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Pseudo-partitions, transversality and locality: a combinatorial characterization for the space measure in algebraic proof systems

Published:09 January 2013Publication History

ABSTRACT

We devise a new combinatorial framework for proving space lower bounds in algebraic proof systems like Polynomial Calculus (Pc) and Polynomial Calculus with Resolution (Pcr). Our method can be thought as a Spoiler-Duplicator game, which is capturing boolean reasoning on polynomials instead that clauses as in the case of Resolution. Hence, for the first time, we move the problem of studying the space complexity for algebraic proof systems in the range of 2-players games, as is the case for Resolution.

A very simple case of our method allows us to obtain all the currently known space lower bounds for Pc/Pcr (CTn, PHPmn, BIT-PHPmn, XOR-PHPmn). The way our method applies to all these examples explains how and why all the known examples of space lower bounds for Pc/Pcr are an application of the method originally given by [Alekhnovich et al 2002] that holds for set of contradictory polynomials having high degree. Our approach unifies in a clear way under a common combinatorial framework and language the proofs of the space lower bounds known so far for Pc/Pcr.

More importantly, using our approach in its full potentiality, we answer to the open problem [Alekhnovich et al 2002, Filmus et al 2012] of proving space lower bounds in Polynomial Calculus and Polynomials Calculus with Resolution for the polynomial encoding of randomly chosen k-CNF formulas. Our result holds for k>= 4. Then, as proved for Resolution in [BenSasson and Galesi 2003], also in Pc and in Pcr refuting a random k-CNF over n variables requires high space measure of the order of Omega(n). Our method also applies to the Graph-PHPmn, which is a PHPmn defined over a constant (left) degree bipartite expander graph. We develop a common language for the two examples.

