English

Optimal PSPACE-hardness of Approximating $q$-CSP Reconfiguration

Computational Complexity 2026-07-30 v1 Discrete Mathematics Data Structures and Algorithms

Abstract

In the Maxmin qq-CSP Reconfiguration problem, given a satisfiable qq-CSP instance and a pair of its satisfying assignments, we are asked to transform one assignment into the other by repeatedly changing the value assigned to a single variable. The objective is to find such a transformation that maximizes the minimum fraction of satisfied constraints along the transformation. In this paper, we prove that for any q2q \geq 2 and ε>0\varepsilon > 0, Maxmin qq-CSP Reconfiguration is PSPACE\mathsf{PSPACE}-hard to approximate within a factor of 12q1+ε\frac{1}{2^{q-1}}+\varepsilon. To complement this hardness result, we prove that a (12q1ε)\bigl(\frac{1}{2^{q-1}}-\varepsilon\bigr)-factor approximation for Maxmin qq-CSP Reconfiguration is in NP\mathsf{NP} in the perfect completeness case. These results establish the optimal PSPACE\mathsf{PSPACE}-hardness of approximating Maxmin qq-CSP Reconfiguration for every q2q \geq 2 under NPPSPACE\mathsf{NP} \neq \mathsf{PSPACE}.

Cite

@article{arxiv.2607.28099,
  title  = {Optimal PSPACE-hardness of Approximating $q$-CSP Reconfiguration},
  author = {Shuichi Hirahara and Naoto Ohsaka},
  journal= {arXiv preprint arXiv:2607.28099},
  year   = {2026}
}

Comments

79 pages, to appear in Proceedings of the 67th IEEE Symposium on Foundations of Computer Science (FOCS 2026)