Author verified. Autonomy: AI-led.</description><category>algorithms</category><category>social-choice</category><category>game-theory</category><category>argument</category></item>
<item><title>Hyperbolic surfaces with large systoles in every large genus</title><link>https://whataifound.org/finding/2026-08-27-large-systoles</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-27-large-systoles</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>For every sufficiently large genus there is a closed hyperbolic surface whose systole is at least log g − 12 log log g, raising the known asymptotic constant from 2/9 to 1.  For every sufficiently large genus g the note constructs a closed hyperbolic surface with systole at least log g − 12 log log g, which gives a lower bound of 1 for the limit inferior of the maximum systole over genus-g surfaces divided by log g, improving the previously known bound of 2/9. It continues the author's earlier work on the diameter of finite covers, using the same constant-twist pants decomposition framework applied to systoles instead.  Lab: Independent. Model: GPT-5.6 Sol. Verification: Author verified. Autonomy: AI-led.</description><category>geometry</category><category>hyperbolic-geometry</category><category>construction</category></item>
<item><title>Not every Heyting algebra is the subterminal lattice of a topos</title><link>https://whataifound.org/finding/2026-08-27-intuitionistic-higher-order-truth</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-27-intuitionistic-higher-order-truth</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>The free Heyting algebra on two generators cannot be the lattice of subterminal objects of an elementary topos, answering the question in the negative.  The question is whether every Heyting algebra arises as the lattice of subterminal objects of an elementary topos, which would say that intuitionistic propositional logic is fully realised by higher-order truth. The answer is no, and the witness is concrete: the free Heyting algebra on two generators cannot be such a lattice.  Lab: Independent. Model: ChatGPT 5.6 Sol. Verification: Author verified. Autonomy: AI-assisted.</description><category>logic</category><category>category-theory</category><category>counterexample</category></item>
<item><title>Supporting affine functionals for entanglement of formation need not exist</title><link>https://whataifound.org/finding/2026-08-27-entanglement-supporting-functional</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-27-entanglement-supporting-functional</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>An explicit two-qubit state has no global supporting affine functional for the entanglement of formation, contradicting an assumption used in several papers.  Several articles assume that the convex roof structure of the entanglement of formation together with finite-dimensional subsystems guarantees a global supporting affine functional at every state, meaning a Hermitian operator whose trace against the state gives the entanglement of formation and which lower-bounds it everywhere else. The paper gives an explicit counterexample at a degenerate state, in the simplest case where both subsystems are qubits. The construction rests on the equivalence between existence of such a supporting functional at a state and Lipschitz lower semicontinuity of the entanglement of formation there, and uses Wootters' closed formula to locate the state.  Lab: Independent. Model: Claude Fable 5. Verification: Author verified. Autonomy: AI-assisted.</description><category>quantum-information</category><category>entanglement</category><category>counterexample</category></item>
<item><title>Rapid mixing for spin systems on graphs of girth at least five</title><link>https://whataifound.org/finding/2026-08-26-spin-systems-girth-five</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-26-spin-systems-girth-five</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Glauber dynamics for proper q-colourings mixes rapidly once q exceeds the maximum degree by any fixed factor, provided the graph has girth at least five.  For every fixed positive δ, the Glauber dynamics on proper q-colourings is shown to mix rapidly when q is at least (1 + δ) times the maximum degree, the graph has girth at least five, and the maximum degree is large in terms of δ. The result extends to general multi-spin systems satisfying a local spectral contraction condition, including the anti-ferromagnetic Potts model. The engine is a new spectral local-to-global principle for multi-spin systems on graphs of girth at least five, together with a Fourier analysis for Glauber dynamics on a star.  Lab: Independent. Model: GPT-5.6 Sol Ultra. Verification: Author verified. Autonomy: Collaborative.</description><category>algorithms</category><category>sampling</category><category>markov-chains</category><category>combinatorics</category><category>argument</category></item>
<item><title>Improved lower bound for large gaps between consecutive primes</title><link>https://whataifound.org/finding/2026-08-25-erdos-4-prime-gaps</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-25-erdos-4-prime-gaps</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>A new sieving construction raises the record lower bound on how large the gap between consecutive primes becomes infinitely often, the first advance on Erdős Problem #4 since 2018.  Writing G(T) for the largest gap between consecutive primes below T, the record since Ford, Green, Konyagin, Maynard and Tao (2018) has been G(T) ≫ log T log₂ T log₄ T/log₃ T, where logₖ is the k-fold iterated logarithm. The manuscript claims G(T) ≫ log T log₂ T/log₄ T, a gain of log₃ T/(log₄ T)², together with Y(X) ≫ X log X/log₃ X for the covering problem behind it. What is new is narrow and specific: the intermediate sieve is replaced, its hard cutoff smoothed into a probabilistic tilt, while the hypergraph covering theorem and the Maynard weight are carried over unchanged from the 2018 paper. Ben Green, a co-author of the bound being beaten, describes the sieving procedure as different from the Erdős-Rankin one that underpinned every bound on the problem since 1938.  Lab: Independent. Model: GPT-5.6 Sol. Verification: Independently checked. Autonomy: AI-led.</description><category>number-theory</category><category>erdos</category><category>prime-gaps</category><category>sieve-methods</category><category>construction</category></item>
<item><title>Sparse domination implies convex body domination</title><link>https://whataifound.org/finding/2026-08-25-sparse-convex-body-domination</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-25-sparse-convex-body-domination</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Any bilinear form with a sparse bound has a convex body sparse bound for its vector-valued extension, answering a question about the relation between the two notions.  If a bilinear form admits an (r,s)-sparse bound, then its coordinate-wise extension to functions valued in complex n-space admits an (r,s)-convex body sparse bound. The proof rests on a randomization argument, and the result is established both for sparse families in a fixed dyadic lattice and for sparse families of arbitrary cubes. As an application the authors deduce sparse domination for iterated commutators, with the local oscillations of the symbol appearing in the sparse form.  Lab: Independent. Model: GPT-5.6 Sol Pro. Verification: Author verified. Autonomy: AI-assisted.</description><category>analysis</category><category>harmonic-analysis</category><category>argument</category></item>
<item><title>Equivalence of generic stability notions for Keisler measures</title><link>https://whataifound.org/finding/2026-08-25-generically-stable-keisler</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-25-generically-stable-keisler</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Three candidate definitions of generic stability for a Borel-definable global Keisler measure are shown to be equivalent, closing a research objective left open by earlier work.  For a first-order theory in discrete or continuous logic and a Borel-definable global Keisler measure, the paper shows three conditions equivalent: that the measure is a frequency interpretation measure, that it is definable and its canonical random extension is generically stable in the randomization theory, and that it is self-averaging. The forward implications were already established by the same authors for discrete theories; the paper's contribution is the two reverse implications, which is what makes the notion of generic stability robust and settles a long-term objective from that earlier work.  Lab: Independent. Model: ChatGPT 5.5; ChatGPT 5.6 Sol; Kimi K3; Claude Fable 5. Verification: Author verified. Autonomy: AI-led.</description><category>model-theory</category><category>logic</category><category>argument</category></item>
<item><title>Fröberg's conjecture for quintics and septics in four variables</title><link>https://whataifound.org/finding/2026-08-25-froberg-quintics-septics</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-25-froberg-quintics-septics</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Fröberg's predicted Hilbert series is proved for ideals generated by any number of general forms of degree five or seven in four variables.  Over a field of characteristic zero in four variables, the paper proves Fröberg's predicted Hilbert series for ideals generated by r general forms of equal degree d, for every r at least 1, in the two cases d = 5 and d = 7. Against the classical cases r at most 5 and the equal-degree theorem of Boij, Dannetun and Lundqvist through degree d + 2, the ranges needing new input are r between 6 and 11 for quintics and 6 and 21 for septics. Each slice reduces to finitely many endpoint ranks of Macaulay multiplication matrices: ten exact endpoint computations from twenty-one sparse forms for quintics, and fifteen from a nested family of 120 integral forms for septics, with every endpoint certificate recording an explicit maximal minor that is nonzero modulo 2 and hence a nonzero integer.  Lab: Independent. Model: GPT-5.6 Sol; Claude Fable 5; Grok 4.6. Verification: Author verified. Autonomy: Collaborative.</description><category>algebra</category><category>commutative-algebra</category><category>computer-assisted</category></item>
<item><title>Optimal linear encoding rate for lossy compression of Bernoulli sources</title><link>https://whataifound.org/finding/2026-08-24-ancheta-massey-linear-coding</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-24-ancheta-massey-linear-coding</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Ancheta's answer to Massey's question about linear encoders for lossy compression is extended from the fair-coin case to every source bias below one half.  Linear encoders achieve the entropy for lossless compression of a Bernoulli source, but for lossy compression linearity is known to be strictly suboptimal against the rate-distortion function. Massey asked in 1978 whether the optimal rate for linear encoding is achieved simply by compressing a fraction of the bits linearly and losslessly and estimating the rest by zero. Ancheta answered yes for bias one half in the same year, and this note extends that to every bias below one half. The key step bounds the entropy of the posterior distribution conditioned on an affine subspace in terms of its marginals.  Lab: Independent. Model: GPT-5.6 Sol. Verification: Author verified. Autonomy: AI-led.</description><category>information-theory</category><category>coding-theory</category><category>argument</category></item>
<item><title>Elliptic curves over the rationals of rank at least 30 and at least 31</title><link>https://whataifound.org/finding/2026-08-23-elliptic-rank-31</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-23-elliptic-rank-31</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Two explicit elliptic curves over the rationals carry 30 and 31 independent rational points, raising the Mordell-Weil rank record twice in four days.  Whether the Mordell-Weil rank of an elliptic curve over the rationals is bounded is open, and progress is measured by explicit records: rank at least 28 from 2006, raised to at least 29 by Elkies and Klagsbrun in 2024. Curve 273 on the elliptic-rank leaderboard reaches rank at least 30 on 2026-08-20 and curve 302 reaches at least 31 on 2026-08-23, each witnessed by explicit independent points. The method is the human Elkies-Klagsbrun elliptic-K3 family search, with the model assisting inside it. Both entries are recorded as two tiers: the lower bound is what the explicit points establish, while exact rank is claimed only conditionally on the Birch-Swinnerton-Dyer conjecture and the generalized Riemann hypothesis.  Lab: Independent. Model: Claude. Verification: Claimed. Autonomy: AI-assisted.</description><category>number-theory</category><category>elliptic-curves</category><category>record</category><category>search</category></item>
<item><title>Transcendence in the affine case of Erdős Problem 270</title><link>https://whataifound.org/finding/2026-08-22-erdos-270-affine-transcendence</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-22-erdos-270-affine-transcendence</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>The series in Erdős Problem 270 is claimed transcendental for every positive integer-valued affine choice of the defining function.  Erdős Problem 270 concerns the series whose n-th term is 1 over the product of the f(n) consecutive integers starting at n + 1. For the affine choice f(n) = an + b this is the sum of n!/((a + 1)n + b)!, and the manuscript claims that constant is transcendental for every a at least 1 and b at least 1 − a, settling the positive integer-valued affine subclass. It also determines the algebraic structure of the family at each fixed slope, and ships a Lean development covering part of the argument.  Lab: Independent. Model: GPT-5.6 Sol (Codex). Verification: Claimed. Autonomy: AI-led.</description><category>number-theory</category><category>erdos</category><category>transcendence</category><category>lean</category></item>
<item><title>Stable commutator length of a relator is not a one-relator group invariant</title><link>https://whataifound.org/finding/2026-08-21-scl-relator-invariance</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-21-scl-relator-invariance</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Two explicit words give isomorphic one-relator groups whose relators have different stable commutator lengths, answering a question of Heuer and Loh in the negative.  For the two explicit words r = aabABabABBAbaabABBAb and r′ = aabABabABabABBAbaBAb, both lying in the commutator subgroup of the free group on a and b, the one-relator groups presented by r = 1 and by r′ = 1 are isomorphic, while r and r′ have different stable commutator lengths. That combination is exactly the negative answer to the question of Heuer and Loh, since it shows the stable commutator length of the relator is not determined by the group it presents.  Lab: Independent. Model: Claude Opus 5; Harmonic Aristotle. Verification: Author verified. Autonomy: AI-assisted.</description><category>group-theory</category><category>geometric-group-theory</category><category>counterexample</category><category>computer-assisted</category></item>
<item><title>Counterexample to the bounded mass property on the Hopf threefold</title><link>https://whataifound.org/finding/2026-08-21-bounded-mass-property</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-21-bounded-mass-property</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>The bounded mass property fails on the Hopf threefold, answering a question of Boucksom, Guedj and Lu.  A compact complex manifold has the bounded mass property if, for one and equivalently every Hermitian form, the masses of the n-th power of that form plus a ddᶜ-exact perturbation stay uniformly bounded over all smooth potentials keeping the form positive. The paper shows this fails on the Hopf threefold, the quotient of punctured complex three-space by the map sending z to e⁻¹z, which answers a question of Boucksom, Guedj and Lu in the negative.  Lab: Independent. Model: Rethlas agent (GPT-5.6 Sol). Verification: Author verified. Autonomy: AI-led.</description><category>geometry</category><category>complex-geometry</category><category>counterexample</category></item>
<item><title>A smooth random fast dynamo on the three-torus</title><link>https://whataifound.org/finding/2026-08-20-fast-dynamo-three-torus</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-20-fast-dynamo-three-torus</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>A random smooth divergence-free velocity field on the three-torus is constructed whose magnetic field grows exponentially at a rate bounded below independently of the resistivity.  The construction is a random, time-dependent, divergence-free velocity field on the three-torus, refreshing independently on finite time blocks and obeying deterministic smooth bounds in space and time, which exhibits fast dynamo behaviour: for every sufficiently small fixed resistivity the almost sure exponential growth rate of the magnetic field solving the linear resistive induction equation is at least one half. The argument turns on an algebraic structure in Fourier space of the induction equation solution operator that lets the expected growth of the logarithmic size of three chosen Fourier modes be propagated, reducing the problem to a simple recursion and avoiding the infinite-dimensional dynamics usually involved.  Lab: Independent. Model: ChatGPT 5.6 Sol Ultra. Verification: Author verified. Autonomy: AI-led.</description><category>analysis</category><category>pde</category><category>probability</category><category>construction</category></item>
