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{{Modern physics}}
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'''Quantum statistical mechanics''' is [[statistical mechanics]] applied to [[quantum mechanics|quantum mechanical systems]]. In quantum mechanics a [[statistical ensemble (mathematical physics)|statistical ensemble]] (probability distribution over possible [[quantum state]]s) is described by a [[density matrix|density operator]] ''S'', which is a non-negative, [[self-adjoint]], [[trace-class]] operator of trace 1 on the [[Hilbert space]] ''H'' describing the quantum system. This can be shown under various [[mathematical formulation of quantum mechanics|mathematical formalisms for quantum mechanics]]. One such formalism is provided by [[quantum logic]].


== Expectation ==
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From classical probability theory, we know that the [[expected value|expectation]] of a [[random variable]] ''X'' is completely determined by its [[Probability distribution|distribution]] D<sub>''X''</sub> by
:<math> \mathbb{E}(X) = \int_\mathbb{R} \lambda \, d \, \operatorname{D}_X(\lambda) </math>
assuming, of course, that the random variable is [[integrable]] or that the random variable is non-negative. Similarly, let ''A'' be an [[observable]] of a quantum mechanical system. ''A'' is given by a densely defined self-adjoint operator on ''H''.  The [[spectral measure]] of ''A'' defined by
 
:<math> \operatorname{E}_A(U) = \int_U \lambda d \operatorname{E}(\lambda), </math>
 
uniquely determines ''A'' and conversely, is uniquely determined by ''A''. E<sub>''A''</sub>  is a boolean homomorphism from the Borel subsets of '''R''' into the lattice ''Q'' of self-adjoint projections of ''H''. In analogy with probability theory, given a state ''S'', we introduce the ''distribution'' of ''A''  under ''S'' which is the probability measure defined on the Borel subsets of '''R''' by
:<math> \operatorname{D}_A(U) = \operatorname{Tr}(\operatorname{E}_A(U) S). </math>
Similarly, the expected value of ''A'' is defined in terms of the probability distribution D<sub>''A''</sub> by
:<math> \mathbb{E}(A) = \int_\mathbb{R} \lambda \, d \, \operatorname{D}_A(\lambda).</math>
Note that this expectation is relative to the  mixed state ''S'' which is used in the definition of D<sub>''A''</sub>.
 
'''Remark'''.  For technical reasons, one needs to consider separately the positive and negative parts of ''A'' defined by the [[Borel functional calculus]] for unbounded operators.
 
One can easily show:
:<math> \mathbb{E}(A)  = \operatorname{Tr}(A S) = \operatorname{Tr}(S A). </math>
 
Note that if ''S'' is a [[pure state]] corresponding to the vector &psi;, then:
:<math> \mathbb{E}(A) = \langle \psi | A | \psi \rangle. </math>
 
== Von Neumann entropy ==<!-- This section is linked from [[Physical information]] -->
 
{{main|Von Neumann entropy}}
 
Of particular significance for describing randomness of a state is the von Neumann entropy of ''S'' ''formally'' defined by
:<math> \operatorname{H}(S) = -\operatorname{Tr}(S \log_2 S) </math>. 
Actually, the operator  ''S'' log<sub>2</sub> ''S'' is not necessarily trace-class. However, if ''S'' is a non-negative self-adjoint operator not of trace class we define Tr(''S'') = +&infin;.  Also note that any density operator ''S'' can be diagonalized, that it can be represented in some orthonormal basis by a (possibly infinite) matrix of the form
:<math> \begin{bmatrix} \lambda_1 & 0 & \cdots & 0 & \cdots \\ 0 & \lambda_2 & \cdots & 0 & \cdots\\ & & \cdots &  \\ 0 & 0 & \cdots &  \lambda_n & \cdots \\ & & \cdots & \cdots \end{bmatrix} </math>
and we define
:<math> \operatorname{H}(S) = - \sum_i \lambda_i \log_2 \lambda_i. </math>
The convention is that <math> \; 0 \log_2 0 = 0</math>, since an event with probability zero should not contribute to the entropy. This value is an extended real number (that is in [0, &infin;]) and this is clearly a unitary invariant of ''S''. 
 
