In 1930, Keller conjectured that every gap-free tiling of ℝⁿ by n-dimensional unit cubes must contain cubes that fully share an (n - 1)-dimensional face. Keller’s conjecture holds for n ≤ 7 and fails for n ≥ 8. The final case, n = 7, was settled in 2020 using a mix of traditional and automated reasoning. The result was obtained by reducing the conjecture to a set of clique-existence problems, encoding those problems into propositional logic, breaking symmetries, and solving them with a SAT solver. In this paper, we present an end-to-end verification in Lean 4 of Keller’s conjecture for all dimensions. First, we simplify a prior reduction of Keller’s conjecture to the clique-existence problems. We then verify an improved SAT encoding of those problems, as well as some symmetry reasoning on the encoding. Throughout our work, we sought to maximize the synergy between interactive and automated techniques while minimizing human proof burden. In particular, the symmetry reasoning was split between Lean and a mechanically-checkable proof system, since neither was suitable on their own for verifying all of the symmetry reasoning. We discuss how and why we chose to split the reasoning across these systems based on their relative strengths and weaknesses.

A recent breakthrough in computer-assisted mathematics showed that every set of 30 points in the plane in general position (i.e., no three points on a common line) contains an empty convex hexagon. Heule and Scheucher solved this problem with a combination of geometric insights and automated reasoning techniques by constructing CNF formulas ϕ_n, with O(n⁴) clauses, such that if ϕ_n is unsatisfiable then every set of n points in general position must contain an empty convex hexagon. An unsatisfiability proof for n = 30 was then found with a SAT solver using 17 300 CPU hours of parallel computation. In this paper, we formalize and verify this result in the Lean theorem prover. Our formalization covers ideas in discrete computational geometry and SAT encoding techniques by introducing a framework that connects geometric objects to propositional assignments. We see this as a key step towards the formal verification of other SAT-based results in geometry, since the abstractions we use have been successfully applied to similar problems. Overall, we hope that our work sets a new standard for the verification of geometry problems relying on extensive computation, and that it increases the trust the mathematical community places in computer-assisted proofs.