References

  1. Michael Alekhnovich, Eli Ben-Sasson, Alexander A. Razborov, and Avi Wigderson. Space complexity in propositional calculus. SIAM J. Comput., 31(4):1184--1211, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Michael Alekhnovich and Alexander A. Razborov. Lower bounds for polynomial calculus: Non-binomial case. In 42nd Annual Symposium on Foundations of Computer Science, pages 190--199, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Albert Atserias. On sufficient conditions for unsatisfiability of random formulas. Journal of ACM, 51(2):281--311, 2004. A preliminary version appeared in the Proceedings of the 17th IEEE Symposium on Logic in Computer Sience (LICS), pagine 325--334, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Albert Atserias and Víctor Dalmau. A combinatorial characterization of resolution width. J. Comput. Syst. Sci., 74(3):323--334, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Albert Atserias, J. Fichte, and M. Thurley. Clause-learning algorithms with many restarts and bounded-width resolution. Theory and Applications of Satisfiability Testing-SAT 2009, pages 114--127, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Paul Beame, Henry A. Kautz, and Ashish Sabharwal. Towards understanding and harnessing the potential of clause learning. J. Artif. Intell. Res. (JAIR), 22:319--351, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Paul Beame and Toniann Pitassi. Simplified and improved resolution lower bounds. In 37th Annual Symposium on Foundations of Computer Science, pages 274 -- 282. IEEE, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Eli Ben-sasson. Expansion in Proof Complexity. PhD thesis, Hebrew University, 2001.Google ScholarGoogle Scholar
  9. Eli Ben-Sasson and Nicola Galesi. Space complexity of random formulae in resolution. Random Struct. Algorithms, 23(1):92--109, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Eli Ben-Sasson and Russell Impagliazzo. Random CNFs are hard for the polynomial calculus. In 40th Annual Symposium on Foundations of Computer Science, pages 415--421, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Eli Ben-Sasson and Jan Johannsen. Lower bounds for width-restricted clause learning on small width formulas. Theory and Applications of Satisfiability Testing--SAT 2010, pages 16--29, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Eli Ben-Sasson and Jakob Nordström. A space hierarchy for k-dnf resolution. Electronic Colloquium on Computational Complexity (ECCC), 16(047), 2009.Google ScholarGoogle Scholar
  13. Eli Ben-Sasson and Jakob Nordström. Understanding space in resolution: Optimal lower bounds and exponential trade-offs. Electronic Colloquium on Computational Complexity (ECCC), 16(034), 2009.Google ScholarGoogle Scholar
  14. Eli Ben-Sasson and Avi Wigderson. Short proofs are narrow - resolution made simple. J. ACM, 48(2):149--169, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Archie Blake. Canonical Expressions in Boolean Algebra. PhD thesis, University of Chicago, 1938.Google ScholarGoogle Scholar
  16. Michael Brickenstein and Alexander Dreyer. Polybori: A framework for gröbner-basis computations with boolean polynomials. J. Symb. Comput, 44(9):1326--1345, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Sam Buss, Maria Luisa Bonet, and Jan Johannsen. Improved separations of regular resolution from clause learning proof systems. Submitted, 2012.Google ScholarGoogle Scholar
  18. Sam Buss, Jan Hoffman, and Jan Johannsen. Resolution trees with lemmas - resolution refinements that characterize dll-algorithms with clause learning. Logical Methods in Computer Science, 4,:4:13, 2008.Google ScholarGoogle Scholar
  19. Samuel R. Buss, Dima Grigoriev, Russell Impagliazzo, and Toniann Pitassi. Linear gaps between degrees for the polynomial calculus modulo distinct primes. J. Comput. Syst. Sci., 62(2):267--289, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Samuel R. Buss, Russell Impagliazzo, Jan Krajícek, Pavel Pudlák, Alexander A. Razborov, and Jirí Sgall. Proof complexity in algebraic systems and bounded depth frege systems with modular counting. Computational Complexity, 6(3):256--298, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Vasek Chvátal and Endre Szemerédi. Many hard examples for resolution. J. ACM, 35(4):759--768, 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Matthew Clegg, Jeff Edmonds, and Russell Impagliazzo. Using the Gröebner basis algorithm to find proofs of unsatisfiability. In Proceedings of the Twenty-Eighth Annual ACM Symposium on the Theory of Computing, pages 174--183, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Stephen A. Cook and Robert A. Reckhow. The relative efficiency of propositional proof systems. Journal of Symbolic Logic, 44:36--50, 1979.Google ScholarGoogle ScholarCross RefCross Ref
  24. David Cox, John Little, and Donal O'Shea. Ideals, Varieties, and Algorithms : An Introduction to Computational Algebraic Geometry and Commutative Algebra, 3rd edition. Springer, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Martin Davis, George Logemann, and Donald Loveland. A machine program for theorem-proving. Commun. ACM, 5:394--397, July 1962. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Martin Davis and Hilary Putnam. A computing procedure for quantification theory. J. ACM, 7:201--215, July 1960. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Juan Luis Esteban, Nicola Galesi, and Jochen Messner. On the complexity of resolution with bounded conjunctions. Theor. Comput. Sci., 321(2--3):347--370, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Juan Luis Esteban and Jacobo Torán. Space bounds for resolution. Information and Computation, 171(1):84--97, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Tomás Feder and Moshe Y. Vardi. 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. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Yuval Filmus, Massimo Lauria, Jakob Nordström, Neil Thapen, and Noga Zewi. Space complexity in polynomial calculus. In IEEE Conference on Computational Complexity 2012, 2012. To appear. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Nicola Galesi and Massimo Lauria. On the automatizability of polynomial calculus. Theory of Computing Systems, 47(2):491--506, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Nicola Galesi and Massimo Lauria. Optimality of size-degree trade-offs for polynomial calculus. ACM Transactions on Computational Logic, 12(1):??, 2010. To appear. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Russell Impagliazzo, Pavel Pudlák, and Jirí Sgall. Lower bounds for the polynomial calculus and the gröbner basis algorithm. Computational Complexity, 8(2):127--144, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Jan Krajícek. Propositional proof complexity i. 2009.Google ScholarGoogle Scholar
  35. Joao P. Marques-Silva and Karem A. Sakallah. Grasp--a new search algorithm for satisfiability. In Proceedings of the IEEE/ACM International Conference on Computer-Aided Design (ICCAD '96),, pages 220--227, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Jakob Nordström. Narrow proofs may be spacious: separating space and width in resolution. In STOC, pages 507--516, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Jakob Nordström and Johan Håstad. Towards an optimal separation of space and length in resolution. In STOC, pages 701--710, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Pavel Pudlák and Jirí Sgall. Algebraic models of computation and interpolation for algebraic proof systems. DIMACS series in Theoretical Computer Science, 39:279--296, 1998.Google ScholarGoogle Scholar
  39. Alexander Razborov. Pseudorandom generators hard for k-dnf resolution and polynomial calculus resolution. Manuscript availbale at author's webpage, 2003.Google ScholarGoogle Scholar
  40. Alexander A. Razborov. Lower bounds for the polynomial calculus. Computational Complexity, 7(4):291--324, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library

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            • Published in

              cover image ACM Conferences
              ITCS '13: Proceedings of the 4th conference on Innovations in Theoretical Computer Science
              January 2013
              594 pages
              ISBN:9781450318594
              DOI:10.1145/2422436

              Copyright © 2013 ACM

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              Publication History

              • Published: 9 January 2013

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