<item><title>Counterexamples to the fractional colouring conjecture for Pauli shadow tomography</title><link>https://whataifound.org/finding/2026-08-20-pauli-fractional-colouring</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-20-pauli-fractional-colouring</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>The fractional chromatic number of the anticommutation graph of large-expectation Pauli observables is not bounded by a constant over ε², removing a proposed route to triply efficient shadow tomography.  Fractional graph colourings are used in shadow tomography of Pauli observables, and it is desirable that any experimentally interesting set of Pauli operators have a small fractional chromatic number for its anticommutation graph. Conjecture 13 of King, Gosset, Kothari and Babbush states that for the set of Pauli observables whose expectation value in a given state has magnitude at least ε, the fractional chromatic number of the induced anticommutation graph is O(ε⁻²). The paper gives counterexamples, so no such constant exists; had the conjecture held it would have implied a triply efficient Pauli shadow tomography algorithm for any subset of Pauli observables given an efficient fractional colouring algorithm.  Lab: Independent. Model: GPT-5.6 Sol. Verification: Author verified. Autonomy: Collaborative.</description><category>quantum-information</category><category>combinatorics</category><category>counterexample</category></item>
<item><title>Counterexample to the smooth Carathéodory conjecture on umbilic points</title><link>https://whataifound.org/finding/2026-08-19-caratheodory-umbilic</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-19-caratheodory-umbilic</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>An explicit support function gives a smoothly embedded two-sphere bounding a convex body with exactly one umbilic point, so the C^(∞) form of Carathéodory's 1922 conjecture is false.  Carathéodory's conjecture, Problem 8.1 of Ghomi's list and traceable to 1922, asks whether every closed convex surface in ℝ³ carries at least two umbilic points. Hamburger settled the real-analytic case in 1940-41 and that theorem is untouched. The counterexample is explicitly a C^(∞) object: an explicit support function produces a smoothly embedded two-sphere bounding a convex body with exactly one umbilic point. The same family disproves the smooth Loewner conjecture, whose member at k = 1 has an isolated trace-free Hessian zero of the wrong index. The gap between the smooth and the real-analytic case is the whole content of the result.  Lab: Independent. Model: Claude; Codex. Verification: Claimed. Autonomy: AI-assisted.</description><category>geometry</category><category>differential-geometry</category><category>counterexample</category><category>lean</category><category>construction</category></item>
<item><title>First open case of the big-line-big-clique conjecture</title><link>https://whataifound.org/finding/2026-08-19-big-line-big-clique</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-19-big-line-big-clique</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Every finite point set of size at least 10¹¹⁰⁵⁵⁹³¹ contains four collinear points or six points that pairwise see each other, settling the first open case of the Kára-Pór-Wood conjecture.  The big-line-big-clique conjecture of Kára, Pór and Wood asserts that for all k and l there is an n such that every finite point set of at least n points contains l collinear points or k points that pairwise see each other, where two points see each other if no other point of the set lies between them. The paper proves the case l = 4, k = 6, the first case left open, with the explicit and very large threshold 10¹¹⁰⁵⁵⁹³¹. The proof combines a lower bound on distance to 5-colorability, a Turán-type stability and edge-density argument, and matching harmonic upper and lower bounds.  Lab: Independent. Model: GPT-5.6 Sol Pro. Verification: Author verified. Autonomy: AI-led.</description><category>combinatorics</category><category>discrete-geometry</category><category>argument</category></item>
<item><title>Counting linear extensions below the 2ⁿ barrier</title><link>https://whataifound.org/finding/2026-08-19-linear-extensions-below-2n</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-19-linear-extensions-below-2n</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>A deterministic algorithm counts the linear extensions of an arbitrary n-element poset in time O^*(1.89ⁿ), breaking the 2ⁿ barrier for the general problem.  A linear extension of a finite poset is a total order respecting it. The algorithm counts them exactly for an arbitrary n-element poset in O^*(1.89ⁿ) time, resolving a question posed by Koivisto at Dagstuhl in 2013. It refines an argument of Kozma for two-dimensional posets: a chain partition handles posets far from an antichain, and otherwise a maximum antichain is fixed and only the first comparable element above each of its elements is recorded, with a decoding lemma enumerating the resulting patterns from their multiplicities. Once a pattern is fixed each antichain element has a release condition and at most one deadline, so the dynamic program need only store how many elements are released in each deadline class.  Lab: Independent. Model: Claude Opus 5; ChatGPT 5.6 Sol. Verification: Author verified. Autonomy: AI-led.</description><category>algorithms</category><category>combinatorics</category><category>exact-algorithms</category></item>
<item><title>Erdős Problem #501 shown independent of ZFC, with both directions in Lean</title><link>https://whataifound.org/finding/2026-08-19-erdos-501-independence</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-19-erdos-501-independence</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>The first question of Erdős Problem #501 is proved independent of ZFC, and both directions are formalized in Lean 4 as statements about the theory ZFC itself.  Erdős Problem #501 asks, for a family of bounded sets of outer measure less than 1 indexed by the reals, whether there must be an infinite independent set, meaning an infinite set of reals none of which lies in the set indexed by another. The answer is independent of ZFC: the continuum hypothesis gives a counterexample by Hechler's 1972 construction, while adding more than continuum-many random reals gives a positive answer. Both directions are formalized, and the independence is stated inside Mathlib's own first-order logic, with the theory ZFC and a sentence Erdős501 defined in a file importing Mathlib only, so that non-provability and non-refutability are themselves proved from the standard axioms. A further target certifies the rendering is faithful by showing the sentence is equivalent in Mathlib's ZFSet to the formalized statement of the question.  Lab: Independent. Model: Sol; Claude. Verification: Formally verified. Autonomy: Collaborative.</description><category>set-theory</category><category>erdos</category><category>lean</category><category>formalization</category><category>forcing</category></item>
<item><title>The DeLaViña-Waller conjecture on the Wiener index</title><link>https://whataifound.org/finding/2026-08-19-delavina-waller-wiener</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-19-delavina-waller-wiener</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>Every connected graph on 2d + 1 vertices of diameter d at least 3 is claimed to have Wiener index at most that of the cycle on the same number of vertices, with the equality cases determined.  The conjecture of DeLaViña and Waller states that a finite simple connected graph on 2d + 1 vertices with diameter exactly d at least 3 has Wiener index, the sum of all pairwise distances, at most that of the odd cycle on 2d + 1 vertices. The preprint claims a proof and pins down the equality cases: the odd cycle for every d at least 3, plus the double star D(2, 3) when d = 3 and the nine-vertex tree S(2, 3, 3) when d = 4.  Lab: Independent. Model: GPT-5.6 Sol; Claude Fable 5. Verification: Author verified. Autonomy: AI-assisted.</description><category>graph-theory</category><category>combinatorics</category><category>argument</category></item>
<item><title>Partial proof of the Kasami APN triple-count conjecture, verified in Lean</title><link>https://whataifound.org/finding/2026-08-19-kasami-apn-triple-counts</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-19-kasami-apn-triple-counts</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>A conjecture from a 2019 cryptography olympiad on triple counts for the Kasami almost perfect nonlinear function is proved in four residue cases and verified exhaustively for small field degrees, with every proof machine-checked.  For the Kasami almost perfect nonlinear function on a binary field, the conjecture concerns a set built from the function's second difference and asserts that, for any two distinct nonzero elements, the number of triples in that set satisfying a fixed linear relation is exactly 2^(2n − 3). The paper proves this when k modulo n lies in the set {1, 2, n − 2, n − 1}, including a complete proof for k = 2 via quadratic-form theory and an exact root-count reduction, and verifies the conjecture exhaustively by computer for every admissible pair with n at most 13. It also corrects one hypothesis in the supporting facts supplied with the original problem, concerning the Müller-Cohen-Matthews permutation.  Lab: Independent. Model: Claude Fable 5; Harmonic Aristotle. Verification: Formally verified. Autonomy: AI-led.</description><category>number-theory</category><category>finite-fields</category><category>cryptography</category><category>lean</category><category>formalization</category></item>
<item><title>Separation between the ordinary and strong Kreiss constants</title><link>https://whataifound.org/finding/2026-08-06-kreiss-constant-separation</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-06-kreiss-constant-separation</guid><pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate><description>A negative solution to the inverse generator problem on Hilbert spaces yields an operator whose Cayley transforms satisfy the ordinary Kreiss condition but are neither strongly Kreiss bounded nor power bounded.  The paper constructs a bounded operator with dense range on a Hilbert space that generates a bounded, strongly stable C0-semigroup while its inverse generates no C0-semigroup, which answers the inverse generator problem in the negative. It also builds an exponentially stable generator with 0 in the resolvent set whose inverse semigroup is unbounded and grows at least double logarithmically; for that generator every Cayley transform satisfies the ordinary Kreiss resolvent condition but is neither strongly Kreiss bounded nor power bounded, which separates the two notions. A numerical consequence follows: the Crank-Nicolson scheme is unstable in operator norm both for every fixed step size over long times and under mesh refinement at any fixed final time. All counterexamples are deduced from a common finite-dimensional construction.  Lab: Independent. Model: ChatGPT 5.6 Pro; Claude Fable. Verification: Author verified. Autonomy: AI-assisted.</description><category>analysis</category><category>operator-theory</category><category>counterexample</category><category>lean</category></item>
<item><title>Counterexample to Nevanlinna's half-plane omitted-values question</title><link>https://whataifound.org/finding/2026-08-26-nevanlinna-half-plane</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-26-nevanlinna-half-plane</guid><pubDate>Mon, 31 Aug 2026 00:00:00 +0000</pubDate><description>An explicit meromorphic function omits three values in a half-plane without being of bounded type there, answering in the negative a question of Nevanlinna open for more than a century.  A meromorphic function on a domain is of bounded type if it is a quotient of two bounded holomorphic functions. Nevanlinna asked whether omitting three values on a half-plane forces bounded type there. The paper constructs a function omitting 0, 1 and ∞ whose a-point divisor fails the Blaschke condition in each half-plane, which is exactly the negation, and notes that postcomposition gives the same conclusion for any prescribed triple of distinct values on the Riemann sphere. The construction runs through a modular covering, a comparison domain and a Farey-edge boundary with Schwarz reflection.  Lab: Independent. Model: GPT-5.6 Sol Ultra. Verification: Author verified. Autonomy: AI-led.</description><category>complex-analysis</category><category>value-distribution</category><category>counterexample</category><category>construction</category></item>
<item><title>Improved algebraic construction for off-diagonal Ramsey numbers</title><link>https://whataifound.org/finding/2026-08-25-ramsey-algebraic-construction</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-25-ramsey-algebraic-construction</guid><pubDate>Mon, 31 Aug 2026 00:00:00 +0000</pubDate><description>A finite-geometry construction supplied by a language model, then reworked by the authors, improves the explicit lower bound for off-diagonal Ramsey numbers.  The authors set out to use p-rank arguments on constructions in finite geometry to push the explicit lower bound for off-diagonal Ramsey numbers. The first construction, a graph on the points of a projective space with adjacency given by a trace condition, came from the model together with a bound on its clique number resting on algebraic geometry. The authors then developed and refined it into the published construction, which gives a bound of the form R(s, t) ≥ t^((1 − o(1))log s/log(log s + 1)). The paper describes the underlying idea as a deterministic analogue of random sampling in finite-geometric settings.  Lab: Independent. Model: ChatGPT 5.6. Verification: Author verified. Autonomy: AI-assisted.</description><category>combinatorics</category><category>ramsey-theory</category><category>finite-geometry</category><category>construction</category></item>
<item><title>Dimension-free weak-type bound for the vector Riesz transform</title><link>https://whataifound.org/finding/2026-08-18-stein-riesz-weak-type</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-18-stein-riesz-weak-type</guid><pubDate>Mon, 31 Aug 2026 00:00:00 +0000</pubDate><description>The best constant in the weak-type (1,1) bound for the vector Riesz transform on n-dimensional space is at most 2 whatever the dimension, answering a question Stein raised in 1986.  Dimension-free bounds for Riesz transforms are known in the strong-type range, and Stein asked at the 1986 ICM whether the weak-type (1,1) endpoint behaves the same way. The paper answers yes with an explicit constant: the best weak-type (1,1) constant for the vector Riesz transform is at most 2, independent of n. The proof goes through a new decomposition of the input data rather than through the torus-transference route the models first proposed, which the authors judged more complicated than necessary and replaced with a direct argument in Euclidean space.  Lab: Independent. Model: GPT-5.6 Sol and Claude Opus 5.0, with Danus and Rethlas agents. Verification: Author verified. Autonomy: Collaborative.</description><category>harmonic-analysis</category><category>riesz-transforms</category><category>argument</category></item>
<item><title>A complex structure on the six-sphere</title><link>https://whataifound.org/finding/2026-08-23-s6-complex-structure</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-23-s6-complex-structure</guid><pubDate>Tue, 25 Aug 2026 00:00:00 +0000</pubDate><description>An explicit compact complex threefold, built as a family of 2-tori over the (3, 4, ∞) orbifold, is diffeomorphic to the six-sphere, which settles the question Hopf raised in 1948 of whether the six-sphere admits a complex structure.  Whether the six-sphere admits a complex structure is the surviving case of a question going back to Hopf: the two-sphere and the six-sphere are the only spheres carrying an almost complex structure, and only the six-dimensional case is open. The manuscript builds a threefold X fibred over the projective line by complex 2-tori, using the period functions of the (3, 4, ∞) triangle group, degenerating to a degree-six del Pezzo fibre at one special point and to bielliptic multiple fibres of multiplicities 3 and 4 at the other two. It argues that X is simply connected with the integral homology of the six-sphere, hence diffeomorphic to it, and that its algebraic dimension is exactly 1. That last number is where the paper collides with the literature, and it says so itself rather than passing over it.  Lab: Anthropic. Model: Claude, version not stated. Verification: Independently checked. Autonomy: AI-assisted.</description><category>complex-geometry</category><category>differential-geometry</category><category>hopf-problem</category><category>construction</category><category>contested</category></item>
