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A Look Back: Early Applications of Maximum Entropy Estimation to Quantum Statistical Mechanics

Published online by Cambridge University Press:  21 October 2009

D.J. Scalapino
Affiliation:
Department of Physics, University of California Santa Barbara, California 93106–9530
W. T. Grandy, Jr
Affiliation:
University of Wyoming
P. W. Milonni
Affiliation:
Los Alamos National Laboratory
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Summary

ABSTRACT. E.T. Jaynes has been the central figure for over three decades in showing how maximum entropy estimation (MEE) provides an extension of logic to cases where one cannot carry out Aristotelian deductive reasoning. Here I will review two early applications of MEE which I hope will provide some insight into how these ideas were being used in quantum and statistical mechanics around 1960.

In May of ‘61 I turned in my Ph.D. thesis (Scalapino, 1961) to Stanford University and, following a well-known dictum, went on to work on other problems. Now, three decades later, on this, the occasion of Ed Jaynes’ seventieth birthday, I decided to look back to see what we were doing when I was first getting to know Ed and his special approach to problems.

Not surprisingly, my thesis contains several applications of the principle of Maximum Entropy Estimation (MEE). In 1957 Ed had written two seminal articles (Jaynes, 1957(a), 1957(b)) showing how one could use Shannon's (1948) Information Theory to construct density matrices for a variety of different problems in equilibrium statistical mechanics. I had been very much taken with this work and wanted to understand how it could be applied to other systems.

Type
Chapter
Information
Physics and Probability
Essays in Honor of Edwin T. Jaynes
, pp. 9 - 14
Publisher: Cambridge University Press
Print publication year: 1993

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