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Coalgebraic Tools for Randomness-Conserving Protocols

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11194))

Abstract

We propose a coalgebraic model for constructing and reasoning about state-based protocols that implement efficient reductions among random processes. We provide basic tools that allow efficient protocols to be constructed in a compositional way and analyzed in terms of the tradeoff between latency and loss of entropy. We show how to use these tools to construct various entropy-conserving reductions between processes.

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References

  1. Adamek, J.: Foundations of Coding. Wiley, Hoboken (1991)

    Book  Google Scholar 

  2. Blum, M.: Independent unbiased coin flips from a correlated biased source: a finite state Markov chain. Combinatorica 6(2), 97–108 (1986)

    Article  MathSciNet  Google Scholar 

  3. Böcherer, G., Ali Amjad, R.: Informational divergence and entropy rate on rooted trees with probabilities. In: Proceedings of the IEEE International Symposium on Information Theory (June 2014)

    Google Scholar 

  4. Chung, K.L.: A Course in Probability Theory, 2nd edn. Academic Press, Cambridge (1974)

    MATH  Google Scholar 

  5. Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley-Interscience, Hoboken (1991)

    Book  Google Scholar 

  6. Doberkat, E.-E.: Stochastic Relations: Foundations for Markov Transition Systems. Studies in Informatics. Chapman Hall, London (2007)

    Book  Google Scholar 

  7. Dodis, Y., Elbaz, A., Oliveira, R., Raz, R.: Improved randomness extraction from two independent sources. In: Jansen, K., Khanna, S., Rolim, J.D.P., Ron, D. (eds.) APPROX/RANDOM -2004. LNCS, vol. 3122, pp. 334–344. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-27821-4_30

    Chapter  Google Scholar 

  8. Elias, P.: The efficient construction of an unbiased random sequence. Ann. Math. Stat. 43(3), 865–870 (1992)

    Article  Google Scholar 

  9. Feller, W.: An Introduction to Probability Theory and Its Applications, vol. 1, 2nd edn. Wiley, Hoboken (1971)

    MATH  Google Scholar 

  10. Hirschler, T., Woess, W.: Comparing entropy rates on finite and infinite rooted trees with length functions. IEEE Trans. Inf. Theory (2017)

    Google Scholar 

  11. Kozen, D., Soloviev, M.: Coalgebraic tools for randomness-conserving protocols. Technical report, Cornell, July 2018. https://arxiv.org/abs/1807.02735

  12. Nisan, N., Ta-shma, A.: Extracting randomness: a survey and new constructions. J. Comput. Syst. Sci. 58, 148–173 (1999)

    Article  MathSciNet  Google Scholar 

  13. Pae, S., Loui, M.C.: Optimal random number generation from a biased coin. In: Proceedings of the 16th ACM-SIAM Symposium on Discrete Algorithms, Vancouver, Canada, pp. 1079–1088, January 2005

    Google Scholar 

  14. Pae, S., Loui, M.C.: Randomizing functions: Simulation of discrete probability distribution using a source of unknown distribution. Trans. Inf. Theory 52(11), 4965–4976 (2006)

    Article  MathSciNet  Google Scholar 

  15. Panangaden, P.: Labelled Markov Processes. Imperial College Press, London (2009)

    Book  Google Scholar 

  16. Peres, Y.: Iterating von Neumann’s procedure for extracting random bits. Ann. Stat. 20(1), 590–597 (1992)

    Article  MathSciNet  Google Scholar 

  17. Peres, Y., Mossel, E., Hillar, C.: New coins from old: computing with unknown bias. Combinatorica 25(6), 707–724 (2005)

    Article  MathSciNet  Google Scholar 

  18. Srinivasan, A., Zuckerman, D.: Computing with very weak random sources. SIAM J. Comput. 28, 264–275 (1999)

    Article  MathSciNet  Google Scholar 

  19. Ta-shma, A.: On extracting randomness from weak random sources. In: Proceedings of the 28th ACM Symposium Theory of Computing, pp. 276–285 (1996)

    Google Scholar 

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Acknowledgments

Thanks to Joel Ouaknine and Aaron Wagner for valuable discussions. Thanks to the Bellairs Research Institute of McGill University for providing a wonderful research environment. Research was supported by NSF grants CCF1637532, IIS-1703846, and IIS-1718108, AFOSR grant FA9550-12-1-0040, ARO grant W911NF-17-1-0592, and a grant from the Open Philanthropy project.

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Correspondence to Dexter Kozen .

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Kozen, D., Soloviev, M. (2018). Coalgebraic Tools for Randomness-Conserving Protocols. In: Desharnais, J., Guttmann, W., Joosten, S. (eds) Relational and Algebraic Methods in Computer Science. RAMiCS 2018. Lecture Notes in Computer Science(), vol 11194. Springer, Cham. https://doi.org/10.1007/978-3-030-02149-8_18

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  • DOI: https://doi.org/10.1007/978-3-030-02149-8_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02148-1

  • Online ISBN: 978-3-030-02149-8

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