The Limits of SDP Relaxations for General-Valued CSPs

Author:

Thapper Johan1ORCID,Živný Stanislav2ORCID

Affiliation:

1. Université Paris-Est, Marne-la-Vallée, Champs-sur-Marne, France

2. University of Oxford, Oxford, UK

Abstract

It has been shown that for a general-valued constraint language Γ the following statements are equivalent: (1) any instance of VCSP(Γ) can be solved to optimality using a constant level of the Sherali-Adams LP hierarchy, (2) any instance of VCSP(Γ) can be solved to optimality using the third level of the Sherali-Adams LP hierarchy, and (3) the support of Γ satisfies the “ bounded width condition ” (i.e., it contains weak near-unanimity operations of all arities). We show that if the support of Γ violates the bounded width condition then not only is VCSP(Γ) not solved by a constant level of the Sherali-Adams LP hierarchy, but it also requires linear levels of the Lasserre SDP hierarchy (also known as the sum-of-squares SDP hierarchy). For Γ corresponding to linear equations in an Abelian group, this result follows from existing work on inapproximability of Max-CSPs. By a breakthrough result of Lee, Raghavendra, and Steurer [STOC’15], our result implies that for any Γ whose support violates the bounded width condition no SDP relaxation of polynomial size solves VCSP(Γ). We establish our result by proving that various reductions preserve exact solvability by the Lasserre SDP hierarchy (up to a constant factor in the level of the hierarchy). Our results hold for general-valued constraint languages (i.e., sets of functions on a fixed finite domain that take on rational or infinite values) and thus also hold in notable special cases of { 0, ∞ }-valued languages (CSPs), {0, 1}-valued languages (Min-CSPs/Max-CSPs), and Q-valued languages (finite-valued CSPs).

Funder

Royal Society University Research Fellowship

European Research Council

European Union's Horizon 2020 research and innovation programme

Publisher

Association for Computing Machinery (ACM)

Subject

Computational Theory and Mathematics,Theoretical Computer Science

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1. Semidefinite Programming and Linear Equations vs. Homomorphism Problems;Proceedings of the 56th Annual ACM Symposium on Theory of Computing;2024-06-10

2. SDPs and Robust Satisfiability of Promise CSP;Proceedings of the 55th Annual ACM Symposium on Theory of Computing;2023-06-02

3. CLAP: A New Algorithm for Promise CSPs;SIAM Journal on Computing;2023-01-25

4. The Combined Basic LP and Affine IP Relaxation for Promise VCSPs on Infinite Domains;ACM T ALGORITHMS;2021

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