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CRC Press eBooks

Quasi-Classical Approximation in Quantum Statistical Mechanics

Lukong Cornelius Fai

Published Feb 19, 2021• 0 citations
Publisher

Abstract

We begin by first showing how, with the Feynman functional integration in the representation of the matrix density, we can make a transition to classical distribution. The Feynman density matrix as seen earlier has the form in 16.77: 16.1 ρ q q ′ = ∫ q ′ q exp S ¯ q , q ′ , − i ℏ β D q τ https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003145554/875ff22b-09e9-4373-a808-2051f13516c8/content/eqn16_1.jpg"/> where 16.2 S ¯ = S ¯ q τ , − i ℏ β ≡ ∫ 0 β − m 2 ℏ 2 q . 2 − U q d τ https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003145554/875ff22b-09e9-4373-a808-2051f13516c8/content/eqn16_2.jpg"/>

DOI
10.1201/9781003145554-16

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CRC Press eBooks•Feb 19, 2021•0 citations
We begin by first showing how, with the Feynman functional integration in the representation of the matrix density, we can make a transition to classical distribution. The Feynman density matrix as seen earlier has the form in 16.77: 16.1 ρ q q ′ = ∫ q ′ q exp S ¯ q , q ′ , − i ℏ β D q τ https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003145554/875ff22b-09e9-4373-a808-2051f13516c8/content/eqn16_1.jpg"/> where 16.2 S ¯ = S ¯ q τ , − i ℏ β ≡ ∫ 0 β − m 2 ℏ 2 q . 2 − U q d τ https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003145554/875ff22b-09e9-4373-a808-2051f13516c8/content/eqn16_2.jpg"/>
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In quantum statistical mechanics one has the fundamental object ρ(β; x a ,x b ), a matrix entry which defines the density matrix ρl, given in the Feynman formulation by the Euclidean path integral of the preceding chapter: $$\begin{array}{*{20}{c}} {\rho {{{(\beta ;{{x}_{a}},{{x}_{b}})}}^{{\underline{\underline {def}} }}}\int_{{{{x}_{a}} = x(0)}}^{{{{x}_{b}} = x(\beta \hbar )}} {\exp ( - {{S}_{E}}(x(t))/\hbar )D[x(t)]} } \\ { = {{I}_{E}}(0,\beta \hbar ,{{x}_{a}},{{x}_{b}})} \\ \end{array}$$ (14.1.1) where β=1kT\beta = \tfrac{1}{{kT}}β=kT1​ is the inverse temperature 1T\tfrac{1}{T}T1​ up to a constant 1k\tfrac{1}{k}k1​, k being Boltzmann’s constant. From ρ one obtains the all-important partition function Ζ as a trace: $$\begin{array}{*{20}{c}} {Z = \int_{{ - \infty }}^{\infty } {\rho (\beta ;x,x)dx} } \hfill \\ { = \int_{{ - \infty }}^{\infty } {\int_{{x(0) = x}}^{{x(\beta \hbar ) = x}} {\exp ( - {{S}_{E}}(x(t))/\hbar )D[x(t)]dx.} } } \hfill \\ \end{array}$$ (14.1.2)
The transition amplitudes 4.47 and 4.82 of chapter 4 may be generalized for a problem with s degrees of freedom that may be described by a set of operators q ̂ = q ̂ α α = 1 s , p ̂ = p ̂ α α = 1 s https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003145554/875ff22b-09e9-4373-a808-2051f13516c8/content/eqni6_1.jpg"/> : 6.1 Κ q ″ , t ″ ; q ′ , t ′ = ∫ ∏ α = 1 s D p α D q α exp i ℏ ∫ t ′ t ″ ∑ α = 1 s p α q . α − Η p q d t https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003145554/875ff22b-09e9-4373-a808-2051f13516c8/content/eqn6_1.jpg"/>
Abstract For present purposes, the first thing to recall about quantum mechanics is that all dynamical quantities, instead of being functions of the location of a system in phase space as in classical mechanics, are now represented by operators in a Hilbert space of quantum states. In particular, the quantum analog of the classical phase space distribution function is the quantum mechanical density matrix. Since this is seldom discussed in introductory texts on either quantum mechanics or statistical mechanics, it may be helpful to summarize some of its basic properties.
It is instructive to note that the principal advantage of linear operators is that their action on any vector is defined purely by their action on a set of basis vectors. Let us consider the linear operator F ̂ https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003145554/875ff22b-09e9-4373-a808-2051f13516c8/content/eqni2_1.jpg"/> transforming the vector a via its components a k : 2.1 F ̂ a i = ∑ k F i k a k https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003145554/875ff22b-09e9-4373-a808-2051f13516c8/content/eqn2_1.jpg"/>