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From Randomness and Entropy to the Arrow of Time

Published online by Cambridge University Press:  16 February 2024

Lena Zuchowski
Affiliation:
University of Bristol

Summary

The Element reconstructs, analyses and compares different derivational routes to a grounding of the Arrow of Time in entropy. It also evaluates the link between entropy and visible disorder, and the related claim of an alignment of the Arrow of Time with a development from order to visible disorder. The Element identifies three different entropy-groundings for the Arrow of Time: (i) the Empirical Arrow of Time, (ii) the Universal Statistical Arrow of Time, and (iii) the Local Statistical Arrow of Time. The Element will also demonstrate that it is unlikely that high entropy states will always coincide with visible disorder. Therefore, it will dispute that there is a strong link between the Arrow of Time and visible disorder.
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Element
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Online ISBN: 9781009217347
Publisher: Cambridge University Press
Print publication: 14 March 2024

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References

Albert, D. Z. (2000). Time and Chance. Cambridge, MA: Harvard University Press.CrossRefGoogle Scholar
Aoki, I. (2012). Entropy Principle for the Development of Complex Biotic Systems: Organisms, Ecosystems, the Earth. London: Elsevier.Google Scholar
Bennett, C. H. (1973). Local Reversibility of Computation. IBM Journal of Research and Development 17, pp. 525–32.CrossRefGoogle Scholar
Bennett, C. H. (1982). The Thermodynamics of Computation: A Review. International Journal of Theoretical Physics 21, pp. 334–7.CrossRefGoogle Scholar
Boltzmann, L. (1872). Weitere Studien ueber Waermegleichgewicht unter Gasmolekuelen. Wiener Berichte 96, pp. 275370.Google Scholar
Boltzmann, L. (1896/1964). Lectures on Gas Theory. New York: Dover.CrossRefGoogle Scholar
Brillouin, L. (1951). Maxwell’s Demon Cannot Operate: Information and Entropy I. Journal of Applied Physics 22, pp. 334–7.CrossRefGoogle Scholar
Brown, H. R. & Uffink, J. (2001). The Origins of Time-Asymmetry in Thermodynamics: The Minus-First Law. Studies in History and Philosophy of Modern Physics 32, pp. 525–38.CrossRefGoogle Scholar
Brown, H. R., Myrvold, W., & Uffink, J. (2009). Boltzmann’s H-Theorem, Its Discontents, and the Birth of Statistical Mechanics. Studies in History and Philosophy of Modern Physics 40, pp. 174–91.CrossRefGoogle Scholar
Bub, J. (2001). Maxwell’s Demon and the Thermodynamics of Computation. Studies in History and Philosophy of Modern Physics 4, pp. 569–79.Google Scholar
Burgers, J. M. (1970). Entropy and Disorder. British Journal for the Philosophy of Science 5, pp. 70–1.Google Scholar
Callender, C. (1999). Reducing Thermodynamics to Statistical Mechanics: The Case of Entropy. The Journal of Philosophy 96, pp. 348–73.Google Scholar
Church, A. (1940). On the Concept of a Random Sequence. Bulletin of the American Mathematical Society 46, pp. 130–5.CrossRefGoogle Scholar
Coffa, J. A. (1972). Randomness and Knowledge. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1972, pp. 103–15.Google Scholar
Correia, F. & Schnieder, B. (2012, Eds.). Metaphysical Grounding: Understanding the Structure of Reality. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Copeland, B. J. & Proudfoot, D. (2005). Turing and the Computer. In Copeland, B. J. (Ed.), Alan Turing’s Automatic Computing Engine: The Master Codebreaker’s Struggle to Build the Modern Computer. Oxford: Oxford University Press, pp. 107–48.CrossRefGoogle Scholar
DeMol, L. (2021). Turing Machines. In Zalta, E. (Ed.). The Stanford Encyclopedia of Philosophy (Winter 2021 Edition), https://plato.stanford.edu/archives/win2021/entries/turing-machine.Google Scholar
Denbigh, K. G. (1989). Note on Entropy, Disorder and Disorganisation. British Journal for the Philosophy of Science 40, pp. 323–32.CrossRefGoogle Scholar