<item><title>Dubickas's question on integral parts of powers of square roots settled</title><link>https://whataifound.org/finding/2026-08-21-dubickas-square-roots</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-21-dubickas-square-roots</guid><pubDate>Tue, 25 Aug 2026 00:00:00 +0000</pubDate><description>The square root of 3 admits a real multiplier making every integral part of its powers even, and among integers only the square root of 2 fails to, answering a question Dubickas posed in 2006 and classifying the whole square-root case.  Dubickas splits the reals above 1 into two classes: α lies in Z when some nonzero real ξ makes every integral part ⌊ξαⁿ⌋ even, and in S otherwise. At α = 3/2 this is Mahler's question and still open; his Problem 3 asks which class contains √3. The answer is that it lies in Z, by an explicit multiplier near 1.3416, and the argument classifies the entire square-root slice: for an integer m at least 2, √m lies in S exactly when m is 2. A further theorem in the paper replaces parity by divisibility by any integer p at least 2.  Lab: Independent. Model: Claude Fable 5 and Claude Opus 5. Verification: Formally verified. Autonomy: AI-led.</description><category>lean</category><category>formalization</category><category>number-theory</category><category>z-numbers</category><category>argument</category></item>
<item><title>A prescribed Hamiltonian cycle that a book-embedding algorithm cannot produce</title><link>https://whataifound.org/finding/2026-08-11-prescribed-cycle-recovery</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-11-prescribed-cycle-recovery</guid><pubDate>Tue, 25 Aug 2026 00:00:00 +0000</pubDate><description>A 16-vertex graph carries a Hamiltonian cycle that the Alam et al. book-embedding algorithm cannot return for any choice of dual spanning tree, answering a question of Bekos, Kaufmann and Pfister in the negative.  Bekos, Kaufmann and Pfister asked whether every prescribed Hamiltonian cycle of a Barnette graph can be recovered from the book-embedding algorithm of Alam and co-authors by choosing the dual spanning tree appropriately. The answer is no. The paper exhibits an explicit 16-vertex Barnette graph whose Hamiltonian cycle has a complementary perfect matching meeting all three edge-colour classes of the simultaneous edge and face colouring the algorithm uses. Every output of the algorithm contains each edge designated green, whatever spanning tree is chosen, and the prescribed cycle omits a green edge under every global colour labelling, so no run can produce it. Note what is not being claimed: the graph satisfies Barnette's conjecture and is Hamiltonian. What fails is the algorithm's ability to reach a particular cycle, not the conjecture.  Lab: Independent. Model: OpenAI Codex, with Claude for adversarial review. Verification: Formally verified. Autonomy: AI-assisted.</description><category>lean</category><category>formalization</category><category>graph-theory</category><category>book-embedding</category><category>algorithms</category><category>construction</category></item>
<item><title>Marton's inner bound shown not to reach the broadcast channel capacity region</title><link>https://whataifound.org/finding/2026-08-20-marton-inner-bound</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-20-marton-inner-bound</guid><pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate><description>There are discrete memoryless broadcast channels whose capacity region is strictly larger than Marton's inner bound, settling in the negative a question open since 1979.  Marton's inner bound has been the best known achievable region for the general two-receiver discrete memoryless broadcast channel since 1979, and whether it is tight has been the central open question of the area. The paper exhibits channels whose capacity strictly exceeds it. The route ran through a related conjecture: the authors first found counterexamples to the Markovity conjecture of Gohari, Liu and Nair, then built a local tensorization test for a ternary-component broadcast channel, developed that into a counterexample to the additivity conjecture, and finally into an unconstrained counterexample to Marton's region. The violation gaps are small, of order ten to the minus six, and are certified with interval arithmetic.  Lab: Independent. Model: GPT-5.6 Sol, Claude Fable 5 and Claude Opus 5. Verification: Author verified. Autonomy: AI-assisted.</description><category>information-theory</category><category>broadcast-channel</category><category>counterexample</category><category>construction</category></item>
<item><title>Counterexample to the Yau–Tian–Donaldson conjecture for constant scalar curvature metrics</title><link>https://whataifound.org/finding/2026-08-19-yau-tian-donaldson</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-19-yau-tian-donaldson</guid><pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate><description>A smooth polarized fivefold that is K-polystable but admits no constant scalar curvature Kähler metric, disproving the form of the Yau–Tian–Donaldson conjecture that Donaldson stated in 2002.  Donaldson conjectured in 2002 that a smooth polarized variety carries a constant scalar curvature Kähler metric exactly when it is K-polystable, the general-polarization successor to the Kähler-Einstein expectation going back to Yau and to Tian's K-stability. This 79-page paper constructs a polarized smooth projective fivefold, proves it K-polystable against all normal ample algebraic test configurations of every positive exponent, and shows it carries no such metric. Its appendix draws a distinction worth keeping: some counterexamples reduce to a finite certificate checkable once the object is written down, as the Jacobian conjecture counterexample does, while others are themselves theorems quantified over everything, and this is the second kind. Candidate manifolds of this shape have been available since 2008; the mathematical content is the classification showing every test configuration has nonnegative Donaldson-Futaki invariant with equality only for products.  Lab: Independent. Model: Claude Fable 5, GPT-5.6-sol and Danus. Verification: Author verified. Autonomy: Collaborative.</description><category>algebraic-geometry</category><category>differential-geometry</category><category>k-stability</category><category>counterexample</category><category>construction</category></item>
<item><title>Bounded prime gaps of 246 formalized in Lean from Bombieri-Vinogradov</title><link>https://whataifound.org/finding/2026-08-18-prime-gaps-246</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-18-prime-gaps-246</guid><pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate><description>A machine-checked Lean development proves that infinitely many pairs of primes differ by at most 246, taking the Bombieri-Vinogradov theorem as a hypothesis rather than proving it.  The 246 bound is the closest mathematics has come to the twin prime conjecture: Zhang broke the bounded-gaps barrier in 2013, Maynard's multidimensional sieve brought it to 600, and the Polymath8b collaboration tightened that to 246 in 2014. This project formalizes the majority of Maynard's paper together with the Polymath8b extension, in Lean 4 on top of Mathlib and the PrimeNumberTheoremAnd development led by Kontorovich and Tao. AxiomProver generated machine-checkable proofs which human formalisers at Axiom Math then curated and librarized into PrimeGapsLib, released as reusable infrastructure. The mathematics is not new; the machine-checked proof of it is.  Lab: Axiom Math. Model: AxiomProver. Verification: Formally verified. Autonomy: Collaborative.</description><category>lean</category><category>formalization</category><category>number-theory</category><category>prime-gaps</category><category>sieve-methods</category></item>
<item><title>Matrix multiplication exponent lowered to below 2.371177</title><link>https://whataifound.org/finding/2026-08-17-matmul-exponent</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-17-matmul-exponent</guid><pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate><description>A reformulated optimization inside the laser method, with AlphaEvolve applied as the final refinement, lowers the best known upper bound on the matrix multiplication exponent from 2.371339 to 2.371177.  The best bounds on the matrix multiplication exponent come from combination loss analysis, a refinement of the laser method. The paper makes three changes to the optimization at its core, and AlphaEvolve is only the third: first the problem is reformulated so it can be solved over a larger space than was previously tractable, then a new optimization algorithm is designed using recent machine-learning methods, and then that algorithm is refined with AlphaEvolve. The combination gives an upper bound of 2.371177 against a previous best of 2.371339. The paper is a note reporting a record, not a structural advance: whether the exponent equals 2 is untouched, and nothing here suggests the laser method can reach it.  Lab: Google DeepMind. Model: AlphaEvolve. Verification: Author verified. Autonomy: Search scaffold.</description><category>alphaevolve</category><category>algorithms</category><category>matrix-multiplication</category><category>complexity</category><category>computation</category></item>
<item><title>Talagrand's convolution conjecture proved on the Boolean hypercube</title><link>https://whataifound.org/finding/2026-08-16-talagrand-convolution</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-16-talagrand-convolution</guid><pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate><description>Convolution by a measure on the Boolean hypercube obeys the dimension-free weak-type decay Talagrand conjectured in 1989, removing the iterated-logarithm factor carried by the best previous bound.  For the Boolean hypercube with uniform measure and convolution by a finite positive measure, Talagrand conjectured that the anti-concentration profile decays like 1/√(log u), with a constant free of the dimension. Yuansi Chen reached that decay in November 2025 up to an additional log log factor, using a perturbed reverse heat flow. This paper reworks the endpoint comparison so that the exponent has a fixed numerator, which removes the need for a growing stopping buffer and with it the log log factor, giving the conjectured bound.  Lab: Independent. Model: Odin Automatic AI Research Agent. Verification: Author verified. Autonomy: AI-led.</description><category>probability</category><category>boolean-analysis</category><category>concentration</category><category>argument</category></item>
<item><title>Banach's isometric conjecture settled in the remaining odd dimensions</title><link>https://whataifound.org/finding/2026-08-13-banach-isometric</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-13-banach-isometric</guid><pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate><description>A real Banach space whose n-dimensional subspaces are all isometric to one another must be a Hilbert space for every odd n, which together with Gromov's even-dimensional theorem closes a question Banach asked in 1932.  Banach asked in 1932 whether a real Banach space X all of whose n-dimensional subspaces are isometric, for some fixed n strictly between 1 and the dimension of X, has to be a Hilbert space. Gromov settled every even n, and later work closed several odd cases, leaving a gap. This 21-page paper proves the remaining odd n, combining bundle topology with Brouwer degree theory, which completes the conjecture in the real case. The complex case is not addressed.  Lab: Independent. Model: ChatGPT 5.5 Pro, ChatGPT 5.6 Pro and GPT-5.6 Sol. Verification: Author verified. Autonomy: AI-assisted.</description><category>functional-analysis</category><category>banach-spaces</category><category>argument</category><category>geometry</category></item>
<item><title>An antibiotic designed by reinforcement learning clears an MRSA infection in mice</title><link>https://whataifound.org/finding/2026-04-23-synthecin</link><guid isPermaLink="false">https://whataifound.org/finding/2026-04-23-synthecin</guid><pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate><description>A reinforcement-learning generator searching a 46-billion-compound synthesizable space produced synthecin, a structurally novel antibacterial that cleared a methicillin-resistant Staphylococcus aureus wound infection in a mouse model.  SyntheMol-RL replaces the Monte Carlo tree search of the earlier SyntheMol with reinforcement learning over roughly 150,000 commercial building blocks and about 50 reaction templates, which lets it generalize across chemically similar blocks and optimize several properties at once. Run against S. aureus with joint objectives of antibacterial activity and aqueous solubility, it proposed candidates that the team then made: 79 compounds unique relative to the training set were synthesized, 13 were potently active in vitro, and 7 of those passed the authors' structural-novelty filters against known antibiotics. One hit, synthecin, was formulated as a topical and cleared a murine MRSA wound infection. The design step is a search harness with a learned policy, not a language model reasoning about chemistry.  Lab: McMaster University / Stanford University. Model: SyntheMol-RL. Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>antibiotics</category><category>drug-discovery</category><category>reinforcement-learning</category><category>generative-model</category><category>mrsa</category><category>in-vivo</category></item>
<item><title>SOP₂ and SOP₃ theories shown to coincide</title><link>https://whataifound.org/finding/2026-08-13-sop2-sop3</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-13-sop2-sop3</guid><pubDate>Fri, 14 Aug 2026 00:00:00 +0000</pubDate><description>The classes of SOP₂ and SOP₃ first-order theories are the same, answering a 2004 question of Džamonja and Shelah and collapsing the bottom of the SOP hierarchy to a single class.  Džamonja and Shelah introduced the tree configurations SOP₁ and SOP₂ in 2004 and asked whether either implication in the chain from SOP₃ to SOP₂ to SOP₁ reverses. Mutchnik answered the second, proving SOP₁ equals SOP₂, and the surviving half organised much of the subsequent NSOP₁ literature, with partial results by Conant, by Kaplan, Ramsey and Simon, and by Mutchnik. This five-page paper proves that SOP₂ implies SOP₃, the converse having been known from the start, which collapses the bottom of the hierarchy to a single class and carries consequences for Keisler-order maximality. The SOPₙ hierarchy for n at least three is untouched, as is everything above it.  Lab: Independent. Model: ChatGPT 5.6. Verification: Author verified. Autonomy: Collaborative.</description><category>model-theory</category><category>logic</category><category>classification-theory</category></item>
<item><title>Complete minimizer picture for Gamow's liquid drop model</title><link>https://whataifound.org/finding/2026-08-12-liquid-drop-minimizers</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-12-liquid-drop-minimizers</guid><pubDate>Fri, 14 Aug 2026 00:00:00 +0000</pubDate><description>Balls uniquely minimize the Gamow liquid drop energy at every volume up to a sharp threshold of about 3.51, and above that threshold no minimizer exists, closing a gap that partial results had narrowed from both sides without meeting.  Gamow's liquid drop functional adds De Giorgi perimeter to a Coulomb repulsion term, and the central question in its literature is the fixed-volume minimization picture: for which volumes a minimizer exists, and whether it is the ball. This proves that balls uniquely minimize, up to translation and null sets, at every volume up to a threshold of 5(2 − 2^(2/3))/(2^(2/3) − 1), roughly 3.51, and that above that threshold no minimizer exists at all. A corollary settles the minimal binding energy question of Frank and Lieb, identifying the infimum of energy per unit volume and the ball of volume 5/2 as the unique minimizer. The mechanism is a capacitary estimate sharpening an Agostiniani–Mazzieri monotonicity formula through Gauss–Bonnet, an improvement the authors note applies only to this particular weight and only in three dimensions.  Lab: Independent. Model: ChatGPT 5.6 Pro. Verification: Author verified. Autonomy: AI-led.</description><category>calculus-of-variations</category><category>geometric-analysis</category><category>mathematical-physics</category></item>
<item><title>A 112-vertex counterexample to the Petersen coloring conjecture</title><link>https://whataifound.org/finding/2026-08-08-petersen-coloring</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-08-petersen-coloring</guid><pubDate>Fri, 14 Aug 2026 00:00:00 +0000</pubDate><description>An explicit simple bridgeless cubic graph on 112 vertices admits no Petersen coloring, and hence no normal 5-edge-coloring, refuting a conjecture of Jaeger from 1985 with machine-checked UNSAT certificates.  Jaeger conjectured in 1985 that every bridgeless cubic graph admits a Petersen coloring: a map from its edges into the edges of the Petersen graph sending the three edges at each vertex to three edges meeting at a common vertex of the Petersen graph. Equivalently, every bridgeless cubic graph has a normal 5-edge-coloring. The conjecture implies both the Berge–Fulkerson conjecture and the 5-cycle-double-cover conjecture. This paper gives an explicit simple connected bridgeless cubic graph on 112 vertices, of girth five and edge and vertex connectivity three, with no such coloring; the graph is pinned by a SHA-256 digest in the theorem statement itself. Non-existence is established by direct SAT formulations, with CaDiCaL 3.0.1 returning UNSAT and drat-trim verifying the resulting DRAT proofs. A second, non-isomorphic counterexample of the same order is supplied. The implication runs one way, so Berge–Fulkerson and the 5-cycle-double-cover conjecture stay open; combined with a theorem of Ma, Mattiolo, Steffen and Wolf, one counterexample yields infinitely many.  Lab: Independent. Model: Unnamed OpenAI model. Verification: Formally verified. Autonomy: AI-assisted.</description><category>graph-theory</category><category>counterexample</category><category>sat-solver</category><category>combinatorics</category></item>
