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Microscopic Reversibility and Macroscopic Irreversibility: From the Viewpoint of Algorithmic Randomness

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Abstract

The emergence of deterministic and irreversible macroscopic behavior from deterministic and reversible microscopic dynamics is understood as a result of the law of large numbers. In this paper, we prove on the basis of the theory of algorithmic randomness that Martin-Löf random initial microstates satisfy an irreversible macroscopic law in the Kac infinite chain model. We find that the time-reversed state of a random state is not random as well as it violates the macroscopic law.

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References

  1. Lebowitz, J.L.: Boltzmann’s entropy and time’s arrow. Phys. Today 46, 32–38 (1993)

    Google Scholar 

  2. Bricmont, J.: Science of Chaos or Chaos in science? In: Gross, P.R., Levitt, N., Lewis, M.W. (eds.) The Flight from Science and Reason, vol. 775, pp. 131–175. Annals of the New York Academy of Sciences, New York (1996)

    Google Scholar 

  3. Lebowitz, J.L., Presutti, E., Spohn, H.: Microscopic models of hydrodynamic behavior. J. Stat. Phys. 51, 841 (1988)

    ADS  MathSciNet  MATH  Google Scholar 

  4. Loschmidt, J.: Über den Zustand des Wärmegleichgewichtes eines Systems von Körpern mit Rücksicht auf die Schwerkraft. Sitzungsber. Kais. Akad. Wiss. Wien, Math. Naturwiss. Cl. Abt. II 73, 128 (1876)

    Google Scholar 

  5. Zermelo, E.: Über einen Satz der Dynamik und die mechanische Wärmetheorie. Wied. Ann. 57, 485–494 (1896)

    MATH  Google Scholar 

  6. Li, M., Vitányi, P.M.B.: An Introduction to Kolmogorov Complexity and Its Applications. Springer-Verlag, New York (2008)

    MATH  Google Scholar 

  7. Nies, A.: Computability and Randomness. Oxford University Press, Oxford (2009)

    MATH  Google Scholar 

  8. Downey, R.G., Hirschfeld, D.R.: Algorithmic Randomness and Complexity. Springer-Verlag, New York (2010)

    MATH  Google Scholar 

  9. Gács, P.: Lecture notes on descriptional complexity and randomness. http://www.cs.bu.edu/faculty/gacs/papers/ait-notes.pdf

  10. Martin-Löf, P.: The definition of random sequences. Inf. Control 9, 602–619 (1966)

    MathSciNet  MATH  Google Scholar 

  11. Kac, M.: Probability and Related Topics in Physical Science. Interscience Publishers Inc., New York (1959)

    MATH  Google Scholar 

  12. Gottwald, G.A., Oliver, M.: Boltzmann’s Dilemma: an introduction to statistical mechanics via the Kac Ring. SIAM Rev. 51, 613–635 (2009)

    ADS  MathSciNet  MATH  Google Scholar 

  13. Maes, C., Netočný, K., Shergelashvili, B.: A selection of nonequilibrium issues. In: Kotecký, R. (ed.) Methods of Contemporary Mathematical Statistical Physics. Lecture Notes in Mathematics, vol. 1970, pp. 247–306. Springer, Berlin (2009)

    MATH  Google Scholar 

  14. Sasa, S., Komatsu, T.S.: Thermodynamic irreversibility from high-dimensional Hamiltonian chaos. Prog. Theor. Phys. 103, 1–52 (2000)

    ADS  MathSciNet  Google Scholar 

  15. Bennett, C.H.: The thermodynamics of computation a review. Int. J. Theor. Phys. 21, 905–940 (1982)

    Google Scholar 

  16. Zurek, W.H.: Thermodynamic cost of computation, algorithmic complexity and the information metric. Nature 341, 119–124 (1989)

    ADS  Google Scholar 

  17. Zurek, W.H.: Algorithmic randomness and physical entropy. Phys. Rev. A 40, 4731 (1989)

    ADS  MathSciNet  Google Scholar 

  18. Caves, C.M.: Information and entropy. Phys. Rev. E. 47, 4010 (1993)

    ADS  Google Scholar 

  19. Gács, P.: The Boltzmann Entropy and Randomness Tests. Proc. Workshop on Physics and Computation, IEEE, pp. 209–216 (1994)

  20. Cooper, S.B.: Computability Theory. Chapman and Hall/CRC, Boca Raton (2004)

    MATH  Google Scholar 

  21. Odifreddi, P.: Classical Recursion Theory, vol. 1. North-Holland Publishing Company, Amsterdam (1990)

    MATH  Google Scholar 

  22. Odifreddi, P.: Classical Recursion Theory, vol. 2. North-Holland Publishing Company, Amsterdam (1999)

    MATH  Google Scholar 

  23. Ville, J.: Étude Critique de la Notion de Collectif. Monographies des Probabilitités. Calcul des Probabilités et ses Applications. Gauthier-Villars, Paris (1939)

    Google Scholar 

  24. Bienvenu, L., Porter, C.: Strong reductions in effective randomness. Theor. Comput. Sci. 459, 55–68 (2012)

    MathSciNet  MATH  Google Scholar 

  25. Solomonoff, R.J.: A formal theory of inductive inference. Part I. Inf. Control 7, 1–22 (1964)

    MathSciNet  MATH  Google Scholar 

  26. Solomonoff, R.J.: A formal theory of inductive inference. Part II. Inf. Control 7, 224–254 (1964)

    MathSciNet  MATH  Google Scholar 

  27. Kolmogorov, A.N.: Three approaches to the quantitative definition of information. Probl. Inf. Transm. 1, 1–7 (1965)

    Google Scholar 

  28. Doob, J.L.: Stochastic Processes. Wiley, New York (1953)

    MATH  Google Scholar 

  29. Zubarev, D.N., Morozov, V., Ropke, G.: Statistical Mechanics of Nonequilibrium Processes. Basic Concepts, Kinetic Theory, vol. 1. Wiley, New York (1996)

