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Approximating the unsatisfiability threshold of random formulas (Extended Abstract)

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Algorithms — ESA '96 (ESA 1996)

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Abstract

Let φ be a random Boolean formula that is an instance of 3-SAT. We consider the problem of computing the least real number κ such that if the ratio of the number of clauses over the number of variables of φ strictly exceeds κ, then φ is almost certainly unsatisfiable. By a well known and more or less straightforward argument, it can be shown that k ≤ 5.191. This upper bound was improved by Kamath, Motwani, Palem, and Spirakis to 4.758, by first providing new improved bounds for the occupancy problem. There is strong experimental evidence that the value of κ is around 4.2. In this work, we define, in terms of the random formula φ, a decreasing sequence of random variables such that if the expected value of any one of them converges to zero, then φ is almost certainly unsatisfiable. By letting the expected value of the first term of the sequence converge to zero, we obtain, by simple and elementary computations, an upper bound for κ equal to 4.667. From the expected value of the second term of the sequence, we get the value 4.598. In general, by letting the expected value of further terms of this sequence converge to zero, one can, if the calculations are performed, obtain even better approximations to κ. This technique generalizes in a straightforward manner to κ-SAT, for κ > 3.

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References

  1. M. Abramowitz and I. E. Stegun (eds.), Handbook of Mathematical Functions With Formulas, Graphs, and Mathematical Tables, 10th printing, U.S. Department of Commerce, National Bureau of Standards, Washington, 1972.

    Google Scholar 

  2. D. Achlioptas, L. M. Kirousis, E. Kranakis, D. Krizanc, M. S.O. Molloy, A Correlation Inequality and Its Application to a Word Problem, Technical Report 96-11, School of Computer Science, Carleton University.

    Google Scholar 

  3. D. J. Aldous, “The harmonic mean formula for probabilities of unions: applications to sparse random graphs”, Discrete Mathematics 76, pp 167–176, 1989.

    Google Scholar 

  4. V. Chvátal and B. Reed, “Mick gets some (the odds are on his side)”, Proc. 33rd IEEE Symposium on Foundations of Computer Science, pp 620–627, 1992.

    Google Scholar 

  5. V. Chvátal and E. Szemerédi, “Many hard examples for resolution”, Journal of the Association for Computing Machinery 35, pp 759–768, 1988.

    Google Scholar 

  6. J. Franco and M. Paull, “Probabilistic analysis of the Davis-Putnam procedure for solving the satisfiability problem”, Discrete Applied Mathematics 5, pp 77–87, 1983.

    Article  Google Scholar 

  7. G. Gasper and M. Rahman, Basic Hypergeometric Series, Encyclopedia of Mathematics and its Applications, vol 35, Cambridge University Press, Cambridge, 1990.

    Google Scholar 

  8. S. Janson, “Poisson approximation for large deviations”, Random Structures and Algorithms 1, pp 221–230, 1990.

    Google Scholar 

  9. A. Kamath, R. Motwani, K. Palem, and P. Spirakis, “Tail bounds for occupancy and the satisfiability threshold conjecture”, Random Structures and Algorithms 7, pp 59–80, 1995. Also in: Proc. 35th FOCS, IEEE, pp 592–603, 1994

    Google Scholar 

  10. L. Kirousis, E. Kranakis, and D. Krizanc, An Upper Bound for a Basic Hypergeometric Series, Carleton University, School of Computer Science, Technical Report TR-96-07, 1996.

    Google Scholar 

  11. S. Kirkpatrick and B. Selman, “Critical behavior in the satisfiability of random Boolean expressions”, Science 264, pp 1297–1301, 1994.

    Google Scholar 

  12. D. Knuth, Fundamental Algorithms, The Art of Computer Programming, vol. 1, 2nd edition, Addison-Wesley, Reading, Massachusetts, 1973.

    Google Scholar 

  13. D. Redfern, The Maple Handbook: Maple V Release 3, Springer-Verlag, New York, 1994.

    Google Scholar 

  14. J.-C. Simon, J. Carlier, O. Dubois, and O. Moulines, “Étude statistique de l'existence de solutions de problèmes SAT, application aux systèmes-experts”, C.R. Acad. Sci. Paris. Sér. I Math. 302, pp 283–286, 1986.

    Google Scholar 

  15. J. H. Spencer, Ten Lectures on the Probabilistic Method, 2nd edition, SIAM, Philadelphia, 1994

    Google Scholar 

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Josep Diaz Maria Serna

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© 1996 Springer-Verlag Berlin Heidelberg

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Kirousis, L.M., Kranakis, E., Krizanc, D. (1996). Approximating the unsatisfiability threshold of random formulas (Extended Abstract). In: Diaz, J., Serna, M. (eds) Algorithms — ESA '96. ESA 1996. Lecture Notes in Computer Science, vol 1136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61680-2_44

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  • DOI: https://doi.org/10.1007/3-540-61680-2_44

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