English

Cohomology in Constraint Satisfaction and Structure Isomorphism

Logic in Computer Science 2022-07-01 v1 Computational Complexity Data Structures and Algorithms

Abstract

Constraint satisfaction (CSP) and structure isomorphism (SI) are among the most well-studied computational problems in Computer Science. While neither problem is thought to be in PTIME,\texttt{PTIME}, much work is done on PTIME\texttt{PTIME} approximations to both problems. Two such historically important approximations are the kk-consistency algorithm for CSP and the kk-Weisfeiler-Leman algorithm for SI, both of which are based on propagating local partial solutions. The limitations of these algorithms are well-known; kk-consistency can solve precisely those CSPs of bounded width and kk-Weisfeiler-Leman can only distinguish structures which differ on properties definable in CkC^k. In this paper, we introduce a novel sheaf-theoretic approach to CSP and SI and their approximations. We show that both problems can be viewed as deciding the existence of global sections of presheaves, Hk(A,B)\mathcal{H}_k(A,B) and Ik(A,B)\mathcal{I}_k(A,B) and that the success of the kk-consistency and kk-Weisfeiler-Leman algorithms correspond to the existence of certain efficiently computable subpresheaves of these. Furthermore, building on work of Abramsky and others in quantum foundations, we show how to use \v{C}ech cohomology in Hk(A,B)\mathcal{H}_k(A,B) and Ik(A,B)\mathcal{I}_k(A,B) to detect obstructions to the existence of the desired global sections and derive new efficient cohomological algorithms extending kk-consistency and kk-Weisfeiler-Leman. We show that cohomological kk-consistency can solve systems of equations over all finite rings and that cohomological Weisfeiler-Leman can distinguish positive and negative instances of the Cai-F\"urer-Immerman property over several important classes of structures.

Keywords

Cite

@article{arxiv.2206.15253,
  title  = {Cohomology in Constraint Satisfaction and Structure Isomorphism},
  author = {Adam Ó Conghaile},
  journal= {arXiv preprint arXiv:2206.15253},
  year   = {2022}
}