Discrete Homotopy and Promise Constraint Satisfaction Problem

TL;DR

This paper develops a discrete combinatorial approach inspired by algebraic topology to analyze the complexity of Promise Constraint Satisfaction Problems, aiming to extend the method to higher dimensions for broader applicability.

Contribution

It introduces a discrete analog of topological methods for PCSPs, establishing foundational concepts and demonstrating its effectiveness through hardness results.

Findings

Established a basic framework relating combinatorial structures to PCSP complexity

Proved several hardness results using the discrete approach

Connected the new method to existing topological techniques

Abstract

The Promise Constraint Satisfaction Problem (PCSP for short) is a generalization of the well-studied Constraint Satisfaction Problem (CSP). The PCSP has its roots in such classic problems as the Approximate Graph Coloring and the $(1+\varepsilon)$-Satisfiability problems. The area received much attention recently with multiple approaches developed to design efficient algorithms for restricted versions of the PCSP, and to prove its hardness. One such approach uses methods from Algebraic Topology to relate the complexity of the PCSP to the structure of the fundamental group of certain topological spaces. In this paper, we attempt to develop a discrete analog of this approach by replacing topological structures with combinatorial constructions and some basic group-theoretic concepts. We consider the `one-dimensional' case of the approach. We introduce and prove the basics of the framework, show how it is related to the complexity of the PCSP, and obtain several hardness results, including the existing ones, as applications of our approach. The main hope, however, is that this discrete variant of the topological approach can be generalized to the `multi-dimensional' case needed for further progress.