Semidefinite Programming and Linear Equations vs. Homomorphism Problems
Lorenzo Ciardo, Stanislav Zivný
Abstract
We introduce a relaxation for homomorphism problems that combines semidefinite programming with linear Diophantine equations, and propose a framework for the analysis of its power based on the spectral theory of association schemes. We use this framework to establish an unconditional lower bound against the semidefinite programming + linear equations model, by showing that the relaxation does not solve the approximate graph homomorphism problem and thus, in particular, the approximate graph colouring problem.
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Install the CLIlune papers fulltext af7c9f14-798e-408c-80ff-c48ebb1e545eCited by top-tier papers5
- New Algorithms and Hardness Results for Robust Satisfiability of (Promise) CSPsJoshua Brakensiek, Lorenzo Ciardo, Venkatesan Guruswami, Aaron Potechin et al.SODA 2026 · 2 citations
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- How Random CSPs Fool HierarchiesSiu On Chan, Hiu Tsun Ng, Sijin PengSTOC 2024 · 1 citation
- On Approximability of Satisfiable k-CSPs: VAmey Bhangale, Subhash Khot, Dor MinzerSTOC 2025
- Lower Bounds for CSP Hierarchies Through Ideal ReductionJonas Conneryd, Yassine Ghannane, Shuo PangSODA 2026
Builds on10
- An Invariance Principle for the Multi-slice, with ApplicationsMark Braverman, Subhash Khot, Noam Lifshitz, Dor MinzerFOCS 2021 · 29 citations
- Local consistency as a reduction between constraint satisfaction problemsVíctor Dalmau, Jakub OprsalLICS 2024 · 15 citations
- Hierarchies of Minion Tests for PCSPs through TensorsLorenzo Ciardo, Stanislav ZivnýSODA 2023 · 13 citations
- Approximate Graph Colouring and the Hollow ShadowLorenzo Ciardo, Stanislav ZivnýSTOC 2023 · 13 citations
- Symmetric Polymorphisms and Efficient Decidability of Promise CSPsJoshua Brakensiek, Venkatesan GuruswamiSODA 2020 · 11 citations
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