'''Remark'''. It is indeed possible that H(''S'') = +&infin; for some density operator ''S''. In fact ''T'' be the diagonal matrix
:<math> T = \begin{bmatrix} \frac{1}{2 (\log_2  2)^2 }& 0 & \cdots & 0 & \cdots \\ 0 & \frac{1}{3 (\log_2  3)^2 } & \cdots & 0 & \cdots\\ & & \cdots &  \\ 0 & 0 & \cdots &  \frac{1}{n (\log_2  n)^2 } & \cdots \\ & & \cdots & \cdots \end{bmatrix} </math>
''T'' is non-negative trace class and one can show ''T'' log<sub>2</sub> ''T'' is not trace-class.
 
'''Theorem'''.  Entropy is a unitary invariant.
 
In analogy with [[Shannon entropy#Formal definitions|classical entropy]] (notice the similarity in the definitions), H(''S'') measures the amount of randomness in the state ''S''. The more dispersed the eigenvalues are, the larger the system entropy. For a system in which the space ''H'' is finite-dimensional, entropy is maximized for the states ''S'' which in diagonal form have the representation
:<math> \begin{bmatrix} \frac{1}{n} & 0 & \cdots & 0 \\ 0 & \frac{1}{n} & \dots & 0 \\ & & \cdots & \\ 0 & 0 & \cdots &  \frac{1}{n} \end{bmatrix} </math>
For such an ''S'', H(''S'') = log<sub>2</sub> ''n''. The state ''S'' is called the maximally mixed state.
 
Recall that a [[pure state]] is one of the form
:<math> S = | \psi \rangle \langle \psi |, </math>
for &psi; a vector of norm 1.
 
'''Theorem'''.  H(''S'') = 0 if and only if ''S'' is a pure state.
 
For ''S'' is a pure state if and only if its diagonal form has exactly one non-zero entry which is a 1.
 
Entropy can be used as a measure of [[quantum entanglement]].
 
== Gibbs canonical ensemble ==
 
{{main|canonical ensemble}}
 
Consider an ensemble of systems described by a Hamiltonian ''H'' with average energy ''E''.  If ''H'' has pure-point spectrum and the eigenvalues <math>E_n</math> of ''H'' go to +&infin; sufficiently fast, e<sup>-''r H''</sup> will be a non-negative trace-class operator for every positive ''r''.
 
The ''[[Gibbs canonical ensemble]]'' is described by the state
:<math> S= \frac{e^{- \beta H}}{\operatorname{Tr}(e^{- \beta H})}. </math>
Where &beta; is such that the ensemble average of energy satisfies 
:<math> \operatorname{Tr}(S H) = E </math>
 
and
 
:<math>\operatorname{Tr}(e^{- \beta H}) = \sum_n e^{- \beta E_n} = Z(\beta) </math>
 
This is called the [[partition function (mathematics)|partition function]]; it is the quantum mechanical version of the [[canonical partition function]] of classical statistical mechanics. The probability that a system chosen at random from the ensemble will be in a state corresponding to energy eigenvalue <math>E_m</math> is
 
:<math>\frac{e^{- \beta E_m}}{\sum_n e^{- \beta E_n}}.</math>
 
Under certain conditions, the Gibbs canonical ensemble maximizes the von Neumann entropy of the state subject to the energy conservation requirement.{{clarify|reason = How so? This ensemble spans over many energies, so what does 'energy conservation' refer to?|date=September 2013}}
 
== Grand canonical ensemble ==
 
{{main|grand canonical ensemble}}
 
For open systems where the energy and numbers of particles may fluctuate, the system is described by the [[grand canonical ensemble]], described by the density matrix
:<math> \rho= \frac{e^{- \beta (H + \mu_1 N_1 + \mu_2 N_2 + \cdots)}}{\operatorname{Tr}(e^{- \beta (H + \mu_1 N_1 + \mu_2 N_2 + \cdots)})}. </math>
where the ''N''<sub>1</sub>, ''N''<sub>2</sub>, ... are the particle number operators for the different species of particles that are exchanged with the reservoir. Note that this is a density matrix including many more states (of varying N) compared to the canonical ensemble.
 
The grand partition function is
:<math>\mathcal Z(\beta, \mu_1, \mu_2, \cdots) = \operatorname{Tr}(e^{- \beta (H + \mu_1 N_1 + \mu_2 N_2 + \cdots)}) </math>
 
== References ==
 
* J. von Neumann, ''Mathematical Foundations of Quantum Mechanics'', Princeton University Press, 1955.
 
* F. Reif, ''Statistical and Thermal Physics'', McGraw-Hill,  1965.
 
[[Category:Quantum mechanics]]
[[Category:Statistical mechanics]]
[[Category:Quantum mechanical entropy]]

Latest revision as of 05:39, 1 November 2014

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