What is a macrostate? Subjective observations and objective dynamics

Abstract

We consider the question of whether thermodynamic macrostates are objective consequences of dynamics, or subjective reflections of our ignorance of a physical system. We argue that they are both; more specifically, that the set of macrostates forms the unique maximal partition of phase space which 1) is consistent with our observations (a subjective fact about our ability to observe the system) and 2) obeys a Markov process (an objective fact about the system's dynamics). We review the ideas of computational mechanics, an information-theoretic method for finding optimal causal models of stochastic processes, and argue that macrostates coincide with the ``causal states'' of computational mechanics. Defining a set of macrostates thus consists of an inductive process where we start with a given set of observables, and then refine our partition of phase space until we reach a set of states which predict their own future, i.e. which are Markovian. Macrostates arrived at in this way are provably optimal statistical predictors of the future values of our observables.

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2009-01-28

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Author's Profile

C. J. Moore
Mississippi State University

Citations of this work

What is a complex system?James Ladyman, James Lambert & Karoline Wiesner - 2013 - European Journal for Philosophy of Science 3 (1):33-67.
Subjective probability and quantum certainty.Carlton M. Caves, Christopher A. Fuchs & Rüdiger Schack - 2007 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 38 (2):255-274.
Simulation and the sense of understanding.Jaakko Kuorikoski - 2011 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. London: Routledge. pp. 168-187.

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References found in this work

Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - New York: Cambridge University Press.
Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.
Statistical explanation & statistical relevance.Wesley C. Salmon - 1971 - [Pittsburgh]: University of Pittsburgh Press. Edited by Richard C. Jeffrey & James G. Greeno.

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