TCS 2014: Theoretical Computer Science pp 104-110 | Cite as

Sensitivity, Block Sensitivity, and Certificate Complexity of Unate Functions and Read-Once Functions

  • Hiroki Morizumi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8705)

Abstract

Sensitivity, block sensitivity, and certificate complexity are complexity measures for Boolean functions. In this paper, we prove that these three complexity measures are equal to each other if a Boolean function is a unate function or a read-once function. We also prove \(\sqrt{n}\) tight lower bounds for the three complexity measures of read-once functions. As an application of our results, the decision tree complexity of unate functions and read-once functions is upper bounded by the square of the sensitivity of the function.

Keywords

Boolean Function Unate Function Monotone Function Complexity Measure Boolean Formula 
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.

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References

  1. 1.
    Ambainis, A., Gao, Y., Mao, J., Sun, X., Zuo, S.: New upper bound on block sensitivity and certificate complexity in terms of sensitivity. CoRR abs/1306.4466 (2013)Google Scholar
  2. 2.
    Ambainis, A., Sun, X.: New separation between s(f) and bs(f). Electronic Colloquium on Computational Complexity (ECCC) 18, 116 (2011)Google Scholar
  3. 3.
    Beals, R., Buhrman, H., Cleve, R., Mosca, M., de Wolf, R.: Quantum lower bounds by polynomials. J. ACM 48(4), 778–797 (2001)CrossRefMATHMathSciNetGoogle Scholar
  4. 4.
    Buhrman, H., de Wolf, R.: Complexity measures and decision tree complexity: a survey. Theor. Comput. Sci. 288(1), 21–43 (2002)CrossRefMATHGoogle Scholar
  5. 5.
    Hatami, P., Kulkarni, R., Pankratov, D.: Variations on the sensitivity conjecture. Theory of Computing, Graduate Surveys 2, 1–27 (2011)Google Scholar
  6. 6.
    Impagliazzo, R., Kabanets, V.: Fourier concentration from shrinkage. Electronic Colloquium on Computational Complexity (ECCC) 20, 163 (2013)Google Scholar
  7. 7.
    Kenyon, C., Kutin, S.: Sensitivity, block sensitivity, and l-block sensitivity of boolean functions. Inf. Comput. 189(1), 43–53 (2004)CrossRefMATHMathSciNetGoogle Scholar
  8. 8.
    Nisan, N.: CREW PRAMs and decision trees. SIAM J. Comput. 20(6), 999–1007 (1991)CrossRefMATHMathSciNetGoogle Scholar
  9. 9.
    Rubinstein, D.: Sensitivity vs. block sensitivity of boolean functions. Combinatorica 15(2), 297–299 (1995)CrossRefMATHMathSciNetGoogle Scholar
  10. 10.
    Virza, M.: Sensitivity versus block sensitivity of boolean functions. Inf. Process. Lett. 111(9), 433–435 (2011)CrossRefMATHMathSciNetGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Hiroki Morizumi
    • 1
  1. 1.Interdisciplinary Graduate School of Science and EngineeringShimane UniversityShimaneJapan

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