Eagle, A. (2005). Randomness Is Unpredictability. British Journal for the Philosophy of Science 56, pp. 749–90.CrossRefGoogle Scholar
Earman, J. & Norton, J. D. (1998). Exorcist XIV: The Wrath of Maxwell’s Demon. Part I. From Maxwell to Szilard. Studies in History and Philosophy of Modern Physics 29, pp. 435–71.CrossRefGoogle Scholar
Earman, J. & Norton, J. D. (1999). Exorcist XIV: The Wrath of Maxwell’s Demon. Part II. From Szilard to Landauer and Beyond. Studies in History and Philosophy of Modern Physics 30, pp. 140.CrossRefGoogle Scholar
Ehrenfest, P. & Ehrenfest, T. (1907). Ueber Zwei Bekannte Einwende Gegen das Boltzmannsche H-Theorem. Physikalische Zeitung 8, pp. 311–14.Google Scholar
Ehrenfest, P. & Ehrenfest, T. (1909). Begriffliche Grundlagen der Statistischen Auffassung in der Mechanik. Leipzig: Teubner.Google Scholar
Frenkel, D. (1999). Entropy-Driven Phase Transitions. Physica A 263, pp. 2638.CrossRefGoogle Scholar
Frigg, R., & Werndl, C. (2011). Entropy: A Guide for the Perplexed. In Beisbart, C., & Hartmann, S. (Ed.). Probabilities in Physics. Oxford: Oxford University Press.Google Scholar
Frisch, M. (2006). A Tale of Two Arrows. Studies in the History and Philosophy of Modern Physics 37, pp. 542–58.CrossRefGoogle Scholar
Georgii, H.-O. & Zagrebnov, V. (2011). Entropy-Driven Phase Transitions in Multitype Lattice Gas Models. Journal of Statistical Physics 102, pp. 3567.CrossRefGoogle Scholar
Gibbs, J. W. (1902/1960). Elementary Principles in Statistical Mechanics. New York: Dover.Google Scholar
Gobbo, D., Ballone, P., & Garabato, B. D. (2020). Coarse-Grained Model of Entropy-Driven Demixing. The Journal of Physical Chemistry B 124, pp. 9267–74.CrossRefGoogle ScholarPubMed
Golosz, J. (2017). Weak Interactions: Asymmetry of Time or Asymmetry in Time? Journal for General Philosophy of Science 48, pp. 1933.CrossRefGoogle Scholar
Goodman, N. (1955/1983). Fact, Fiction and Forecast. Cambridge, MA: Harvard University Press.Google Scholar
Haglund, J. (2017). Good Use of a Bad Metaphor: Entropy as Disorder. Science & Education 26, pp. 205–14.Google Scholar
Hempel, C. G. (1945). Studies in the Logic of Confirmation. Mind 54, pp. 126, 97121.CrossRefGoogle Scholar
Hershey, D. (2009). Entropy Theory of Aging Systems: Humans, Corporations and the Universe. London: Imperial College Press.CrossRefGoogle Scholar
Kalman, R. E. (1994). Randomness Reexamined. Modelling, Identification and Control 15, pp. 141–51.CrossRefGoogle Scholar
Kolmogorov, A. N. & Uspenskii, V. A. (1988). Algorithms and Randomness. SIAM Theory and Probability of Applications 32, pp. 389412.CrossRefGoogle Scholar
Landsman, K. (2020). Randomness? What Randomness? Foundations of Physics 50, pp. 61104.CrossRefGoogle Scholar
Laplace, P.-S. (1826/1851). Philosophical Essay on Probabilities. New York: Dover.Google Scholar
Lavis, D. A. (2005). Boltzmann and Gibbs: An Attempted Reconciliation. Studies in History and Philosophy of Modern Physics 36, pp. 245–73.CrossRefGoogle Scholar
Le Poidevin, R., & MacBeath, M. (1993, Eds.). The Philosophy of Time. Oxford: Oxford University Press.Google Scholar
Leff, H. S. (2007). Entropy, Its Language and Interpretation. Foundations of Physics 37, pp. 1744–66.CrossRefGoogle Scholar
Lineweaver, C. H., Davies, P. C. W., & Ruse, M. (2013, Eds.). Complexity and the Arrow of Time. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Loschmidt, J. (1876). Ueber den Zustand des Waermegleichgewichts eines Systemes von Koerpern mit Ruecksicht auf die Schwerkraft. Sitzungs-berichte der Akademie der Wissenschaften zu Wien, Mathematisch-Naturwissenschaftlichle Klasse 73, pp. 128–42.Google Scholar
Margenstern, M. (2000). Frontier between Decidability and Undecidability: A Survey. Theoretical Computer Science 231, pp. 217–51.CrossRefGoogle Scholar
Martin-Loef, P. (1966). The Definition of a Random Sequence. Information and Control 9, pp. 602–19.Google Scholar
Maxwell, J. C. (1867). Letter to Tait, P. G., 11/12/1867. In Knott, C. G. (1911). Life and Scientific Work of Peter Guthrie Tait. Cambridge: Cambridge University Press, p. 214.Google Scholar
