Quantum statistical mechanics, quantum probability and quantum characteristic function

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Abstract

The theory of quantum statistical mechanics is reviewed in the light of the quantum probability theory developed in recent years by mathematicians. We show that-which is our main motivation here-the former is a special model in the framework of the latter, by extending the characteristic function in the classical probability theory to the quantum probability theory based on the requirements of quantum statistical mechanics. We find that due to the fact that fundamental dynamical variables of a quantum system must respect certain commutation relations, one has to reform the classical characteristic function defined on a Euclidean space to a normalized, nonnegative definite function defined on a group which is generated by a Lie algebra formed from these commutation relations. Our key finding is that the group-theoretical characteristic function could be adopted to replace the density matrix commonly used in quantum statistical mechanics for representing a state of the quantum ensemble, and more than that, the new representation has some significant advantages in applications. To show its advantages compared with the conventional density matrix scenario, we illustrate its applications in: solving the master equation that describes the irreversible evolution of a quantum open system; determining the pointer states of a quantum open system; and expanding the density matrix with the pointer states. In particular, thanks to the quantum characteristic function, we are able to write down the solutions of the quantum-optical master equation explicitly, obtain its steady solutions and verify that the pointer states are exactly coherent states. Besides, the Caldeira-Leggett master equation for the quantum Brownian motion and its extension to the Lindblad type are also studied.

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APA

Gu, Y. (2020). Quantum statistical mechanics, quantum probability and quantum characteristic function. Scientia Sinica: Physica, Mechanica et Astronomica, 50(7). https://doi.org/10.1360/SSPMA-2019-0365

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