Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
149 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Satisfiability of commutative vs. non-commutative CSPs (2404.11709v3)

Published 17 Apr 2024 in cs.CC, cs.LO, and quant-ph

Abstract: The Mermin-Peres magic square is a celebrated example of a system of Boolean linear equations that is not (classically) satisfiable but is satisfiable via linear operators on a Hilbert space of dimension four. A natural question is then, for what kind of problems such a phenomenon occurs? Atserias, Kolaitis, and Severini answered this question for all Boolean Constraint Satisfaction Problems (CSPs): For 0-Valid-SAT, 1-Valid-SAT, 2-SAT, Horn-SAT, and Dual Horn-SAT, classical satisfiability and operator satisfiability is the same and thus there is no gap; for all other Boolean CSPs, these notions differ as there are gaps, i.e., there are unsatisfiable instances that are satisfiable via operators on Hilbert spaces. We generalize their result to CSPs on arbitrary finite domains and give an almost complete classification: First, we show that NP-hard CSPs admit a separation between classical satisfiability and satisfiability via operators on finite- and infinite-dimensional Hilbert spaces. Second, we show that tractable CSPs of bounded width have no satisfiability gaps of any kind. Finally, we show that tractable CSPs of unbounded width can simulate, in a satisfiability-gap-preserving fashion, linear equations over an Abelian group of prime order $p$; for such CSPs, we obtain a separation of classical satisfiability and satisfiability via operators on infinite-dimensional Hilbert spaces. Furthermore, if $p=2$, such CSPs also have gaps separating classical satisfiability and satisfiability via operators on finite- and infinite-dimensional Hilbert spaces.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (57)
  1. Padmanabhan K Aravind. Bell’s theorem without inequalities and only two distant observers. Found. Phys., 15:397–405, 2002. doi:10.1023/A:1021272729475.
  2. Generalized satisfiability problems via operator assignments. J. Comput. Syst. Sci., 105:171–198, 2019. arXiv:1704.01736, doi:10.1016/J.JCSS.2019.05.003.
  3. Constraint satisfaction problems solvable by local consistency methods. J. ACM, 61(1):3:1–3:19, 2014. doi:10.1145/2556646.
  4. Robustly solvable constraint satisfaction problems. SIAM J. Comput., 45(4):1646–1669, 2016. arXiv:1512.01157, doi:10.1137/130915479.
  5. Polymorphisms, and how to use them. In Andrei Krokhin and Stanislav Živný, editors, The Constraint Satisfaction Problem: Complexity and Approximability, volume 7 of Dagstuhl Follow-Ups, pages 1–44. Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 2017. doi:10.4230/DFU.Vol7.15301.1.
  6. John S Bell. On the problem of hidden variables in quantum mechanics. Rev. Mod. Phys., 38(3):447, 1966. doi:10.1103/RevModPhys.38.447.
  7. Manuel Bodirsky. Complexity of infinite-domain constraint satisfaction, volume 52. Cambridge University Press, 2021.
  8. On the descriptive complexity of temporal constraint satisfaction problems. J. ACM, 70(1):2:1–2:58, 2023. doi:10.1145/3566051.
  9. SDPs and robust satisfiability of promise CSP. In Proc. 55th Annual ACM Symposium on Theory of Computing (STOC’23), pages 609–622. ACM, 2023. arXiv:2211.08373, doi:10.1145/3564246.3585180.
  10. Combinatorial optimization algorithms via polymorphisms. CoRR, abs/1501.01598, 2015. arXiv:1501.01598.
  11. Andrei Bulatov. Bounded relational width. Unpublished manuscript, 2009. URL: https://www2.cs.sfu.ca/~abulatov/papers/relwidth.pdf.
  12. Classifying the complexity of constraints using finite algebras. SIAM J. Comput., 34(3):720–742, 2005. doi:10.1137/S0097539700376676.
  13. Andrei A. Bulatov. A Dichotomy Theorem for Constraints on a Three-Element Set. In Proc. 43rd Symposium on Foundations of Computer Science (FOCS’02), pages 649–658. IEEE Computer Society, 2002. doi:10.1109/SFCS.2002.1181990.