<item><title>Sendov's conjecture proved for every degree</title><link>https://whataifound.org/finding/2026-08-05-sendov-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-05-sendov-conjecture</guid><pubDate>Fri, 14 Aug 2026 00:00:00 +0000</pubDate><description>For every complex polynomial of degree at least two whose zeros all lie in the closed unit disk, each zero has a critical point of the polynomial within distance one, closing a question open since 1959.  Sendov's conjecture states that if every zero of a complex polynomial of degree n at least two lies in the closed unit disk, then every zero has a critical point within distance one. Degrees up to eight were settled piecemeal between 1969 and 1999, and Tao proved the conjecture for all sufficiently large degree in 2020 without specifying the threshold, which left the middle range open. Lech Mazur, working with GPT-5.6 Pro, produced an argument covering every degree along with a Lean development of roughly 90,000 lines. Terence Tao then digested the proof, describing it as remarkably elementary with no complex analysis used beyond the fundamental theorem of algebra, and formalized the entire argument himself in about 15,000 lines. He reports that the same argument resolves the Phelps–Rodriguez conjecture in full generality.  Lab: Independent. Model: GPT-5.6 Pro. Verification: Formally verified. Autonomy: Collaborative.</description><category>lean</category><category>complex-analysis</category><category>polynomials</category><category>formalization</category></item>
<item><title>Counterexamples to Schiffer's conjecture and the Pompeiu problem</title><link>https://whataifound.org/finding/2026-08-05-schiffer-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-05-schiffer-conjecture</guid><pubDate>Fri, 14 Aug 2026 00:00:00 +0000</pubDate><description>Infinitely many planar domains that are not balls admit a Neumann eigenfunction of the Laplacian that is constant on the boundary, disproving Schiffer's conjecture and, through a classical equivalence, the 1929 Pompeiu problem.  Pompeiu asked in 1929 whether a bounded domain over which some nonzero function integrates to zero under every rigid motion must be a ball. Schiffer's 1957 reformulation asks the same thing through Neumann eigenfunctions of the Laplacian that are constant on the boundary, and appears as Problem 80 on Yau's 1982 list; Williams proved the two formulations equivalent for simply connected domains in 1976. Cao-Labora and de Dios Pont construct infinitely many N-fold symmetric planar domains, with N large, that are not balls and carry such an eigenfunction. The strategy is to relax the problem so that N may be any real number, which corresponds to the Schiffer problem only at integers, apply bifurcation theory there, and show the size of the local bifurcation branch can be taken independently of N. Their Corollary 1.2 applies Williams' equivalence to the same domains, so a single construction settles both problems.  Lab: Independent. Model: GPT-5.6, Claude Opus 4.8, Claude Fable 5. Verification: Formally verified. Autonomy: AI-assisted.</description><category>lean</category><category>spectral-geometry</category><category>counterexample</category><category>analysis</category></item>
<item><title>Cycle double cover conjecture proved for all bridgeless multigraphs</title><link>https://whataifound.org/finding/2026-07-10-cycle-double-cover</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-10-cycle-double-cover</guid><pubDate>Fri, 14 Aug 2026 00:00:00 +0000</pubDate><description>Every finite bridgeless loopless multigraph has a multiset of cycles covering each edge exactly twice, resolving a conjecture open since 1973, with a machine-checked Lean proof of the unconditional statement.  The cycle double cover conjecture, posed by Szekeres in 1973 and independently by Seymour in 1979, asks whether every bridgeless graph admits a multiset of cycles in which every edge appears exactly twice. It is a textbook open problem in graph theory and sits at the centre of a cluster of neighbouring conjectures. OpenAI announced on 10 July 2026 that GPT-5.6 Sol Ultra, running 64 concurrent subagents, produced a three-page proof of the full statement in under an hour, and published the proof and the prompt, with a Lean 4 formalization following. The formalized route goes through the Jaeger–Kilpatrick eight-flow theorem: it constructs a nowhere-zero flow valued in three copies of the integers mod two, then converts that flow into a cycle double cover. Sang-il Oum published a ten-page exposition a week later, presenting the argument with slight modifications intended to make it more accessible.  Lab: OpenAI. Model: GPT-5.6 Sol Ultra. Verification: Formally verified. Autonomy: AI-led.</description><category>lean</category><category>graph-theory</category><category>combinatorics</category><category>multi-agent</category></item>
<item><title>Proportion of zeta zeros on the critical line raised to 67.25%</title><link>https://whataifound.org/finding/2026-08-10-zeta-zeros-critical-line</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-10-zeta-zeros-critical-line</guid><pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate><description>An unconditional proof that at least 67.25% of the nontrivial zeros of the Riemann zeta function are simple and lie on the critical line, up from a previous record of about 41.6%, with a machine-checked Lean formalization.  The Riemann hypothesis asserts every nontrivial zero lies on the critical line. Short of proving it, the standard measure of progress is the proportion of zeros known unconditionally to lie there: Selberg established a positive proportion, Levinson reached a third in 1974, Conrey two fifths in 1989, and the record had crept to roughly 41.6%. This work proves at least 3/2 − 1/√2cot 1/√2 = 67.25…% of zeros are simple and on the line, and that at least 0.83625 of zeros are distinct. The decisive step combined the unconditional pair-correlation work of Baluyot, Goldston, Suriajaya and Turnage-Butterbaugh with a 2000 paper of Bombieri, treating the whole function space at once with the quadratic form allowed to be non-diagonal rather than splitting it. The process is itself the record worth noting: the model was asked to attempt the Riemann hypothesis outright, with the mathematical choices left to it, and the bound improvement fell out of failing at that. It generated and discarded roughly 650 ideas in a first session; in a second it coordinated about 60 subagents which ran some 2,400 shell commands, wrote hundreds of scripts, checked numerically against known zeros and refereed one another. Two subagents developed the key ideas, thirteen fed them, thirty tried and failed, thirteen validated, two drafted the paper, across roughly 31 million output tokens in two Claude Code sessions. The model also proposed writing the result up, checked 54 arXiv papers for prior art, and recommended a human number theorist validate it.  Lab: Anthropic. Model: Claude (unreleased research version). Verification: Formally verified. Autonomy: AI-led.</description><category>lean</category><category>number-theory</category><category>riemann-hypothesis</category><category>multi-agent</category></item>
<item><title>Asymptotic degree-diameter problem resolved for fixed diameter</title><link>https://whataifound.org/finding/2026-08-04-moore-bound</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-04-moore-bound</guid><pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate><description>The maximum order of a graph with maximum degree d and diameter k satisfies nₖ(d)/dᵏ tending to 1 as d grows, for every fixed k, resolving the asymptotic form of a question open since 1978, with a Lean 4 formalization.  The Moore bound caps the order of a graph of maximum degree d and diameter k at roughly dᵏ. Whether that cap is asymptotically attainable for fixed diameter was open: Bannai and Ito had settled which exact Moore graphs exist, and constructions had approached the bound only for small diameters. This proves the limit of nₖ(d)/dᵏ is 1 for every fixed k, with a companion lower bound on the edge variant and a tight asymptotic for the bipartite version. The paper carries an explicit tool and computational resource disclosure: GPT-5.6 Pro was used in exploratory brainstorming directed by the authors, who formulated the required parameter scale and proposed higher-rank spherical buildings as the geometric setting. The model suggested splitting complete flags into their odd- and even-rank subflags, initially in connection with the edge problem; that suggestion became the halved-flag construction carrying the main theorem, and the graph is named for it.  Lab: Independent. Model: GPT-5.6 Pro. Verification: Formally verified. Autonomy: AI-assisted.</description><category>lean</category><category>graph-theory</category><category>combinatorics</category><category>extremal-combinatorics</category></item>
<item><title>Optimal exponent relating sumsets and difference sets determined</title><link>https://whataifound.org/finding/2026-07-29-sumset-difference-exponent</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-29-sumset-difference-exponent</guid><pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate><description>The least universal exponent c with |A + A|/|A| bounded by (|A − A|/|A|)ᶜ for every finite integer set A is determined, settling the extremal question with a Lean 4 formalization.  For a finite set A of integers with at least two elements, the ratio of log(|A + A|/|A|) to log(|A − A|/|A|) measures how far sumset growth can outrun difference-set growth. Determining its largest possible value fixes the least universal exponent c such that |A + A|/|A| ≤ (|A − A|/|A|)ᶜ for every such A. Tencent Hunyuan's Hyra research agent, powered by the Hy3 model, explored and optimized finite-set constructions over roughly a 24-hour run, moving from finite numerical searches to natural-language proposals of general constructions and supporting arguments, and produced the construction underlying the paper. The human authors independently checked the construction, corrected and rewrote the exposition, and prepared the final proof manually.  Lab: Tencent Hunyuan. Model: Hy3 (Hyra research agent). Verification: Formally verified. Autonomy: AI-led.</description><category>lean</category><category>additive-combinatorics</category><category>number-theory</category></item>
<item><title>Kemeny rank aggregation shown NP-hard for three voters</title><link>https://whataifound.org/finding/2026-07-28-kemeny-three-voters</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-28-kemeny-three-voters</guid><pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate><description>Computing a Kemeny-optimal aggregate ranking is NP-hard when the input is exactly three complete rankings, closing the minimal open case left by hardness results for even voter counts.  Kemeny aggregation asks for the ranking minimizing total disagreement with a set of input rankings. Hardness was known for every even number of voters n at least 4, while n = 2 is solvable in polynomial time, leaving three voters as the minimal open case since 2001. GPT-5.6 Sol Ultra found the reduction from MAX CUT; Claude Fable 5 helped simplify parts of it. Combined with the earlier results, every fixed number of voters n at least 3 is now known to be hard. The reduction is Lean-checked alongside an author-written preprint.  Lab: Independent. Model: GPT-5.6 Sol Ultra, Claude Fable 5. Verification: Formally verified. Autonomy: AI-led.</description><category>lean</category><category>complexity-theory</category><category>computational-social-choice</category></item>
<item><title>Feige's conjecture on sums of nonnegative random variables settled</title><link>https://whataifound.org/finding/2026-07-27-feige-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-27-feige-conjecture</guid><pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate><description>For independent nonnegative random variables with mean at most 1 and sum S, the probability that S is below its mean plus one is at least 1/e, the sharp constant Feige conjectured in 2004; three independent proofs appeared within days.  Feige proved in 2004 that for independent nonnegative random variables X₁, …, Xₙ with 𝔼[Xᵢ] ≤ 1 and S their sum, Pr(S &lt; 𝔼[S] + 1) is bounded below by a positive constant, established 1/13, and conjectured the sharp value 1/e. The primary paper states plainly in its abstract that the proof was found by ChatGPT 5.6 Pro, which combined the Vlassis-Thomas Dirichlet calibration theorem with Grunbaum-type convex geometry; the authors then checked, revised and rewrote the argument. The sharper form determines the optimal small-deviation bound. An end-to-end Lean formalization accompanies the paper, covering the Vlassis-Thomas theorem, Grunbaum's centroid theorem and the combining argument, developed with Codex.  Lab: Independent. Model: ChatGPT 5.6 Pro. Verification: Formally verified. Autonomy: AI-led.</description><category>lean</category><category>probability</category><category>concentration-inequalities</category></item>
<item><title>Gaussian product inequality conjecture proved</title><link>https://whataifound.org/finding/2026-07-20-gaussian-product-inequality</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-20-gaussian-product-inequality</guid><pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate><description>For any centered Gaussian vector and positive exponents, the expectation of the product of absolute powers is at least the product of the individual expectations, settling a conjecture posed in 2007.  The conjecture states that for a centered Gaussian vector X = (X₁, …, Xₙ), not necessarily nondegenerate, and any positive exponents a₁, …, aₙ, the expectation of the product of the |Xᵢ|^aᵢ is at least the product of the expectations of the |Xᵢ|^aᵢ. The stronger form adds that when every variance is positive, equality holds exactly when the coordinates are independent. The model returned a complete and correct solution from Greaves's prompt. It did not include the equality characterization, but only because that case was not in the prompt as posed. The proof was formalized in Lean using Codex, and the full prompt and output are public as a shared chat transcript.  Lab: Independent. Model: ChatGPT 5.6 Sol. Verification: Formally verified. Autonomy: AI-led.</description><category>lean</category><category>probability</category><category>gaussian-inequalities</category></item>
<item><title>Sabidussi's compatibility conjecture proved</title><link>https://whataifound.org/finding/2026-07-14-sabidussi-compatibility</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-14-sabidussi-compatibility</guid><pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate><description>The edges of a finite connected multigraph carrying a closed eulerian trail can be partitioned into circuits so that no circuit contains two edges used consecutively in the trail, with a Lean 4 formalization.  Sabidussi's conjecture asks whether, given a finite connected multigraph together with a closed eulerian trail, the edge set can always be partitioned into circuits none of which contains two edges that the trail uses consecutively. The proof establishes this and in fact does more: it four-colours the edges so as to satisfy the constraints. The work was developed with GPT-5.6 Pro and GPT-5.6 Sol, with the author reviewing the proof, and a Lean 4 formalization accompanies the preprint in the author's repository.  Lab: Independent. Model: GPT-5.6 Pro, GPT-5.6 Sol. Verification: Formally verified. Autonomy: Collaborative.</description><category>lean</category><category>graph-theory</category><category>combinatorics</category></item>
<item><title>Identity for the critical exponents of jamming derived analytically</title><link>https://whataifound.org/finding/2026-06-02-jamming-exponent-identity</link><guid isPermaLink="false">https://whataifound.org/finding/2026-06-02-jamming-exponent-identity</guid><pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate><description>The relation a + b = 1 between critical exponents at the jamming transition, previously seen only numerically in the full replica-symmetry-breaking solution of hard spheres, is derived from the scaling equations and published after peer review.  In the full replica-symmetry-breaking solution for hard spheres, the critical exponents a and b at the jamming transition had been observed numerically to high precision to satisfy a + b = 1, without an analytic derivation from the scaling equations. Parisi and Zamponi asked Claude for help; the model quickly proposed what proved to be essentially the correct idea, combining integration-by-parts identities with a maximum principle. Its first formal write-up contained errors, which the authors then fixed and verified before publication in the Journal of Statistical Mechanics.  Lab: Independent. Model: Claude Sonnet 4.6, Claude Opus 4.7. Verification: Peer reviewed. Autonomy: Collaborative.</description><category>statistical-physics</category><category>jamming</category><category>critical-exponents</category></item>
