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Extractors and Rank Extractors for Polynomial Sources

  • Ariel GabizonEmail author
Chapter
Part of the Monographs in Theoretical Computer Science. An EATCS Series book series (EATCS)

Summary

In this chapter we construct explicit deterministic extractors from polynomial sources, namely from distributions sampled by low-degree multivariate polynomials over finite fields. This naturally generalizes previous work on extraction from affine sources (which are degree 1 polynomials). A direct consequence is a deterministic extractor for distributions sampled by polynomial-size arithmetic circuits over exponentially large fields.

The steps in our extractor construction, and the tools (mainly from algebraic geometry) that we use for them, are of independent interest.

The first step is a construction of rank extractors, which are polynomial mappings that “extract” the algebraic rank from any system of low-degree polynomials. More precisely, for any n polynomials, k of which are algebraically independent, a rank extractor outputs k algebraically independent polynomials of slightly higher degree. The rank extractors we construct are applicable not only over finite fields but also over fields of characteristic zero.

The next step is relating algebraic independence to min-entropy. We use a theorem of Wooley to show that these parameters are tightly connected. This allows replacing the algebraic assumption on the source (above) by the natural information-theoretic one. It also shows that a rank extractor is already a high-quality condenser for polynomial sources over polynomially large fields.

Finally, to turn the condensers into extractors, we employ a theorem of Bombieri, giving a character sum estimate for polynomials defined over curves. It allows extracting all the randomness (up to a multiplicative constant) from polynomial sources over exponentially large fields.

Keywords

Finite Field Convex Combination Full Rank Arithmetic Circuit Partial Derivative Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 3.
    B. Barak, R. Impagliazzo, and A. Wigderson. Extracting randomness using few independent sources. SIAM J. Comput, 36(4):1095–1118, 2006.MathSciNetzbMATHCrossRefGoogle Scholar
  2. 5.
    B. Barak, A. Rao, R. Shaltiel, and A. Wigderson. 2-source dispersers for sub-polynomial entropy and Ramsey graphs beating the Frankl–Wilson construction. In Proceedings of the 38th Annual ACM Symposium on Theory of Computing, pages 671–680, 2006.Google Scholar
  3. 8.
    E. Bombieri. On exponential sums in finite fields.American Journal of Mathematics, 88:71–105, 1966.MathSciNetzbMATHCrossRefGoogle Scholar
  4. 10.
    J. Bourgain. On the construction of affine extractors.Geometric And Functional Analysis, 17(1):33–57, 2007.MathSciNetzbMATHCrossRefGoogle Scholar
  5. 21.
    R. Ehrenborg and G. Rota. Apolarity and canonical forms for homogeneous polynomials.Europ. J. Combinatorics, 14:157–181, 1993.MathSciNetzbMATHCrossRefGoogle Scholar
  6. 28.
    F. R. Gantmacher.The Theory of Matrices, volume 1. New York, NY, 1959.Google Scholar
  7. 29.
    O. Goldreich. Three XOR-lemmas - an exposition.Electronic Colloquium on Computational Complexity (ECCC), 2(056), 1995. Google Scholar
  8. 38.
    N. Kayal. The complexity of the annihilating polynomial.Manuscript, 2007.Google Scholar
  9. 39.
    R. Lide and H. Niederreiter.Finite fields. Cambridge University Press, New York, NY, USA, 1997.Google Scholar
  10. 43.
    M. S. L’vov. Calculation of invariants of programs interpreted over an integrality domain. Kibernetika, (4):23–28, 1984.MathSciNetGoogle Scholar
  11. 47.
    N. Nisan and D. Zuckerman. More deterministic simulation in logspace. In Proceedings of the Twenty-Fifth Annual ACM Symposium on Theory of Computing, pages 235–244, New York, NY, USA, 1993. ACM Press.Google Scholar
  12. 51.
    A. Rao. An exposition of Bourgain’s 2-source extractor. Technical Report TR07-034, ECCC, 2007.Google Scholar
  13. 54.
    R. Raz, O. Reingold, and S. Vadhan. Error reduction for extractors. In Proceedings of the 40th Annual IEEE Symposium on Foundations of Computer Science, 1999.Google Scholar
  14. 60.
    J. T. Schwartz. Fast probabilistic algorithms for verification of polynomial identities. J. ACM, 27(4):701–717, 1980.zbMATHCrossRefGoogle Scholar
  15. 68.
    L. Trevisan and S. Vadhan. Extracting randomness from samplable distributions. In Proceedings of the 41st Annual Symposium on Foundations of Computer Science, pages 32–42, 2000b.Google Scholar
  16. 73.
    T. Wooley. A note on simultaneous congruences. J. Number Theory, 58:288–297, 1996.MathSciNetzbMATHCrossRefGoogle Scholar
  17. 76.
    R. Zippel. Probabilistic algorithms for sparse polynomials. In Proceedings of the International Symposium on Symbolic and Algebraic Computation, pages 216–226. Springer-Verlag, 1979.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Dept. Computer ScienceUniversity of Texas at AustinAustinUSA

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