Searcharxiv⌕ Search

arXiv · 2610.10477

Primal/Dual Method for the Grothendieck Constant

Abstract

We determine the hundredths digit of the real Grothendieck constant by proving $1.773 \leq K_G \leq 1.7799$. Furthermore, numerical heuristics suggest the estimate $K_G \approx 1.779$. We start by simplifying the Gaussian duality theory of $K_G$, based on Hermite projection games and Krivine rounding schemes. The bounds are obtained by a heuristic primal/dual search for these objects, followed by rigorous {\em certification} of their values. The search and certification are performed using AI tools, and in particular the rigorous certificates are very large (analytical reductions to thousands of numerical inequalities).

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Steven Heilman, Chris Jones, Giulio Malavolta. 2026-10-07. Primal/Dual Method for the Grothendieck Constant. https://arxiv.org/abs/2610.10477

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Near-Linear Regimes for One-Sided Distribution-Free Junta Testing

We study adaptive one-sided distribution-free testing of Boolean $k$-juntas, with membership-query access to the function and sample access to an arbitrary unknown distribution. For general Boolean functions, we give a tester using $O(k^2\log(k+1)+k/ε)$ queries, independently of the ambient dimension. The tester maintains disjoint relevant blocks certified by observed disagreements. Within each fresh batch, it jointly decodes literal signatures for a small family of random base masks, then uses linear combinations to generate $Θ(1/ε)$ probes. Their ideal counterparts are pairwise independent, yielding constant conditional progress probability; a global $O(k)$ batch budget gives the additive query bound. Consequently, the complexity is $O((k/ε)\log(k+1))$ when $ε\le1/k$, and $O(k/ε)$ when $ε\le1/(k\log(k+1))$. We also analyze an indexed-table implementation that reuses previously computed block orientations. For functions symmetric on an unknown set of relevant variables, it uses $O(k\log^2(k+1)/ε)$ queries: safely checked blocks contain a single globally relevant variable, making their cached nonliteral sides reusable. For arbitrary functions, a stable-deletion analysis establishes soundness of the same implementation at $O(k^2\log(k+1)/ε)$ queries. All variants always accept $k$-juntas, and every rejection is certified by $k+1$ disjoint relevant blocks. The fresh-batch construction and the reuse analysis use the same certified-block framework, with different randomness and stopping rules.

cs.CC↗

A Relative-Computability Theory of Self-Improving Agents

Agents increasingly modify the procedures by which they solve tasks and improve themselves. Autonomy over improvement, gains in practical capability, and enlargement of computational reach are distinct properties. We develop an oracle-relative model with mutable solvers, evaluators, and improvers. Uniform simulation keeps every total decision procedure produced by effective self-revision over $A$ within $\mathcal{C}(A)=\{D:D\leq_T A\}$; oracle joins account for additional access, while the relativized limit lemma separates limiting answers from effective completion. A worked model of Boolean rule acquisition makes the distinction constructive. For a known finite-dimensional feature language, we characterize exactly which answers a query history determines, obtain a sharp teacher-query bound, and give a terminating protocol that permits revisions to the query proposer. The learned solver can dispense with the teacher on every input while remaining in the same computability layer. However, uniformly constructing the required feature-span specification from arbitrary effective feature programs is already as hard as the relative halting problem. We also give a conditional criterion for strict ascent and distinguish it from finite behavioral evidence. The framework thus separates acquisition, certification, and computability ascent, identifying both a positive route to verified support removal and the assumptions on which it depends.

cs.CC↗

An $n^2\log\log n$ Lower Bound for Permanent Circuits with Valid Division

We record lower bounds for permanent circuits with valid division over characteristic zero, counting nonscalar multiplications and divisions while additions and scalar operations are free. Chapter 5 of OpenAI's Ten Advances supplies the block construction and critical-locus estimate; these, with the parameter choice made here and the classical bounds of Strassen and Baur-Strassen, give liminf as n tends to infinity of L_div(per_n)/(n^2 log_2 log_2 n) >= 1/12. Our finite-parameter refinement for matching-minor polynomials observes that the coefficient vector at deletion size h lies in a space of dimension at most min{binom(t,h), binom(t,d-h)}. Twelve machine-checked declarations of the Lean development accompanying OpenAI's manuscript on border determinantal complexity of the permanent (September 24, 2026) imply, by a short written argument, the existence of a geometric slice; a further written, unformalized application of the same criterion gives L_div(per_n) >= (n^2/119790) log_2(n/44) for n >= 1936. Assuming Proposition 7.3 of that manuscript gives the bound (n^2/86400) log_2(n/48) for n >= 1408. These are order-of-growth results; the elementary Hessian bound n^2/2 is larger at practical orders.

cs.CC↗