  14. Andrei A. Bulatov. A dichotomy theorem for constraint satisfaction problems on a 3-element set. J. ACM, 53(1):66–120, 2006. doi:10.1145/1120582.1120584.
  15. Andrei A. Bulatov. A dichotomy theorem for nonuniform CSPs. In Proc. 58th Annual IEEE Symposium on Foundations of Computer Science (FOCS’17), pages 319–330, 2017. arXiv:1703.03021, doi:10.1109/FOCS.2017.37.
  16. Consequences and limits of nonlocal strategies. In Proc. 19th Annual IEEE Conference on Computational Complexity (CCC’04), pages 236–249. IEEE Computer Society, 2004. doi:10.1109/CCC.2004.1313847.
  17. Perfect commuting-operator strategies for linear system games. J. Math. Phys., 58(1), 2017. arXiv:1606.02278, doi:10.1063/1.4973422.
  18. Characterization of binary constraint system games. In Proc. 41st International Colloquium on Automata, Languages, and Programming (ICALP’14), volume 8572 of Lecture Notes in Computer Science, pages 320–331. Springer, 2014. doi:10.1007/978-3-662-43948-7_27.
  19. Approximation algorithms for noncommutative constraint satisfaction problems. 2023. arXiv:2312.16765.
  20. Robust Satisfiability for CSPs: Hardness and Algorithmic Results. ACM Trans. Comput. Theory, 5(4):15:1–15:25, 2013. doi:10.1145/2540090.
  21. Closure functions and width 1 problems. In Proc. 4th International Conference on Principles and Practice of Constraint Programming (CP’99), volume 1713 of Lecture Notes in Computer Science, pages 159–173. Springer, 1999. doi:10.1007/978-3-540-48085-3_12.
  22. Some Practicable Filtering Techniques for the Constraint Satisfaction Problem. In Proc. 15th International Joint Conference on Artificial Intelligence (IJCAI’97), pages 412–417. Morgan Kaufmann, 1997.
  23. The computational structure of monotone monadic SNP and constraint satisfaction: A study through Datalog and group theory. SIAM J. Comput., 28(1):57–104, 1998. doi:10.1137/S0097539794266766.
  24. Approximation algorithms for Max-3-Cut and other problems via complex semidefinite programming. J. Comput. Syst. Sci., 68(2):442–470, 2004. doi:10.1016/J.JCSS.2003.07.012.
  25. Tight Bounds on the Approximability of Almost-Satisfiable Horn SAT and Exact Hitting Set. Theory Comput., 8(1):239–267, 2012. doi:10.4086/TOC.2012.V008A011.
  26. Paul R Halmos. Introduction to Hilbert space and the theory of spectral multiplicity. Courier Dover Publications, 2017.
  27. On the complexity of H-coloring. J. Comb. Theory, Ser. B, 48(1):92–110, 1990. doi:10.1016/0095-8956(90)90132-J.
  28. Graphs and homomorphisms, volume 28 of Oxford Lecture Series in Mathematics and its Applications. OUP Oxford, 2004.
  29. How to determine the expressive power of constraints. Constraints, 4(2):113–131, 1999. doi:10.1023/A:1009890709297.
  30. Closure properties of constraints. J. ACM, 44(4):527–548, 1997. doi:10.1145/263867.263489.
  31. Zhengfeng Ji. Binary constraint system games and locally commutative reductions. 2013. arXiv:1310.3794.
  32. MIP*{}^{*}start_FLOATSUPERSCRIPT * end_FLOATSUPERSCRIPT=RE. Technical report, 2020. arXiv:2001.04383.
  33. MIP*{}^{*}start_FLOATSUPERSCRIPT * end_FLOATSUPERSCRIPT = RE. Commun. ACM, 64(11):131–138, 2021. doi:10.1145/3485628.
  34. The problem of hidden variables in quantum mechanics. J. Mathematics and Mechanics, 17(1):59–87, 1967. URL: http://www.jstor.org/stable/24902153.
  35. On the expressive power of datalog: Tools and a case study. J. Comput. Syst. Sci., 51(1):110–134, 1995. doi:10.1006/jcss.1995.1055.
