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arxiv:2602.12772

Formalizing Gröbner Basis Theory in Lean

Published on Feb 13
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Abstract

The work formalizes Gröbner basis theory in Lean 4 using multivariate polynomial infrastructure, covering division algorithms, Buchberger's criterion, reduced bases, and connections between finite and infinite variable settings via monomial-order embeddings and filter limits.

We present a formalization of Gröbner basis theory in Lean 4, built on top of Mathlib's infrastructure for multivariate polynomials and monomial orders. Our development covers the core foundations of Gröbner basis theory, including polynomial division with remainder, Buchberger's criterion, and the existence and uniqueness of reduced Gröbner bases. We develop the theory uniformly for polynomial rings indexed by arbitrary types, enabling the treatment of Gröbner bases in rings with infinitely many variables. Furthermore, we connect the finite and infinite settings by showing that infinite-variable reduced Gröbner bases can be characterized via reduced Gröbner bases on finite-variable subrings through monomial-order embeddings and filter-based limit constructions.

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