McTaggart, J. M. E. (1908). The Unreality of Time. Mind 17, pp. 457–74.Google Scholar
Mellor, D. H. (1998). Real Time II. London: Routledge.CrossRefGoogle Scholar
North, J. (2011). Time in Thermodynamics. In Callender, C. (Ed.). The Oxford Handbook of Time. Oxford: Oxford University Press, pp. 146.Google Scholar
Norton, J. D. (2005). Eater of the Lotus: Landauer’s Principle and the Return of Maxwell’s Demon. Studies in History and Philosophy of Modern Physics 36, pp. 375411.CrossRefGoogle Scholar
Norton, J. D. (2013). All Shook Up: Fluctuations, Maxwell’s Demon and the Thermodynamics of Computation. Entropy 2013, pp. 4432–83.Google Scholar
Poincaré, H. (1890). Sur le Probleme des Trois Corps et les Equations de la Dyanmiqué. Acta Mathematica 13, pp. 1270.Google Scholar
Popper, K. R. (1959/2002). The Logic of Scientific Discovery. London: Routledge.Google Scholar
Price, H. (1997). Time’s Arrow and Archimedes’ Point: New Directions for the Physics of Time. Oxford: Oxford University Press.CrossRefGoogle Scholar
Prior, A. N. (1967). Past, Present, Future. Oxford: Oxford University Press.CrossRefGoogle Scholar
Rickles, D. (2016). The Philosophy of Physics. Cambridge: PolityGoogle Scholar
Roberts, W. B. (2022). Reversing the Arrow of Time. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Robertson, K. (2020). In Search of the Holy Grail: How to Reduce the Second Law of Thermodynamics. Forthcoming in The British Journal for the Philosophy of Science.Google Scholar
Sklar, L. (1993). Physics and Chance: Philosophical Issues in the Foundations of Statistical Mechanics. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Smoluchowski, M. (1912). Experimentell nachweisbare, der ueblichen Thermodynamik wiedersprechende Molekularphenomaene, Physikalische Zeitschrift 13, pp. 1069–80.Google Scholar
Smoluchowski, M. (1914). Gueltigkeitsgrenzen des Zweiten Hauptsatzes der Waermetheorie. In Vortraege ueber die Kinetische Theorie der Materie und der Elektrizitaet. Leibzig: Teuber.Google Scholar
Szilard, L. (1929/1972). On the Decrease of Entropy in a Thermodynamic System by Intervention of Intelligent Beings. In The Collected Works of Leo Szilard: Scientific Papers. Boston: Massachusetts Institute of Technology Press.Google Scholar
Turing, A. M. (1936). On Computable Numbers, with an Application to the Entscheidungsproblem. Proceedings of the London Mathematical Society 42, pp. 230–65.Google Scholar
Uffink, J. (2003). Irreversibility and the Second Law of Thermodynamics. In Greven, A., Keller, G., & Warnecke, G. (Eds.). Entropy. Princeton, NJ: Princeton University Press, pp. 121–46.Google Scholar
Van Rield, R. & van Gulick, R. (2019). Scientific Reduction. In Zalta, E. (Ed.). The Stanford Encyclopedia of Philosophy (Spring 2019 Edition), https://plato.stanford.edu/archives/spr2019/entries/scientific-reduction/.Google Scholar
Von Mises, R. (1957). Probability, Statistics and Truth. New York: Dover.Google Scholar
Wald, R. M. (2006). The Arrow of Time and the Initial Conditions of the Universe. Studies in History and Philosophy of Modern Physics 37, pp. 394–8.CrossRefGoogle Scholar
Weinberg, S. (2008). Cosmology. Oxford: Oxford University Press.CrossRefGoogle Scholar
Werndl, C. (2009a). Are Deterministic Descriptions and Indeterministic Descriptions Observationally Equivalent? Studies in History and Philosophy of Modern Physics 40, pp. 232–42.CrossRefGoogle Scholar
Werndl, C. (2009b). What Are the New Implications of Chaos for Unpredictability? British Journal for the Philosophy of Science 60, pp. 195220.CrossRefGoogle Scholar
Werndl, C. (2011). On the Observational Equivalence of Continuous-Time Deterministic and Indeterministic Descriptions. European Journal for Philosophy of Science 1, pp. 193225.CrossRefGoogle Scholar
Zuchowski, L. C. (2012). Disentangling Complexity from Randomness and Chaos. Entropy 14, pp. 177212.CrossRefGoogle Scholar
Zuchowski, L. C. (2017). A Philosophical Analysis of Chaos Theory. London. Palgrave Macmillan.CrossRefGoogle Scholar

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