<item><title>Ten results in mathematics and theoretical computer science with Lean certificates</title><link>https://whataifound.org/finding/2026-08-01-astra-ten-advances</link><guid isPermaLink="false">https://whataifound.org/finding/2026-08-01-astra-ten-advances</guid><pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate><description>An unreleased OpenAI model produced ten results including the first explicit non-sofic group and a disproof of Connes's rigidity conjecture, each published with a machine-checkable Lean 4 proof.  The ten cover high-dimensional sphere packing, binary and spherical codes, non-sofic groups, Connes's rigidity conjecture, arithmetic circuit complexity, quantum parallel repetition, the closest vector problem, Ehrhart's volume conjecture, multicolor Ramsey numbers and extremal number conjectures. Soficity was introduced by Gromov in 1999 and whether a non-sofic group exists had stood open since; Connes posed his rigidity conjecture in 1980, and the disproof constructs infinitely many non-isomorphic property (T) groups sharing a von Neumann algebra. Humans used the same model to prepare the manuscripts and then to formalize each argument in Lean 4.32.0. OpenAI put the token cost of finding all ten at roughly $2,000 at Sol API rates.  Lab: OpenAI. Model: Astra. Verification: Formally verified. Autonomy: AI-led.</description><category>group-theory</category><category>lean</category><category>formalization</category><category>sphere-packing</category><category>quantum-complexity</category></item>
<item><title>Eight problems from the Kourovka Notebook solved and formalized in Lean</title><link>https://whataifound.org/finding/2026-07-20-kourovka-notebook</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-20-kourovka-notebook</guid><pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate><description>A formal reasoning agent developed the proof strategies for eight open problems in group theory without human guidance on which mathematical steps to take, and machine-checked every one in Lean 4.  The Kourovka Notebook has collected open problems in group theory since 1965, with a new issue every two to four years. Aristotle solved eight of them: 3.46 (a group with exactly two maximal locally soluble normal subgroups), 18.50, 19.25, 20.125 (a surjective non-injective Rota-Baxter operator on a non-abelian group), 21.8, 21.24, 21.147 and 21.150. The oldest first appeared in the third issue in 1969. Solutions take the form of proofs, counterexamples and constructions, each formalized in Lean 4 and published in a companion repository. The authors then informalized the Lean proofs into conventional prose and submitted both to the Notebook editors and the original problem proposers, who accepted them before publication.  Lab: Harmonic. Model: Aristotle. Verification: Formally verified. Autonomy: Autonomous.</description><category>group-theory</category><category>lean</category><category>formalization</category><category>kourovka-notebook</category><category>autonomous-discovery</category></item>
<item><title>Two kagome superconductors predicted by machine learning and confirmed in the lab</title><link>https://whataifound.org/finding/2026-06-17-kagome-superconductors</link><guid isPermaLink="false">https://whataifound.org/finding/2026-06-17-kagome-superconductors</guid><pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate><description>A screening pipeline that narrowed over 1.3 million candidate structures picked out YRu3B2 and LuRu3B2, which were then synthesized and measured to superconduct at 0.81 K and 0.95 K.  The SuperC consortium used machine-learning pre-screening to cut a very large chemical space down to a tractable candidate list, then ran first-principles calculations on what survived, arriving at 741 dynamically and thermodynamically stable compounds with DFT-predicted Tc above 5 K. Morosan's group at Rice synthesized two of them and confirmed bulk superconductivity by magnetization and specific heat measurement. Both compounds carry a kagome lattice, in which electrons form flat bands.  Lab: Aalto University / Rice University. Model: Unknown. Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>superconductivity</category><category>kagome</category><category>high-throughput-screening</category><category>dft</category><category>experimental-confirmation</category></item>
<item><title>Phase 1 trial of a computationally designed pan-sarbecovirus vaccine</title><link>https://whataifound.org/finding/2026-05-18-pevac-ps-sarbecovirus</link><guid isPermaLink="false">https://whataifound.org/finding/2026-05-18-pevac-ps-sarbecovirus</guid><pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate><description>A vaccine whose antigen was designed entirely in silico from sarbecovirus sequence data was safe in 39 healthy volunteers and raised immune responses against SARS-CoV-2, SARS, and bat viruses that have never infected humans.  Rather than target one strain, the team analysed sarbecovirus genetic data to compute a single synthetic antigen capturing structural features shared across the subgenus, on the theory that a vaccine aimed at what the family has in common survives the evolution of any one member. The candidate, pEVAC-PS, is a DNA vaccine delivered needle-free by micro fluid jet. The phase 1 dose-escalation trial ran in 39 healthy volunteers aged 18 to 50, sponsored by University Hospital Southampton NHS Foundation Trust, and reported no significant side effects.  Lab: University of Cambridge / DIOSynVax. Model: Unknown. Verification: Peer reviewed. Autonomy: AI-assisted.</description><category>vaccine-design</category><category>clinical-trial</category><category>coronavirus</category><category>antigen-design</category><category>phase-1</category></item>
<item><title>Counterexample to Grothendieck's question on finite flat group schemes</title><link>https://whataifound.org/finding/2026-07-11-grothendieck-group-schemes</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-11-grothendieck-group-schemes</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A finite locally free group scheme of order four whose fourth power map is not trivial, answering a question Grothendieck raised in the 1960s; one model produced the construction and another formalised it in Lean.  Grothendieck asked whether every finite locally free group scheme of order n is killed by n. Deligne proved it for commutative group schemes; the non-commutative case stayed open. The counterexample is a Hopf algebra of rank four over the ring ℤ[a, b]/(a³, b³, a²b + 2), with coordinate algebra R[U, V]/(U² − abU + b²V, V² − a²V), whose fourth convolution power is not the convolution unit. Kevin Buzzard, told of a 12-page informal write-up, replied that he does not read AI-generated informal mathematics and asked for a Lean proof instead; four hours later a 1,076-line Lean formalisation existed, and it compiles on a laptop in under five minutes. It was submitted to mathlib as pull request #41748.  Lab: Independent. Model: OpenAI Sol (construction); Claude Fable (Lean formalisation). Verification: Formally verified. Autonomy: Collaborative.</description><category>algebraic-geometry</category><category>group-schemes</category><category>counterexample</category><category>lean</category><category>formalization</category></item>
<item><title>First Herculaneum scroll read end to end without unrolling it</title><link>https://whataifound.org/finding/2026-06-25-herculaneum-scroll-read</link><guid isPermaLink="false">https://whataifound.org/finding/2026-06-25-herculaneum-scroll-read</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>PHerc. 1667 was virtually unwrapped and read in full from X-ray scans using learned ink detection: about 1.4 metres of papyrus across roughly 22 columns of Greek, identified as Philodemus, On Gods, Book 8.  The Herculaneum scrolls were carbonised by the AD 79 eruption of Vesuvius and disintegrate if physically unrolled. The pipeline scans a scroll by X-ray tomography, traces the rolled sheet as a three-dimensional surface, flattens it, and runs a network that detects near-invisible carbon ink from sub-millimetre surface texture. Luke Farritor's model recovered the first word, πορφύρας ("purple"), in October 2023, and the 2023 Grand Prize for four passages of 140 characters was claimed in February 2024. In June 2026, PHerc. 1667 became the first scroll recovered continuously from beginning to end, and a title read in a related scroll established that Philodemus' On Gods ran to at least eight books.  Lab: Vesuvius Challenge. Model: Community-developed ink-detection neural networks. Verification: Author verified. Autonomy: AI-assisted.</description><category>papyrology</category><category>virtual-unwrapping</category><category>ink-detection</category><category>ancient-texts</category></item>
<item><title>Limits to black-box amplification in QMA, with the key step written by GPT-5</title><link>https://whataifound.org/finding/2025-09-25-qma-amplification-limits</link><guid isPermaLink="false">https://whataifound.org/finding/2025-09-25-qma-amplification-limits</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A quantum complexity paper proving black-box error amplification for QMA cannot push completeness closer to certainty than doubly exponentially, in which the pivotal technical step was produced by GPT-5 in about half an hour.  The authors were stuck on how the largest eigenvalue of a matrix behaved as a parameter varied. GPT-5 proposed reformulating the quantity so that a complex approximation-theory bound applied, and that reformulation became the technical core of the oracle separation. Aaronson wrote that the step would have cost him or a graduate student a couple of weeks and that it was the first substantive AI contribution to a paper of his. The result makes his 2008 oracle separation quantitative and shows recent amplification results are optimal for black-box procedures.  Lab: UT Austin / CWI Amsterdam. Model: GPT-5 Thinking. Verification: Author verified. Autonomy: AI-assisted.</description><category>quantum-complexity</category><category>proof-assistance</category><category>oracle-separation</category></item>
<item><title>New families of unstable singularities in fluid equations</title><link>https://whataifound.org/finding/2025-09-17-unstable-singularities</link><guid isPermaLink="false">https://whataifound.org/finding/2025-09-17-unstable-singularities</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Physics-informed neural networks found previously unknown unstable self-similar blow-up solutions for three fluid equations, computed to near machine precision, and revealed an unexpected near-linear relation between a solution's instability order and its blow-up rate.  A physics-informed neural network minimises the residual of the differential equation itself rather than fitting data, which lets it hunt for self-similar blow-up profiles that ordinary simulation cannot hold onto because they are repelling. The team reports a stable and three unstable singularities for the incompressible porous media equation, a stable and three unstable solutions plus a candidate fourth for 2D Boussinesq, and an unstable singularity for 3D Euler with boundary. Residuals were driven near machine precision, the accuracy level a later computer-assisted proof would need. Across equations the blow-up rate depends almost linearly on the order of instability, a pattern nobody had predicted.  Lab: Google DeepMind (with Brown, NYU and Stanford). Model: Physics-informed neural networks with Gauss–Newton optimisation. Verification: Author verified. Autonomy: Search scaffold.</description><category>pde</category><category>fluid-dynamics</category><category>singularity</category><category>physics-informed-neural-networks</category></item>
<item><title>AI-generated bacteriophage genomes that replicate and kill bacteria</title><link>https://whataifound.org/finding/2025-09-17-evo-phage-genomes</link><guid isPermaLink="false">https://whataifound.org/finding/2025-09-17-evo-phage-genomes</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Genome language models wrote complete ΦX174-like bacteriophage genomes from scratch; of 285 designs that could be built, 16 produced viable infectious phages, several with faster lysis than the natural virus.  The team fine-tuned Evo 1 and Evo 2 on a cleaned set of nearly 15,000 Microviridae genomes, generated 302 candidate genomes with ΦX174-like architecture, chemically synthesised the 285 that could be assembled, and tested them for plaque formation in E. coli. Sixteen were viable, with substantial sequence divergence from the template. Several generated phages outcompeted wild-type ΦX174 in growth and lysis kinetics, and a cocktail of them cleared three ΦX174-resistant E. coli strains. The authors frame it as the first generative design of a complete functional genome.  Lab: Arc Institute / Stanford University. Model: Evo 1 and Evo 2. Verification: Peer reviewed. Autonomy: AI-led.</description><category>genome-design</category><category>bacteriophage</category><category>generative-biology</category><category>biosecurity</category></item>
<item><title>Machine-checked Lean proofs for five of six 2025 IMO problems</title><link>https://whataifound.org/finding/2025-07-28-aristotle-imo-lean</link><guid isPermaLink="false">https://whataifound.org/finding/2025-07-28-aristotle-imo-lean</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Harmonic's Aristotle produced formally verified Lean 4 proofs for five of the six 2025 IMO problems, so the gold-medal-standard score rests on a compiler rather than on human graders.  Aristotle drafts an informal proof, breaks it into intermediate lemmas, formalises each in Lean 4, and iterates against the compiler's feedback, which lets it use the large natural-language corpus of mathematics while still emitting machine-checked output. Harmonic published the Lean artifacts for the 2025 problems in a public repository. The announcement came a week after the natural-language gold results from Google DeepMind and OpenAI.  Lab: Harmonic. Model: Aristotle. Verification: Formally verified. Autonomy: AI-led.</description><category>olympiad</category><category>lean</category><category>formalization</category><category>benchmark</category></item>
<item><title>Gold-medal standard at the 2025 International Mathematical Olympiad</title><link>https://whataifound.org/finding/2025-07-21-gemini-deepthink-imo</link><guid isPermaLink="false">https://whataifound.org/finding/2025-07-21-gemini-deepthink-imo</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>An advanced version of Gemini Deep Think read the official problem statements and wrote natural-language proofs for five of the six 2025 IMO problems inside the contest time limits, scoring 35 of 42, graded and certified by the official IMO coordinators.  The model worked end to end in natural language within the two 4.5-hour sessions, with no human translating problems into a formal language, and solved problems one through five. Google DeepMind was in the first cohort whose results were officially graded and certified by IMO coordinators against the rubric used for student scripts; 35 points is the gold-medal threshold. OpenAI announced the same 35/42 score two days earlier with an experimental reasoning model, graded internally by three former IMO medallists rather than by the IMO.  Lab: Google DeepMind. Model: Gemini Deep Think (advanced version). Verification: Independently checked. Autonomy: AI-led.</description><category>olympiad</category><category>benchmark</category><category>natural-language-proof</category></item>
<item><title>Phase 2a results for a drug whose target and molecule both came from AI</title><link>https://whataifound.org/finding/2025-06-03-rentosertib-phase2a</link><guid isPermaLink="false">https://whataifound.org/finding/2025-06-03-rentosertib-phase2a</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Rentosertib, a TNIK inhibitor whose target was picked by one AI system and whose molecule was generated by another, improved forced vital capacity by 98.4 mL at the top dose against a 20.3 mL decline on placebo in a 71-patient randomised trial.  TNIK was prioritised as a fibrosis target by PandaOmics from omics and literature data; the inhibitor was generated and optimised by Chemistry42. GENESIS-IPF was a 12-week double-blind placebo-controlled Phase 2a across 22 sites in China, randomising 71 idiopathic pulmonary fibrosis patients across placebo and three dose arms. The 60 mg once-daily arm showed the largest lung-function improvement, and the drug was generally well tolerated. Published in Nature Medicine.  Lab: Insilico Medicine. Model: PandaOmics (target) + Chemistry42 (molecule). Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>drug-discovery</category><category>clinical-trial</category><category>target-discovery</category><category>fibrosis</category></item>
