Doubly Saturated Ramsey Graphs: A Case Study in Computer-Assisted Mathematical Discovery

Fuente: arXiv
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Auteurs principaux: Przybocki, Benjamin, Mackey, John, Heule, Marijn J. H., Subercaseaux, Bernardo
Format: Preprint
Publié: 2026
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author Przybocki, Benjamin
Mackey, John
Heule, Marijn J. H.
Subercaseaux, Bernardo
author_facet Przybocki, Benjamin
Mackey, John
Heule, Marijn J. H.
Subercaseaux, Bernardo
contents Ramsey-good graphs are graphs that contain neither a clique of size $s$ nor an independent set of size $t$. We study doubly saturated Ramsey-good graphs, defined as Ramsey-good graphs in which the addition or removal of any edge necessarily creates an $s$-clique or a $t$-independent set. We present a method combining SAT solving with bespoke LLM-generated code to discover infinite families of such graphs, answering a question of Grinstead and Roberts from 1982. In addition, we use LLMs to generate and formalize correctness proofs in Lean. This case study highlights the potential of integrating automated reasoning, large language models, and formal verification to accelerate mathematical discovery. We argue that such tool-driven workflows will play an increasingly central role in experimental mathematics.
format Preprint
id arxiv_https___arxiv_org_abs_2604_21187
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Doubly Saturated Ramsey Graphs: A Case Study in Computer-Assisted Mathematical Discovery
Przybocki, Benjamin
Mackey, John
Heule, Marijn J. H.
Subercaseaux, Bernardo
Combinatorics
Artificial Intelligence
Ramsey-good graphs are graphs that contain neither a clique of size $s$ nor an independent set of size $t$. We study doubly saturated Ramsey-good graphs, defined as Ramsey-good graphs in which the addition or removal of any edge necessarily creates an $s$-clique or a $t$-independent set. We present a method combining SAT solving with bespoke LLM-generated code to discover infinite families of such graphs, answering a question of Grinstead and Roberts from 1982. In addition, we use LLMs to generate and formalize correctness proofs in Lean. This case study highlights the potential of integrating automated reasoning, large language models, and formal verification to accelerate mathematical discovery. We argue that such tool-driven workflows will play an increasingly central role in experimental mathematics.
title Doubly Saturated Ramsey Graphs: A Case Study in Computer-Assisted Mathematical Discovery
topic Combinatorics
Artificial Intelligence
url https://arxiv.org/abs/2604.21187