  36. Conjunctive-query containment and constraint satisfaction. J. Comput. Syst. Sci., 61(2):302–332, 2000. doi:10.1006/jcss.2000.1713.
  37. The complexity of general-valued CSPs. SIAM J. Comput., 46(3):1087–1110, 2017. arXiv:1502.07327, doi:10.1137/16M1091836.
  38. Marcin Kozik. Solving CSPs Using Weak Local Consistency. SIAM J. Comput., 50(4):1263–1286, 2021. arXiv:1605.00565, doi:10.1137/18M117577X.
  39. Characterizations of several Maltsev conditions. Algebra universalis, 73(3):205–224, 2015. doi:10.1007/s00012-015-0327-2.
  40. Bounded width problems and algebras. Algebra Univers., 56:439–466, 2007. doi:10.1007/s00012-007-2012-6.
  41. Quantum isomorphism is equivalent to equality of homomorphism counts from planar graphs. In Proc. 61st IEEE Annual Symposium on Foundations of Computer Science (FOCS’20), pages 661–672. IEEE, 2020. doi:10.1109/FOCS46700.2020.00067.
  42. Quantum homomorphisms. J. Comb. Theory, Ser. B, 118:228–267, 2016. doi:10.1016/J.JCTB.2015.12.009.
  43. Existence theorems for weakly symmetric operations. Algebra Univers., 59(3-4):463–489, 2008. doi:10.1007/s00012-008-2122-9.
  44. N. David Mermin. Simple unified form for the major no-hidden-variables theorems. Phys. Rev. Lett., 65(27):3373, 1990. doi:10.1103/PhysRevLett.65.3373.
  45. N. David Mermin. Hidden variables and the two theorems of John Bell. Rev. Mod. Phys., 65(3):803, 1993. doi:10.1103/RevModPhys.65.803.
  46. Ryan O’Donnell. Analysis of Boolean Functions. Cambridge University Press, 2014.
  47. Satisfiability problems and algebras of boolean constraint system games. 2023. arXiv:2310.07901.
  48. Asher Peres. Incompatible results of quantum measurements. Phys. Lett., 151(3-4):107–108, 1990. doi:10.1016/0375-9601(90)90172-K.
  49. E.L. Post. The two-valued iterative systems of mathematical logic, volume 5 of Annals of Mathematical Studies. Princeton University Press, 1941. doi:10.2307/2268608.
  50. Prasad Raghavendra. Optimal algorithms and inapproximability results for every CSP? In Proc. 40th Annual ACM Symposium on Theory of Computing (STOC’08), pages 245–254. ACM, 2008. doi:10.1145/1374376.1374414.
  51. Thomas Schaefer. The complexity of satisfiability problems. In Proc. 10th Annual ACM Symposium on the Theory of Computing (STOC’78), pages 216–226, 1978. doi:10.1145/800133.804350.
  52. William Slofstra. Tsirelson’s problem and an embedding theorem for groups arising from non-local games. J. Am. Math. Soc., 33(1):1–56, 2020. doi:10.1090/jams/929.
  53. The complexity of finite-valued CSPs. J. ACM, 63(4):37:1–37:33, 2016. arXiv:1210.2987, doi:10.1145/2974019.
  54. The power of Sherali–Adams relaxations for general-valued CSPs. SIAM J. Comput., 46(4):1241–1279, 2017. arXiv:1606.02577, doi:10.1137/16M1079245.
  55. The limits of SDP relaxations for general-valued CSPs. ACM Trans. Comput. Theory, 10(3):12:1–12:22, 2018. arXiv:1612.01147, doi:10.1145/3201777.
  56. Dmitriy Zhuk. A proof of CSP dichotomy conjecture. In Proc. 58th Annual IEEE Symposium on Foundations of Computer Science (FOCS’17), pages 331–342, 2017. arXiv:1704.01914, doi:10.1109/FOCS.2017.38.
  57. Dmitriy Zhuk. A proof of the CSP dichotomy conjecture. J. ACM, 67(5):30:1–30:78, 2020. arXiv:1704.01914, doi:10.1145/3402029.

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com