<item><title>A fully machine-generated paper passed workshop peer review</title><link>https://whataifound.org/finding/2025-03-12-ai-scientist-workshop-paper</link><guid isPermaLink="false">https://whataifound.org/finding/2025-03-12-ai-scientist-workshop-paper</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>One of three end-to-end AI-generated manuscripts submitted to an ICLR 2025 workshop averaged 6.33 from reviewers and would have been accepted; the authors withdrew it, and the bar cleared was a workshop track, not the main conference.  The AI Scientist-v2 generates a hypothesis, writes and runs the experiments through agentic tree search, and produces the manuscript, figures and related work without human editing. Sakana submitted three such papers to the ICLR 2025 workshop "I Can't Believe It's Not Better", with the knowledge and cooperation of the workshop organisers and ICLR leadership, and agreed in advance to withdraw anything accepted. One paper, on whether an explicit compositional regularisation term improves compositional generalisation, scored 6.33 and cleared the bar.  Lab: Sakana AI. Model: The AI Scientist-v2. Verification: Author verified. Autonomy: AI-led.</description><category>autonomous-research</category><category>peer-review</category><category>agents</category><category>contested</category></item>
<item><title>Enzymes with working catalytic machinery designed from scratch</title><link>https://whataifound.org/finding/2025-02-13-designed-serine-hydrolases</link><guid isPermaLink="false">https://whataifound.org/finding/2025-02-13-designed-serine-hydrolases</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Diffusion-based protein design produced serine hydrolases with catalytic efficiencies up to 2.2 × 10⁵ M⁻¹ s⁻¹ on five folds unlike any natural serine hydrolase, with crystal structures matching the design models to under 1 Å.  An enzyme needs more than the right shape: its active site has to stay organised at every step of the reaction, which is where designed enzymes have historically failed. The team generated backbones with RFdiffusion from a minimal active-site description, then used an ensemble-generation network to check that the catalytic geometry held along the whole reaction coordinate, keeping only designs that passed. The resulting hydrolases approach natural catalytic efficiency on folds not found among natural serine hydrolases, and the crystal structures match the designs closely. Published in Science.  Lab: Institute for Protein Design, University of Washington. Model: RFdiffusion with PLACER ensemble scoring. Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>protein-design</category><category>enzyme-design</category><category>rfdiffusion</category><category>catalysis</category></item>
<item><title>A working fluorescent protein generated by a language model</title><link>https://whataifound.org/finding/2025-01-16-esmgfp</link><guid isPermaLink="false">https://whataifound.org/finding/2025-01-16-esmgfp</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>ESM3 designed esmGFP, a bright green fluorescent protein sharing only 58% of its sequence with the closest known natural fluorescent protein, a distance the authors estimate at over 500 million years of natural evolution.  ESM3 is a masked language model over protein sequence, structure and function jointly. Prompted with the residues that form the GFP chromophore and little else, and run through iterative generation, it produced candidates that were synthesised and assayed in the lab. esmGFP fluoresces at brightness comparable to natural GFPs while differing at 96 of 229 positions from its nearest natural relative. Published in Science.  Lab: EvolutionaryScale. Model: ESM3 (98B). Verification: Peer reviewed. Autonomy: AI-led.</description><category>protein-design</category><category>generative-biology</category><category>fluorescent-protein</category></item>
<item><title>Generative model designs crystals to order; its flagship synthesis turned out to be a known compound</title><link>https://whataifound.org/finding/2025-01-16-mattergen</link><guid isPermaLink="false">https://whataifound.org/finding/2025-01-16-mattergen</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>MatterGen generates crystal structures conditioned on target properties, and its headline experimental validation was later shown to match a compound reported in 1972 that sits in the model's own training data.  MatterGen is a diffusion model over crystal structures (atom types, coordinates and lattice jointly), trained on about 608,000 stable materials from the Materials Project and Alexandria, and fine-tunable to condition on a target property. Conditioned on a bulk modulus of 200 GPa it proposed a structure that collaborators at the Shenzhen Institutes of Advanced Technology synthesised, measuring 169 GPa, within 20% of the specification. Published in Nature.  Lab: Microsoft Research. Model: MatterGen. Verification: Disputed. Autonomy: Search scaffold.</description><category>materials</category><category>crystal-structure</category><category>diffusion-model</category><category>contested</category></item>
<item><title>A neural decoder that identifies quantum errors more accurately than hand-designed methods</title><link>https://whataifound.org/finding/2024-11-20-alphaqubit</link><guid isPermaLink="false">https://whataifound.org/finding/2024-11-20-alphaqubit</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A transformer trained on Google's Sycamore surface-code data cut decoding errors by 6% against tensor-network decoding and 30% against correlated matching, the best reported accuracy at the time.  A quantum error-correcting code produces a stream of syndrome measurements; a decoder has to infer from them which errors actually occurred. Hand-designed decoders assume a simplified noise model, whereas AlphaQubit is a transformer trained first on simulated data and then fine-tuned on hundreds of millions of real syndrome samples from Sycamore, so it can learn the device's actual correlated noise, leakage and crosstalk. It beat both the accuracy-oriented tensor-network decoder and the fast matching decoder, and held up in simulation to distance-11 codes. Published in Nature.  Lab: Google DeepMind / Google Quantum AI. Model: AlphaQubit. Verification: Peer reviewed. Autonomy: AI-led.</description><category>quantum-computing</category><category>error-correction</category><category>transformer</category></item>
<item><title>Complete wiring diagram of an adult fruit-fly brain</title><link>https://whataifound.org/finding/2024-10-02-flywire-connectome</link><guid isPermaLink="false">https://whataifound.org/finding/2024-10-02-flywire-connectome</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Machine segmentation of an electron-microscopy volume, corrected by a large community of proofreaders, produced the first synapse-level map of an entire adult brain: 139,255 neurons and roughly 50 million synapses.  A female Drosophila brain was sliced into about 7,000 sections and imaged by electron microscopy, producing a volume no team could trace by hand. Neural networks segmented the neurons automatically; more than 200 labs and a crowd of proofreaders then corrected the segmentation over several years and annotated over 8,000 cell types. Simulations built directly on the resulting wiring diagram predicted which neurons drive feeding and grooming, and the predictions held up experimentally. Published as a Nature package in October 2024.  Lab: FlyWire Consortium (Princeton, MRC LMB, Cambridge, Vermont). Model: Automated electron-microscopy segmentation networks. Verification: Peer reviewed. Autonomy: AI-assisted.</description><category>connectome</category><category>electron-microscopy</category><category>segmentation</category><category>drosophila</category></item>
<item><title>Joint structure prediction for proteins, nucleic acids and ligands (AlphaFold 3)</title><link>https://whataifound.org/finding/2024-05-08-alphafold3</link><guid isPermaLink="false">https://whataifound.org/finding/2024-05-08-alphafold3</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A diffusion-based successor to AlphaFold predicts complexes spanning proteins, DNA, RNA, small molecules and ions in a single model, with large accuracy gains over the specialised docking tools used for each case.  AlphaFold 2 predicted the fold of a protein chain; drug discovery mostly needs the structure of that protein bound to something else. AlphaFold 3 replaces the structure module with a diffusion model operating directly on atom coordinates, which lets one network cover protein–ligand, protein–nucleic-acid and antibody–antigen complexes. Reported accuracy substantially exceeds specialised docking tools on protein–ligand benchmarks. Published in Nature.  Lab: Google DeepMind / Isomorphic Labs. Model: AlphaFold 3. Verification: Peer reviewed. Autonomy: AI-led.</description><category>protein-structure</category><category>drug-discovery</category><category>alphafold</category><category>diffusion-model</category></item>
<item><title>Reinforcement learning steers a tokamak away from tearing instabilities</title><link>https://whataifound.org/finding/2024-02-21-tearing-mode-avoidance</link><guid isPermaLink="false">https://whataifound.org/finding/2024-02-21-tearing-mode-avoidance</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A controller trained on past DIII-D shots forecast tearing-mode instabilities up to 300 ms ahead and adjusted the plasma in real time to avoid them, holding high-performance conditions that would otherwise have collapsed.  Tearing modes break up the magnetic surfaces confining a fusion plasma and can end a discharge. Existing approaches suppress them once they appear; this one predicts them. A network trained on past DIII-D discharges estimates the instability probability, and a reinforcement-learning policy trained against a learned plasma model adjusts beam power and plasma shape to keep that probability low while holding pressure high. It was tested live on DIII-D, not only in simulation. Published in Nature.  Lab: Princeton University / PPPL / DIII-D National Fusion Facility. Model: Deep reinforcement learning controller over a learned plasma model. Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>fusion</category><category>plasma-control</category><category>reinforcement-learning</category><category>tokamak</category></item>
<item><title>Olympiad geometry solved without human demonstrations</title><link>https://whataifound.org/finding/2024-01-17-alphageometry</link><guid isPermaLink="false">https://whataifound.org/finding/2024-01-17-alphageometry</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A language model trained purely on synthetic data, paired with a symbolic deduction engine, solved 25 of 30 olympiad geometry problems against 10 for the previous best automated system and 25.9 for the average human gold medallist.  Geometry proofs stall when they need an auxiliary construction, an extra point or line that is not in the problem statement. AlphaGeometry pairs a symbolic deduction engine, which exhausts what follows mechanically, with a language model that proposes constructions when deduction runs dry. The model was trained on 100 million synthetic proofs generated from random diagrams, with no human proof data, and its output is a symbolic proof that the deduction engine checks. Published in Nature.  Lab: Google DeepMind. Model: AlphaGeometry. Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>olympiad</category><category>geometry</category><category>neuro-symbolic</category><category>benchmark</category></item>
<item><title>A language-model agent that planned and ran chemistry experiments on lab robots</title><link>https://whataifound.org/finding/2023-12-20-coscientist</link><guid isPermaLink="false">https://whataifound.org/finding/2023-12-20-coscientist</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Coscientist, driven by GPT-4 with web search, documentation search, code execution and lab automation, designed and executed palladium-catalysed cross-coupling reactions on real robotic hardware from a one-line goal.  Given "perform Suzuki and Sonogashira reactions", the agent searched the literature to identify the chemistry, read the hardware documentation for an API it had not seen, wrote the control code, located the reagents on the plate from a UV-Vis reading, and ran the reactions on a liquid handler. The paper reports six tasks in total, including reaction optimisation under Bayesian search. Published in Nature.  Lab: Carnegie Mellon University. Model: GPT-4 (Coscientist agent). Verification: Peer reviewed. Autonomy: AI-led.</description><category>lab-automation</category><category>agents</category><category>cross-coupling</category><category>self-driving-lab</category></item>
<item><title>A new structural class of antibiotic candidates against MRSA</title><link>https://whataifound.org/finding/2023-12-20-antibiotic-structural-class</link><guid isPermaLink="false">https://whataifound.org/finding/2023-12-20-antibiotic-structural-class</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Graph neural networks trained on 39,312 assayed compounds and applied to 12 million molecules surfaced a chemical class active against MRSA in mice, with the substructures driving each prediction made explicit rather than left opaque.  The team measured antibiotic activity and human-cell cytotoxicity for 39,312 compounds, trained network ensembles on that data, and predicted both properties for over 12 million molecules. Rather than reading off top scores, they extracted the chemical substructures the models were keying on, which let them pick a class rather than isolated hits. Two lead compounds cleared MRSA infection in mouse models, topically and systemically, and appear to kill by collapsing the electrochemical gradient across the bacterial membrane. Published in Nature.  Lab: MIT / Broad Institute / Harvard. Model: Ensembles of graph neural networks with substructure attribution. Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>antibiotics</category><category>graph-neural-network</category><category>explainability</category><category>mrsa</category></item>
<item><title>Medium-range weather forecasts from a graph neural network beat the operational physics model</title><link>https://whataifound.org/finding/2023-11-14-graphcast</link><guid isPermaLink="false">https://whataifound.org/finding/2023-11-14-graphcast</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>GraphCast produced more accurate 10-day forecasts than ECMWF's HRES on roughly 90% of the evaluated variable and lead-time combinations, in under a minute on a single TPU against hours on a supercomputer.  GraphCast takes the two most recent global atmospheric states and predicts the next state six hours ahead on a roughly 0.25° grid, applied repeatedly to reach ten days. It is trained on ERA5 reanalysis rather than on the equations of motion, and it beat HRES, the operational gold standard, on the large majority of evaluated variables, rising to almost all of them within the troposphere. It also flagged severe weather events, including cyclone tracks, earlier than the physics model despite never being trained to look for them. Published in Science, with code and weights released.  Lab: Google DeepMind. Model: GraphCast. Verification: Peer reviewed. Autonomy: AI-led.</description><category>weather</category><category>forecasting</category><category>graph-neural-network</category></item>
<item><title>Pathogenicity predictions for 71 million human missense variants</title><link>https://whataifound.org/finding/2023-09-19-alphamissense</link><guid isPermaLink="false">https://whataifound.org/finding/2023-09-19-alphamissense</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>An AlphaFold-derived model classified 89% of all 71 million possible human missense variants as likely benign or likely pathogenic, against the roughly 0.1% that carry a clinical classification today.  AlphaMissense fine-tunes AlphaFold's structural representation on human and primate variant frequency data, so it learns which substitutions natural selection tolerates without being trained on clinical labels. Applied across 19,233 canonical human proteins it scored every possible single amino-acid change, calling 57% likely benign and 32% likely pathogenic. The full catalogue and the model code were released publicly. Published in Science.  Lab: Google DeepMind. Model: AlphaMissense. Verification: Peer reviewed. Autonomy: AI-led.</description><category>genomics</category><category>variant-effect</category><category>clinical-genetics</category></item>
<item><title>Two theorems found by machine pattern-spotting in knot theory and representation theory</title><link>https://whataifound.org/finding/2021-12-01-knot-theory-intuition</link><guid isPermaLink="false">https://whataifound.org/finding/2021-12-01-knot-theory-intuition</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>Networks trained to predict one mathematical invariant from another, then probed for which inputs mattered, pointed mathematicians to a proved theorem linking a knot's signature to a new geometric quantity, and to structure behind the combinatorial invariance conjecture.  The recipe was to train a network to predict one invariant from another, then use attribution to see which inputs carried the signal, and hand that to a mathematician. In knot theory it led Marc Lackenby to define a new quantity, the natural slope of a knot, and to prove a theorem bounding the signature in terms of it. In representation theory it led Geordie Williamson to structure in Bruhat interval graphs bearing on the combinatorial invariance conjecture for Kazhdan–Lusztig polynomials. Published in Nature.  Lab: Google DeepMind (with Oxford and Sydney). Model: Supervised networks with gradient-based attribution. Verification: Peer reviewed. Autonomy: AI-assisted.</description><category>knot-theory</category><category>representation-theory</category><category>conjecture-generation</category></item>
