🤖 AI Summary
This paper investigates the computational complexity of solving equations over finitely generated monoids under promise constraints. Given a finitely generated (not necessarily finite) monoid $M$, a finite simple monoid $N$, and a homomorphism $varphicolon M o N$, we consider solving equation systems over $N$ that are promised to have solutions in $M$. The work establishes, for the first time in the infinite-promise setting, a universal complexity dichotomy theorem: such problems are either in P or NP-complete. Methodologically, it extends the promise CSP framework to algebraic structures—specifically monoids—with explicit relational constraints, integrating techniques from variety theory, analysis of homomorphic images, and algebraic complexity theory. Crucially, it lifts prior restrictions requiring $M$ to be finite, thereby unifying and precisely characterizing the solvability boundary for a significantly broader class of monoids.
📝 Abstract
Larrauri and v{Z}ivn'y recently established a complete complexity classification of the problem of solving a system of equations over a monoid $N$ assuming that a solution exists over a monoid $M$, where both monoids are finite and $M$ admits a homomorphism to $N$. Using the algebraic approach to promise constraint satisfaction problems, we extend their complexity classification in two directions: we obtain a complexity dichotomy in the case where arbitrary relations are added to the monoids, and we moreover allow the monoid $M$ to be finitely generated.