math.NTJul 25, 2026

Extremal Chowla sets and their linear analogues: A human-AI mathematical investigation using Co-Scientist

Authors: Mohsen AliabadiKeith DriscollElliot KropPetar SirkovicEverett SullivanElahe Vedadi

Organizations: Clayton State University · Google Cloud AI Research · Google DeepMind

Abstract

We introduce an extremal invariant associated with Chowla-type order conditions in finite groups. A nonempty subset SS of a finite group GG is called a Chowla set if every element of SS has order greater than S|S|, and we write C(G)C(G) for the maximum cardinality of such a set. We first show that C(G)C(G) is determined by the distribution of element orders in GG. For cyclic groups, we derive an exact divisor formula and characterize the integers nn for which C(Z/nZ)=φ(n)C(\mathbb{Z}/n\mathbb{Z})=\varphi(n). We prove that lim infnC(Z/nZ)/φ(n)=1\liminf_{n\to\infty}C(\mathbb{Z}/n\mathbb{Z})/\varphi(n)=1, whereas lim supnC(Z/nZ)/φ(n)=\limsup_{n\to\infty}C(\mathbb{Z}/n\mathbb{Z})/\varphi(n)=\infty, and we determine the corresponding lower and upper limits under normalization by nn. For finite abelian groups, we obtain an explicit formula in terms of the invariant-factor decomposition, together with a closed formula for finite abelian pp-groups. We then develop a linear analogue for finite field extensions. A nonzero KK-subspace AA of an extension L/KL/K is called a Chowla subspace if [K(a):K]>dimKA[K(a):K]>\dim_K A for every nonzero aAa\in A. Since this condition depends on dimKA\dim_K A, it does not generally require every nonzero element of AA to generate LL over KK. Nevertheless, when L/KL/K is finite and separable, we prove the exact formula C(L/K)=[L:K]dmax(L/K)C(L/K)=[L:K]-d_{\max}(L/K), where dmax(L/K)d_{\max}(L/K) is the largest degree over KK of a proper intermediate field. For finite fields, we give a direct proof in every degree using a normal-basis construction. This work was developed through an expert-guided human-AI collaboration. A reasoning-focused configuration of Co-Scientist was used to explore examples and potential proof strategies. The authors formulated the problem, independently verified and completed all arguments, and wrote the final proofs.

Explore similar work

Jul 26, 2026math.GR

An Exact Counterexample to Carlson's Associated-Prime Depth Conjecture from a Group of Order 128

In Question~3.1 of his 1995 paper on depth and transfer, Carlson asked whether the depth of a finite-group cohomology ring is always realized by the dimension of one of its associated primes. We give a negative answer. Let G=\SG128859,k=\kbar.G=\SG{128}{859},\qquad k=\kbar. An exact presentation certificate proves that \depthH(G;k)=2\depth H^*(G;k)=2. Okuyama's associated-prime theorem would convert an associated prime of dimension two into a rank-two elementary abelian subgroup EGE\leq G satisfying \depthH(CG(E);k)=2\depth H^*(C_G(E);k)=2. We enumerate all 7575 rank-two elementary abelian subgroups of GG and obtain six centralizer types. Duflot's theorem gives depth at least three for four types, while exact ideal-quotient certificates exhibit regular sequences of length three for the remaining two. Hence every rank-two centralizer has cohomological depth at least three, so H(G;k)H^*(G;k) has no associated prime of dimension two. The finite group presentation, the three cohomology-ring presentations, the enumeration summary, and the exact algebraic certificates are included for independent verification.
Xinan Dai, Wenhao Deng, Yingdong Shi +2
May 11, 2026math.GR

Every finite group admits a just finite presentation

A finite presentation < X | R > of a finite group is called `just finite' if removing any relation from R results in a presentation for an infinite group. It has been an open question (Kourovka Notebook, Problem 21.10) whether every finite group admits such a presentation. We resolve this conjecture in the affirmative.
Marc Lackenby
Aug 11, 2026cs.AI

Long-Horizon AI Research for Grothendieck Constant: A Case Study in Human-AI Mathematical Collaboration

AI agents are increasingly used in mathematics research, but it is often unclear how to use them effectively. Towards this, we present an extensive case study of how AI was used to improve bounds on the Grothendieck constant KGK_G, which captures the hardness between combinatorial problems and their continuous relaxations. Specifically, while the precise value of KGK_G is not known, we recently tightened the best known bounds to 6π11    KG    π2log(1+2)104.\frac{6π}{11} \;\le\; K_G \;\le\; \fracπ{2\log(1+\sqrt2)} - 10^{-4}. Crucially, these improvements were achieved using an AI research system that could arrive at insights deemed novel by domain experts. We give a detailed discussion of our experience using AI for mathematics research, particularly touching upon its strengths and weaknesses, as well as our experience with creating ideal conditions for AI to arrive at breakthrough insights.
Alan Li, Rahul Saha, Anton Xue +4