<item><title>Reinforcement learning refutes several conjectures in extremal combinatorics</title><link>https://whataifound.org/finding/2021-04-29-wagner-combinatorics</link><guid isPermaLink="false">https://whataifound.org/finding/2021-04-29-wagner-combinatorics</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A neural network building graphs edge by edge under a cross-entropy search produced explicit counterexamples to several published conjectures in graph theory and extremal combinatorics.  Each conjecture was rewritten as a scoring function on graphs. A network proposes graphs one edge at a time, the top-scoring constructions are kept, and the network is retrained on them, so the search drifts toward whatever the conjecture says should be impossible. Among the conjectures refuted are a question of Brualdi and Cao on maximising permanents of pattern-avoiding matrices and several concerning adjacency and distance eigenvalues of graphs. The counterexamples are small finite graphs printed in the paper, so each can be checked by hand or by a few lines of code.  Lab: Tel Aviv University. Model: Deep cross-entropy method (custom network). Verification: Independently checked. Autonomy: Search scaffold.</description><category>combinatorics</category><category>graph-theory</category><category>counterexample</category><category>reinforcement-learning</category></item>
<item><title>Halicin, an antibiotic found by a neural network screening a compound library</title><link>https://whataifound.org/finding/2020-02-20-halicin</link><guid isPermaLink="false">https://whataifound.org/finding/2020-02-20-halicin</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A graph neural network trained on 2,335 molecules picked halicin out of a repurposing library; it killed multidrug-resistant bacteria including Acinetobacter baumannii and Mycobacterium tuberculosis in vitro and cleared infections in mice.  The model was trained to predict growth inhibition of E. coli from structure alone, then applied to the Drug Repurposing Hub. Halicin, an abandoned diabetes candidate, scored highly despite being structurally unlike known antibiotics. It kills by dissipating the proton-motive force across the bacterial membrane, and the team could not evolve resistant E. coli over 30 days of serial passage. A follow-up screen of about 107 million molecules from ZINC15 produced eight further candidates. Published in Cell.  Lab: MIT / Broad Institute. Model: Directed message-passing graph neural network (Chemprop). Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>antibiotics</category><category>drug-repurposing</category><category>graph-neural-network</category></item>
<item><title>An eighth planet around Kepler-90 found by a neural network</title><link>https://whataifound.org/finding/2017-12-14-kepler-90i</link><guid isPermaLink="false">https://whataifound.org/finding/2017-12-14-kepler-90i</guid><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><description>A convolutional network re-examining Kepler light curves recovered transit signals the standard pipeline had ranked below threshold, yielding Kepler-90i and making Kepler-90 the first star besides the Sun known to host eight planets.  The network was trained on 15,000 previously vetted Kepler signals to separate genuine transits from false positives, then pointed at 670 stars already known to host multiple planets, searching the weak signals the automated pipeline had discarded. It surfaced Kepler-90i (about 30% larger than Earth, orbiting every 14.4 days, with a surface hot enough to rival Mercury) and Kepler-80g, which completes a five-planet resonant chain. Published in The Astronomical Journal.  Lab: Google Brain / University of Texas at Austin. Model: Convolutional neural network (AstroNet). Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>exoplanets</category><category>kepler</category><category>transit-detection</category></item>
<item><title>Counterexamples to the Gaussian moments conjecture</title><link>https://whataifound.org/finding/2026-07-20-gaussian-moments</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-20-gaussian-moments</guid><pubDate>Mon, 27 Jul 2026 00:00:00 +0000</pubDate><description>Explicit low-degree polynomials disproving a 2017 conjecture that had been proposed as a route to proving the Jacobian conjecture, found days after that conjecture was itself disproved.  Derksen, van den Essen and Zhao proposed the Gaussian moments conjecture and showed that the Jacobian conjecture would follow from it. Long reports that a cubic counterexample in four variables was produced by GPT-5.6 Sol Pro with no human intervention after the initial prompt, which simply noted that the Jacobian conjecture had just been disproved and asked whether a small counterexample to GMC might therefore exist; Claude Fable 5 then found a quartic counterexample in three variables and supplied independent algebraic checks. Together these show GMC(n) is false for every n ≥ 3.  Lab: Independent. Model: GPT-5.6 Sol Pro + Claude Fable 5. Verification: Author verified. Autonomy: AI-led.</description><category>algebra</category><category>polynomial-maps</category><category>counterexample</category><category>jacobian-conjecture</category></item>
<item><title>Near-quadratic lower bound for derivative-free convex optimization</title><link>https://whataifound.org/finding/2026-07-14-zeroth-order-oracle-bound</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-14-zeroth-order-oracle-bound</guid><pubDate>Mon, 27 Jul 2026 00:00:00 +0000</pubDate><description>A lower bound of order d²/log d on the number of exact function evaluations needed to minimize a convex Lipschitz function, closing a gap open since 1996 and showing a 1996 algorithm was essentially optimal.  In zeroth-order optimization an algorithm may only query a function's value, never its gradient. Protasov's 1996 algorithm needed about d² evaluations in d dimensions, but the best known lower bound was only about d, leaving open whether a much faster method existed. The new bound of Ω(d²/log(d + 1)) matches the upper bound to polylogarithmic factors. Kerger reports that after a ten-page prompt built on his own earlier failed attempts, the model produced the complete proof in a single 2.5-hour session with no intervention; he then reviewed it and formally verified the core bound in Lean 4, which compiles against Mathlib with no `sorry` and no bespoke axioms.  Lab: Independent. Model: GPT-5.6 Sol Pro. Verification: Formally verified. Autonomy: AI-led.</description><category>optimization</category><category>complexity-theory</category><category>lower-bounds</category><category>lean</category></item>
<item><title>Nine Erdős problems and 44 OEIS conjectures proved with machine-checked proofs</title><link>https://whataifound.org/finding/2026-05-21-alphaproof-nexus</link><guid isPermaLink="false">https://whataifound.org/finding/2026-05-21-alphaproof-nexus</guid><pubDate>Mon, 27 Jul 2026 00:00:00 +0000</pubDate><description>An agent pairing language models with the Lean proof assistant resolved 9 of 353 open Erdős problems and 44 of 492 open OEIS conjectures, with every proof mechanically verified.  The system proposes proofs with a language model and checks every step in Lean, so a hallucinated argument cannot pass. Beyond the Erdős and OEIS totals it settled a 15-year-old question on log-concavity of pure O-sequences in codimension 3 and type 2, and proved an exact O(1/t) convergence rate for anchored gradient descent-ascent via a parameter choice not previously identified. Two of the Erdős problems had been open for 56 years. All formal proofs were released in a public repository.  Lab: Google DeepMind. Model: AlphaProof Nexus (LLM + Lean). Verification: Formally verified. Autonomy: Search scaffold.</description><category>lean</category><category>automated-theorem-proving</category><category>erdos-problems</category><category>combinatorics</category></item>
<item><title>AlphaEvolve across 67 problems: 20 improvements, 8 regressions</title><link>https://whataifound.org/finding/2025-11-03-alphaevolve-at-scale</link><guid isPermaLink="false">https://whataifound.org/finding/2025-11-03-alphaevolve-at-scale</guid><pubDate>Mon, 27 Jul 2026 00:00:00 +0000</pubDate><description>A systematic study with Terence Tao of an evolutionary coding agent on 67 open problems in analysis, combinatorics and geometry, reporting where it beat the literature and where it did not.  Rather than a single headline result, this is the systematic version: 67 problems attempted, with outcomes recorded either way. Tao reports roughly 20 cases of a new result, most others matching known bounds, and 8 where the tool did worse than the literature. Genuine advances include new three-dimensional constructions for finite-field Nikodym sets, which then prompted a human-refined hybrid construction beating both algebraic and random baselines, and an improved upper bound for Sidon sets, from 1.96365 to about 1.9526. On the well-known conjectures of Sidorenko, Sendov and Crouzeix it found no counterexample, which Tao notes may simply reflect that they are true.  Lab: Google DeepMind. Model: AlphaEvolve (Gemini-based). Verification: Independently checked. Autonomy: Search scaffold.</description><category>combinatorics</category><category>geometry</category><category>analysis</category><category>evolutionary-search</category></item>
<item><title>Strong prime number theorem formalized in Lean by an autoformalization agent</title><link>https://whataifound.org/finding/2025-09-11-gauss-strong-pnt</link><guid isPermaLink="false">https://whataifound.org/finding/2025-09-11-gauss-strong-pnt</guid><pubDate>Mon, 27 Jul 2026 00:00:00 +0000</pubDate><description>An agent completed a Lean formalization of the strong prime number theorem in about three weeks, finishing a project two expert mathematicians had left blocked after 18 months.  Tao and Kontorovich began a Lean formalization of the strong prime number theorem (the version with an explicit error term) in January 2024, and by July 2025 had announced intermediate progress blocked on core difficulties in complex analysis. Math, Inc. reports that Gauss produced over 25,000 lines of Lean and roughly 1,100 theorems and definitions in about three weeks, completing the project. The repository README states that most statements and proofs were produced by the agent, with humans supplying the high-level blueprint, reviewing key lemmas, and adapting prior work.  Lab: Math, Inc.. Model: Gauss (autoformalization agent). Verification: Author verified. Autonomy: AI-assisted.</description><category>lean</category><category>formalization</category><category>number-theory</category><category>prime-number-theorem</category></item>
<item><title>Counterexample to the Dinitz–Garg–Goemans conjecture</title><link>https://whataifound.org/finding/2026-07-22-dinitz-garg-goemans</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-22-dinitz-garg-goemans</guid><pubDate>Fri, 24 Jul 2026 00:00:00 +0000</pubDate><description>An explicit seven-node network whose cheapest single-route (unsplittable) shipping costs more than its fractional cost even under the allowed capacity slack, disproving a conjecture from the late 1990s.  Dinitz, Garg, and Goemans proved that any fractional multicommodity flow can be rounded to an unsplittable (single-path-per-demand) flow while violating each arc's capacity by at most the maximum demand. Goemans conjectured this rounding could also be done without increasing the total cost. The counterexample is a directed graph on seven nodes carrying three demands (15, 10, 15); its fractional solution costs 58, yet every unsplittable routing that stays within the allowed capacity cushion (violation ≤ 15) costs at least 60. Rybin reached it with GPT-5.6 Pro in four short prompts and reported that the model returned proof certificates, an exhaustive-enumeration verification program, machine-readable data, and LaTeX source.  Lab: Independent. Model: GPT-5.6 Pro. Verification: Formally verified. Autonomy: AI-led.</description><category>combinatorial-optimization</category><category>network-flow</category><category>counterexample</category><category>unsplittable-flow</category></item>
<item><title>Improved bound for the Erdős minimum-overlap problem</title><link>https://whataifound.org/finding/2025-05-alphaevolve-minimum-overlap</link><guid isPermaLink="false">https://whataifound.org/finding/2025-05-alphaevolve-minimum-overlap</guid><pubDate>Tue, 21 Jul 2026 00:00:00 +0000</pubDate><description>AlphaEvolve nudged the best known bound for Erdős's minimum-overlap constant, the first improvement since 2016, and sharpened several autocorrelation inequalities.  As part of a sweep across open problems in mathematical analysis, AlphaEvolve improved the upper bound on the Erdős minimum-overlap constant from about 0.380927 to about 0.380924, the first movement since 2016, and improved constants in autocorrelation inequalities. The gains are numerically small but exceed long-standing records, and the constructions are explicit and checkable.  Lab: Google DeepMind. Model: AlphaEvolve (Gemini-based). Verification: Independently checked. Autonomy: Search scaffold.</description><category>analysis</category><category>erdos</category><category>alphaevolve</category></item>
<item><title>Deep reinforcement learning controls tokamak fusion plasma</title><link>https://whataifound.org/finding/2022-02-16-tokamak-plasma-control</link><guid isPermaLink="false">https://whataifound.org/finding/2022-02-16-tokamak-plasma-control</guid><pubDate>Tue, 21 Jul 2026 00:00:00 +0000</pubDate><description>A reinforcement-learning controller learned to shape and stabilise the magnetic confinement of real fusion plasma inside the TCV tokamak, holding configurations that are hard to sustain by hand.  Working with EPFL's Swiss Plasma Center, DeepMind trained a deep reinforcement-learning agent to command the magnetic control coils of the TCV tokamak. Learning in a simulator against specified target shapes, the controller then ran on the real machine, holding elongated, snowflake and other configurations, including a 'droplet' state with two separate plasmas at once. It is one of the first times a single learned controller replaced the hand-engineered cascade normally required.  Lab: Google DeepMind. Model: DeepMind RL controller. Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>physics</category><category>fusion</category><category>reinforcement-learning</category><category>control</category></item>
<item><title>Accurate protein structure prediction across the known proteome (AlphaFold2)</title><link>https://whataifound.org/finding/2021-07-15-alphafold2</link><guid isPermaLink="false">https://whataifound.org/finding/2021-07-15-alphafold2</guid><pubDate>Tue, 21 Jul 2026 00:00:00 +0000</pubDate><description>AlphaFold2 predicted three-dimensional structures for nearly all catalogued proteins from amino-acid sequence at accuracy rivalling experiment, work that earned the 2024 Nobel Prize in Chemistry.  AlphaFold2 pairs an attention-based neural network with evolutionary sequence information to predict how a protein folds from its amino-acid sequence. At the 2020 CASP14 blind assessment it reached accuracy competitive with experimental methods, and DeepMind and EMBL-EBI then released predicted structures for over 200 million proteins, nearly the entire catalogued proteome. Demis Hassabis and John Jumper shared the 2024 Nobel Prize in Chemistry for the work, alongside David Baker for computational protein design.  Lab: Google DeepMind. Model: AlphaFold2. Verification: Independently checked. Autonomy: AI-led.</description><category>protein-structure</category><category>biology</category><category>alphafold</category><category>nobel-prize</category></item>
<item><title>Counterexample to the Jacobian conjecture in dimension three</title><link>https://whataifound.org/finding/2026-07-19-jacobian-conjecture</link><guid isPermaLink="false">https://whataifound.org/finding/2026-07-19-jacobian-conjecture</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>An explicit polynomial map in three variables with constant Jacobian determinant −2 that is nevertheless not invertible, disproving a conjecture open since 1939.  The map F(x, y, z) = (u³z + y²u(4 + 3xy), y + 3xu²z + 3xy²(4 + 3xy), 2x − 3x²y − x³z) with u = 1 + xy has Jacobian determinant identically −2, yet sends the three distinct points (0, 0, −1/4), (1, −3/2, 13/2) and (−1, 3/2, 13/2) all to (−1/4, 0, 0). A map with a global inverse cannot be three-to-one. Alpöge, a number theorist at Anthropic, announced it on X the day it was found.  Lab: Anthropic. Model: Claude Fable 5. Verification: Formally verified. Autonomy: Collaborative.</description><category>algebraic-geometry</category><category>counterexample</category><category>polynomial-maps</category></item>