    MATH  Google Scholar 

  30. Zubarev, D.N., Morozov, V., Ropke, G.: Statistical Mechanics of Nonequilibrium Processes. Relaxation and Hydrodynamic Processes, vol. 2. Wiley, New York (1997)

    MATH  Google Scholar 

  31. van Lambalgen, M.: Random sequences. Ph.D. Thesis, University of Amsterdam, Amsterdam (1987)

  32. Cover, T.M., Thomas, J.A.: Elements of Information Theory, 2nd edn. Wiley, New York (2012)

    MATH  Google Scholar 

  33. Lefevere, R.: Macroscopic diffusion from a Hamilton-like dynamics. J. Stat. Phys. 151, 861 (2013)

    ADS  MathSciNet  MATH  Google Scholar 

  34. Lefevere, R.: Fick’s law in a random lattice lorentz gas. Arch. Ration. Mech. Anal. 216, 983 (2015)

    MathSciNet  MATH  Google Scholar 

  35. Gács, P.: Uniform test of algorithmic randomness over a general space. Theor. Comput. Sci. 341, 91–137 (2005)

    MathSciNet  MATH  Google Scholar 

  36. Hoyrup, M., Rojas, C.: Computability of probability measures and Martin-Löf randomness over metric spaces. Inf. Comput. 207, 830–847 (2009)

    MathSciNet  MATH  Google Scholar 

  37. Galatolo, S., Hoyrup, M., Rojas, C.: Effective symbolic dynamics, random points, statistical behavior, complexity and entropy. Inf. Comput. 208, 23–41 (2010)

    MathSciNet  MATH  Google Scholar 

  38. Gács, P., Hoyrup, M., Rojas, C.: Randomness on computable probability spaces—a dynamical point of view. Theor. Comput. Syst. 48, 465–486 (2011)

    MathSciNet  MATH  Google Scholar 

  39. Gács, P.: Quantum algorithmic entropy. J. Phys. A. 34, 6859–6880 (2001)

    ADS  MathSciNet  MATH  Google Scholar 

  40. Vitányi, P.M.: Quantum Kolmogorov complexity based on classical descriptions. IEEE Trans. Inf. Theo. 47, 2464–2479 (2001)

    MathSciNet  MATH  Google Scholar 

  41. Nies, A., Scholz, V.: Martin-Löf quantum states. arXiv:1709.08422

  42. Tasaki, H.: Typicality of thermal equilibrium and thermalization in isolated macroscopic quantum systems. J. Stat. Phys. 163, 937–997 (2016)

    ADS  MathSciNet  MATH  Google Scholar 

  43. Goldstein, S., Lebowitz, J.L., Tumulka, R., Zanghí, N.: Canonical typicality. Phys. Rev. Lett. 96, 050403 (2006)

    ADS  MathSciNet  Google Scholar 

  44. Popescu, S., Short, A.J., Winter, A.: Entanglement and the foundations of statistical mechanics. Nat. Phy. 2, 754 (2006)

    Google Scholar 

  45. Sugita, A.: On the basis of quantum statistical mechanics. Nonlinear Phenom. Complex Syst. 10, 192 (2007)

    MathSciNet  Google Scholar 

  46. Reimann, P.: Typicality for generalized microcanonical ensembles. Phys. Rev. Lett. 99, 160404 (2007)

    ADS  Google Scholar 

  47. Rigol, M., Dunjko, V., Olshanii, M.: Thermalization and its mechanism for generic isolated quantum systems. Nature 452, 854 (2008)

    ADS  Google Scholar 

  48. Iyoda, E., Kaneko, K., Sagawa, T.: Fluctuation theorem for many-body pure quantum states. Phys. Rev. Lett. 119, 100601 (2017)

    ADS  MathSciNet  Google Scholar 

  49. Kaneko, K., Iyoda, E., Sagawa, T.: Work extraction from a single energy eigenstate. Phys. Rev. E 99, 032128 (2019)

    ADS  Google Scholar 

  50. Chetrite, R., Gupta, S.: Two refreshing views of fluctuation theorems through kinematics elements and exponential martingale. J. Stat. Phys. 143, 543 (2011)

    ADS  MathSciNet  MATH  Google Scholar 

  51. Neri, I., Rolán, É., Jülicher, F.: Statistics of infima and stopping times of entropy production and applications to active molecular processes. Phys. Rev. X. 7, 011019 (2017)

    Google Scholar 

  52. Shafer, G., Vovk, V.: Probability and Finance: It’s Only a Game!. Wiley, New York (2001)

    MATH  Google Scholar 

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Acknowledgements

The authors thank Naoto Shiraishi and Takahiro Sagawa for their useful comments. The present work was supported by JSPS KAKENHI Grant Number JP17H01148.

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Correspondence to Ken Hiura.

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Communicated by Hal Tasaki.

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Hiura, K., Sasa, Si. Microscopic Reversibility and Macroscopic Irreversibility: From the Viewpoint of Algorithmic Randomness. J Stat Phys 177, 727–751 (2019). https://doi.org/10.1007/s10955-019-02387-0

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