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Minimum propositional proof length is NP-hard to linearly approximate

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Mathematical Foundations of Computer Science 1998 (MFCS 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1450))

Abstract

We prove that the problem of determining the minimum propositional proof length is NP-hard to approximate within any constant factor. These results hold for all Frege systems, for all extended Frege systems, for resolution and Horn resolution, and for the sequent calculus and the cut-free sequent calculus. Also, if NP is not in \(QP = DTIME(n^{log^{O(1)} n} )\), then it is impossible to approximate minimum propositional proof length within a factor of \(2^{log^{(1 - \varepsilon )} n}\) for any є > 0. All these hardness of approximation results apply to proof length measured either by number of symbols or by number of inferences, for tree-like or dag-like proofs. We introduce the Monotone Minimum (Circuit) Satisfying Assignment problem and prove the same hardness results for Monotone Minimum (Circuit) Satisfying Assignment.

Supported in part by INTAS grant N96-753

Supported in part by NSF grant DMS-9503247 and grant INT-9600919/ME-103 from NSF and MšMT (Czech Republic)

Research supported by the Bernard Elkin Chair for Computer Science and by US-Israel grant 95-00238

Supported in part by NSF grant CCR-9457782, US-Israel BSF grant 95-00238, and grant INT-9600919/ME-103 from NSF and MSMT (Czech Republic)

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References

  1. S. Arora, L. Babai, J. Stern, and Z. Sweedyk, The hardness of approximate optima in lattices, codes, and systems of linear equations, Journal of Computer and System Sciences, 54 (1997), pp. 317–331. Earlier version in Proc. 34th Symp. Found. of Comp. Sci., 1993, pp.724–733.

    Article  MATH  MathSciNet  Google Scholar 

  2. S. Arora and C. Lund, Hardness of approximations, in Approximation Algorithms for NP-hard Problems, D. S. Hochbaum, ed., PWS Publishing Co., Boston, 1996, p. ???

    Google Scholar 

  3. P. Beame and T. Pitassi, Simplified and improved resolution lower bounds, in Proceedings, 37th Annual Symposium on Foundations of Computer Science, Los Alamitos, California, 1996, IEEE Computer Society, pp. 274–282.

    Google Scholar 

  4. M. Bellare, Proof checking and approximation: Towards tight results, SIGACT News, 27 (1996), pp. 2–13. Revised version at http://www-cse.ucsd.edu/users/mihir.

    Article  Google Scholar 

  5. M. Bellare, S. Goldwasser, C. Lund, and A. Russell, Efficient probabalistically checkable proofs and applications to approximation, in Proceedings of the Twenty-Fifth Annual ACM Symposium on Theory of Computing, Association for Computing Machinery, 1993, pp. 294–304.

    Google Scholar 

  6. M. L. Bonet, T. Pitassi, and R. Raz, No feasible interpolation for TC0-Frege proofs, in Proceedings of the 38th Annual Symposium on Foundations of Computer Science, Piscataway, New Jersey, 1997, IEEE Computer Society, pp. 264–263.

    Google Scholar 

  7. S. R. Buss, On Gödel's theorems on lengths of proofs II: Lower bounds for recognizing k symbol provability, in Feasible Mathematics II, P. Clote and J. Remmel, eds., Birkhäauser-Boston, 1995, pp. 57–90.

    Google Scholar 

  8. M. Clegg, J. Edmonds, and R. Impagliazzo, Using the Groebner basis algorithm to find proofs of unsatisfiability, in Proceedings of the Twenty-eighth Annual ACM Symposium on the Theory of Computing, Association for Computing Machinery, 1996, pp. 174–183.

    Google Scholar 

  9. U. Feige, A threshold of ln n for approximating set cover, in Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing, Association for Computing Machinery, 1996, pp. 314–318.

    Google Scholar 

  10. K. Iwama, Complexity of finding short resolution proofs, in Mathematical Foundations of Computer Science 1997, I. Prívara and P. Ruzicka, eds., Lecture Notes in Computer Science #1295, Springer-Verlag, 1997, pp. 309–318.

    Google Scholar 

  11. K. Iwama and E. Miyano, Intractibility of read-once resolution, in Proceedings of the Tenth Annual Conference on Structure in Complexity Theory, Los Alamitos, California, 1995, IEEE Computer Society, pp. 29–36.

    Google Scholar 

  12. S. Khanna, M. Sudan, and L. Trevisan, Constraint satisfaction: The approximability of minimization problems, in Twelfth Annual Conference on Computational Complexity, IEEE Computer Society, 1997, pp. 282–296.

    Google Scholar 

  13. J. Krajíček and P. Pudlák, Some consequences of cryptographic conjectures for S 12 and EF, in Logic and Computational Complexity, D. Leivant, ed., Berlin, 1995, Springer-Verlag, pp. 210–220.

    Google Scholar 

  14. C. Lund and M. Yannakakis, On the hardness of approximating minimization problems, Journal of the Association for Computing Machinery, 41 (1994), pp. 960–981.

    MATH  MathSciNet  Google Scholar 

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Luboš Brim Jozef Gruska Jiří Zlatuška

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© 1998 Springer-Verlag Berlin Heidelberg

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Alekhnovich, M., Buss, S., Moran, S., Pitassi, T. (1998). Minimum propositional proof length is NP-hard to linearly approximate. In: Brim, L., Gruska, J., Zlatuška, J. (eds) Mathematical Foundations of Computer Science 1998. MFCS 1998. Lecture Notes in Computer Science, vol 1450. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0055766

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  • DOI: https://doi.org/10.1007/BFb0055766

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