<item><title>Disproof of the Erdős unit-distance conjecture</title><link>https://whataifound.org/finding/2026-05-erdos-unit-distance</link><guid isPermaLink="false">https://whataifound.org/finding/2026-05-erdos-unit-distance</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>A reasoning model produced the core construction disproving a 1946 conjecture in discrete geometry, finding point configurations with more unit-distance pairs than the conjecture permitted.  The model produced a construction beating the conjectured bound, with an inexplicit exponent greater than 1. Nine mathematicians - Alon, Bloom, Gowers, Litt, Sawin, Shankar, Tsimerman, Wang and Wood - published a human-verified version of the argument; Sawin separately made the exponent explicit at n^1.014. Gowers called it 'the first example of a result produced autonomously by an AI that I find exciting in itself.'  Lab: OpenAI. Model: GPT-5 series reasoning model. Verification: Independently checked. Autonomy: AI-led.</description><category>discrete-geometry</category><category>combinatorics</category><category>erdos</category></item>
<item><title>Structure in Bruhat intervals of permutation groups</title><link>https://whataifound.org/finding/2026-01-alphaevolve-bruhat</link><guid isPermaLink="false">https://whataifound.org/finding/2026-01-alphaevolve-bruhat</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>AlphaEvolve identified unexpected special structure in Bruhat intervals for particular permutation groups.  Part of a continuing series of AlphaEvolve results in combinatorics. The system evolves candidate programs under a human-specified evaluation function, so the search is automated but the problem framing is human.  Lab: Google DeepMind. Model: AlphaEvolve (Gemini-based). Verification: Independently checked. Autonomy: Search scaffold.</description><category>combinatorics</category><category>alphaevolve</category></item>
<item><title>Erdős problem #728 resolved and formalized in Lean</title><link>https://whataifound.org/finding/2026-01-erdos-728</link><guid isPermaLink="false">https://whataifound.org/finding/2026-01-erdos-728</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>GPT-5.2 produced a proof of a previously open Erdős problem; Harmonic's Aristotle formalized it in Lean, making it the first Erdős problem regarded as fully resolved by AI with machine-checked proof.  The problem concerns the existence of infinitely many integers a, b, n satisfying divisibility and inequality conditions involving factorials. GPT-5.2 generated the argument, Aristotle formalized it in Lean, and a human-readable writeup was posted to arXiv. Modifications of the same argument also resolved problems #729 and #401.  Lab: OpenAI / Harmonic. Model: GPT-5.2 Pro + Aristotle. Verification: Formally verified. Autonomy: Autonomous.</description><category>number-theory</category><category>erdos</category><category>lean</category><category>formalization</category></item>
<item><title>Early science acceleration experiments with GPT-5</title><link>https://whataifound.org/finding/2025-11-gpt5-science-acceleration</link><guid isPermaLink="false">https://whataifound.org/finding/2025-11-gpt5-science-acceleration</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>A multi-domain study documenting cases where GPT-5 contributed to research progress across mathematics, physics, biology and materials science.  A collection of case studies rather than a single result. Useful as a source of individual entries; each contained claim needs separate grading before it belongs in the registry on its own.  Lab: OpenAI. Model: GPT-5. Verification: Peer reviewed. Autonomy: AI-assisted.</description><category>meta</category><category>multi-domain</category></item>
<item><title>GPT-5 "solved 10 Erdős problems": it located existing solutions</title><link>https://whataifound.org/finding/2025-10-19-gpt5-erdos-retrieval</link><guid isPermaLink="false">https://whataifound.org/finding/2025-10-19-gpt5-erdos-retrieval</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>An OpenAI executive announced that GPT-5 had solved 10 previously open Erdős problems and made progress on 11 more; the problems were only 'open' in the sense that one database maintainer was unaware of the already-published solutions the model surfaced.  OpenAI VP Kevin Weil posted that 'GPT-5 found solutions to 10 (!) previously unsolved Erdős problems.' Thomas Bloom, who maintains erdosproblems.com, replied that listing a problem as open there only means he personally was unaware of a solution, and that GPT-5 had found existing papers containing the solutions rather than proving anything new. The post was deleted; Demis Hassabis called the episode 'embarrassing' and Yann LeCun mocked it.  Lab: OpenAI. Model: GPT-5. Verification: Already known. Autonomy: Retrieval.</description><category>number-theory</category><category>erdos</category><category>already-known</category><category>cautionary</category><category>retrieval</category></item>
<item><title>Improved step-size bound in smooth convex optimization</title><link>https://whataifound.org/finding/2025-08-gpt5-convex-bound</link><guid isPermaLink="false">https://whataifound.org/finding/2025-08-gpt5-convex-bound</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>GPT-5 Pro extended a guaranteed-convexity window for gradient descent from η ≤ 1/L to η ≤ 1.5/L, but the optimal 1.75/L bound had already been published months earlier.  Bubeck posed an open problem from a convex optimization paper. After about 17 minutes of reasoning the model produced an improved bound using Bregman divergence inequalities and cocoercivity. Bubeck verified the proof as correct and described it as new mathematics.  Lab: OpenAI. Model: GPT-5 Pro. Verification: Already known. Autonomy: AI-assisted.</description><category>optimization</category><category>already-known</category><category>cautionary</category></item>
<item><title>4×4 complex matrix multiplication in 48 scalar multiplications</title><link>https://whataifound.org/finding/2025-05-alphaevolve-matmul</link><guid isPermaLink="false">https://whataifound.org/finding/2025-05-alphaevolve-matmul</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>AlphaEvolve found a scheme multiplying 4×4 complex matrices with 48 scalar multiplications, improving on Strassen's 49 from 1969.  Strassen's 1969 algorithm had stood at 49 multiplications for 56 years in this setting. AlphaEvolve was not purpose-built for matrix multiplication; it is a general evolutionary coding agent. The scheme is exactly checkable.  Lab: Google DeepMind. Model: AlphaEvolve (Gemini-based). Verification: Independently checked. Autonomy: Search scaffold.</description><category>algorithms</category><category>linear-algebra</category><category>alphaevolve</category></item>
<item><title>Improved lower bound for the 11-dimensional kissing number</title><link>https://whataifound.org/finding/2025-05-alphaevolve-kissing</link><guid isPermaLink="false">https://whataifound.org/finding/2025-05-alphaevolve-kissing</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>AlphaEvolve improved the best known configuration for the kissing number problem in 11 dimensions.  Part of a sweep across 50+ open problems in analysis, geometry, combinatorics and number theory. AlphaEvolve rediscovered state-of-the-art solutions in roughly 75% of cases and improved on the best known in about 20%. The kissing number problem asks how many non-overlapping unit spheres can touch a central one.  Lab: Google DeepMind. Model: AlphaEvolve (Gemini-based). Verification: Independently checked. Autonomy: Search scaffold.</description><category>geometry</category><category>sphere-packing</category><category>alphaevolve</category></item>
<item><title>Candidate treatment for dry age-related macular degeneration</title><link>https://whataifound.org/finding/2025-robin-macular</link><guid isPermaLink="false">https://whataifound.org/finding/2025-robin-macular</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>The Robin system automated hypothesis generation, experiment design and data analysis, identifying a novel candidate treatment for dry AMD.  Presented as an end-to-end automated discovery loop with humans executing the physical experiments. Robin proposed enhancing retinal pigment epithelium phagocytosis as a therapeutic strategy, then identified ripasudil and KL001 as candidates and confirmed in vitro efficacy for both. It went on to propose and analyse a follow-up RNA sequencing experiment, which showed upregulation of ABCA1, a lipid efflux pump and a possible novel target in its own right. Published in Nature in May 2026.  Lab: FutureHouse. Model: Robin (multi-agent). Verification: Peer reviewed. Autonomy: AI-led.</description><category>drug-discovery</category><category>ophthalmology</category><category>multi-agent</category></item>
<item><title>AI co-scientist hypotheses on antimicrobial resistance and liver fibrosis</title><link>https://whataifound.org/finding/2025-02-ai-coscientist-amr</link><guid isPermaLink="false">https://whataifound.org/finding/2025-02-ai-coscientist-amr</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>A multi-agent system generated hypotheses that were subsequently validated experimentally in the lab.  The system proposed mechanisms in antimicrobial resistance and liver fibrosis that wet-lab work then supported. Notable as one of the earliest cases of an AI-generated hypothesis surviving experimental test rather than just sounding plausible. The peer-reviewed version, published in Nature in May 2026, covers three biomedical applications together: drug repurposing, novel-target discovery and explaining mechanisms of antimicrobial resistance. It adds drug-repurposing candidates and synergistic combination therapies for acute myeloid leukaemia that were then validated in vitro.  Lab: Google. Model: AI Co-Scientist (Gemini 2.0 multi-agent). Verification: Peer reviewed. Autonomy: AI-assisted.</description><category>hypothesis-generation</category><category>microbiology</category><category>multi-agent</category></item>
<item><title>Silver-medal standard at the 2024 International Mathematical Olympiad</title><link>https://whataifound.org/finding/2024-07-25-alphaproof-imo</link><guid isPermaLink="false">https://whataifound.org/finding/2024-07-25-alphaproof-imo</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>AlphaProof and AlphaGeometry 2 together solved four of the six 2024 IMO problems for 28 of 42 points (one short of the gold threshold), with the algebra and number-theory solutions produced and checked in the Lean proof assistant.  AlphaProof, a reinforcement-learning system that works inside Lean, solved two algebra problems and one number-theory problem (including P6, the competition's hardest, which few human contestants solved), while AlphaGeometry 2 solved the geometry problem in seconds. The two combinatorics problems went unsolved. The Lean-based solutions are machine-checked by construction; the full performance was graded by mathematicians Timothy Gowers and Joseph Myers under competition-style marking.  Lab: Google DeepMind. Model: AlphaProof + AlphaGeometry 2. Verification: Independently checked. Autonomy: AI-led.</description><category>olympiad</category><category>lean</category><category>formalization</category><category>benchmark</category></item>
<item><title>New lower bound constructions for the cap set problem</title><link>https://whataifound.org/finding/2023-12-funsearch-capset</link><guid isPermaLink="false">https://whataifound.org/finding/2023-12-funsearch-capset</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>FunSearch discovered larger cap sets than any previously known construction, the first time an LLM-based system produced a genuinely new discovery on an established open problem.  FunSearch pairs an LLM that proposes programs with an automated evaluator that rejects incorrect ones, sidestepping hallucination by construction. Applied to extremal combinatorics, it found new large cap sets in both finite-dimensional and asymptotic cases. Published in Nature. Historically the first entry in this registry's scope.  Lab: Google DeepMind. Model: FunSearch (PaLM 2 / Codey). Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>combinatorics</category><category>cap-set</category><category>funsearch</category><category>historic-first</category></item>
<item><title>Improved heuristics for online bin packing</title><link>https://whataifound.org/finding/2023-12-funsearch-binpacking</link><guid isPermaLink="false">https://whataifound.org/finding/2023-12-funsearch-binpacking</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>FunSearch produced bin-packing heuristics outperforming standard baselines on benchmark distributions.  Discovered programs are human-readable, which allowed domain experts to inspect and deploy them. Practical rather than theoretical significance.  Lab: Google DeepMind. Model: FunSearch (PaLM 2 / Codey). Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>algorithms</category><category>heuristics</category><category>funsearch</category></item>
<item><title>Large-scale prediction of new stable crystalline materials (GNoME)</title><link>https://whataifound.org/finding/2023-11-29-gnome</link><guid isPermaLink="false">https://whataifound.org/finding/2023-11-29-gnome</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>GNoME predicted about 2.2 million new inorganic crystal structures, roughly 380,000 of them flagged as thermodynamically stable, presented as an order-of-magnitude expansion of known stable materials.  Graph Networks for Materials Exploration (GNoME) is a graph neural network trained in an active-learning loop against density-functional-theory calculations to predict formation energies and filter candidates by stability. DeepMind released the predicted structures as a public dataset. Published in Nature.  Lab: Google DeepMind. Model: GNoME (graph neural network). Verification: Disputed. Autonomy: Search scaffold.</description><category>materials</category><category>crystal-structure</category><category>graph-neural-network</category><category>contested</category></item>
<item><title>Autonomous laboratory reports solid-state synthesis of new inorganic compounds</title><link>https://whataifound.org/finding/2023-11-29-a-lab-synthesis</link><guid isPermaLink="false">https://whataifound.org/finding/2023-11-29-a-lab-synthesis</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>Berkeley's A-Lab, an AI-driven autonomous laboratory, reported synthesising 41 novel inorganic compounds out of 58 targets over 17 days with minimal human intervention.  A-Lab coupled machine-learning synthesis-recipe prediction with robotic sample preparation, heating and X-ray characterisation, drawing targets from stability predictions including GNoME's. It reported making 41 of 58 targeted compounds autonomously. Published in Nature alongside GNoME.  Lab: Lawrence Berkeley National Laboratory. Model: A-Lab (ML planning + robotics). Verification: Disputed. Autonomy: AI-led.</description><category>materials</category><category>autonomous-lab</category><category>synthesis</category><category>contested</category></item>
<item><title>Faster sorting routines discovered and merged into the LLVM C++ library</title><link>https://whataifound.org/finding/2023-06-07-alphadev</link><guid isPermaLink="false">https://whataifound.org/finding/2023-06-07-alphadev</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>AlphaDev found shorter branchless routines for sorting small fixed-length inputs; reverse-engineered to C++, they were merged into LLVM's libc++, the first change to those routines in over a decade.  AlphaDev treated the construction of a sorting routine as a single-player game played directly in CPU assembly, rewarding shorter and faster correct programs. For sort-3, sort-4 and sort-5 it removed instructions relative to the human-tuned library code, yielding large speedups on short sequences. The routines were reverse-engineered to C++ and accepted into the LLVM libc++ standard sort, which ships to millions of users. Published in Nature.  Lab: Google DeepMind. Model: AlphaDev (AlphaZero-based). Verification: Independently checked. Autonomy: Search scaffold.</description><category>algorithms</category><category>sorting</category><category>reinforcement-learning</category><category>deployed</category></item>
<item><title>Faster matrix-multiplication algorithms found by reinforcement learning</title><link>https://whataifound.org/finding/2022-10-05-alphatensor</link><guid isPermaLink="false">https://whataifound.org/finding/2022-10-05-alphatensor</guid><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><description>AlphaTensor discovered matrix-multiplication schemes using fewer scalar multiplications than any previously known, including a way to multiply 4×4 matrices over GF(2) in 47 multiplications versus the 49 of two-level Strassen.  AlphaTensor recast the search for matrix-multiplication algorithms as a single-player game of decomposing a 3-D tensor into rank-one terms, then trained an AlphaZero-style agent to play it. It matched or beat the best known rank for many matrix sizes, and over GF(2) found a 4×4 scheme using 47 multiplications, improving on the 49 obtained by applying Strassen's 1969 algorithm twice. Every decomposition it returns is an exact identity checkable by hand. Published in Nature.  Lab: Google DeepMind. Model: AlphaTensor (AlphaZero-based). Verification: Peer reviewed. Autonomy: Search scaffold.</description><category>algorithms</category><category>linear-algebra</category><category>reinforcement-learning</category></item>
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