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arXiv:1004.0951 · Physical Review A

Pseudounitary freedom in the operator-sum representation

Yong-Cheng Ou, Mark Byrd

Published Aug 23, 2010• 6 citations
arXivHTMLPDF

Abstract

A dynamical map is a map that takes one density operator to another. Such a map can be written in an operator-sum representation (OSR) by using a spectral decomposition. The method of construction applies to general maps, which need not be completely positive. The OSR is not unique; there is freedom to choose a different set of operators in the OSR, yet still obtain the same map. Here, we show that, whereas the freedom for completely positive maps is unitary, the freedom for maps that are not necessarily completely positive is pseudounitary.

DOI
10.1103/physreva.82.022325

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A dynamical map is a map that takes one density operator to another. Such a map can be written in an operator-sum representation (OSR) by using a spectral decomposition. The method of construction applies to general maps, which need not be completely positive. The OSR is not unique; there is freedom to choose a different set of operators in the OSR, yet still obtain the same map. Here, we show that, whereas the freedom for completely positive maps is unitary, the freedom for maps that are not necessarily completely positive is pseudounitary.
Linear maps of matrices describing the evolution of density matrices for a quantum system initially entangled with another are identified and found to be not always completely positive. They can even map a positive matrix to a matrix that is not positive, unless we restrict the domain on which the map acts. Nevertheless, their form is similar to that of completely positive maps. Only some minus signs are inserted in the operator-sum representation. Each map is the difference of two completely positive maps. The maps are first obtained as maps of mean values and then as maps of basis matrices. These forms also prove to be useful. An example for two entangled qubits is worked out in detail. The relation to earlier work is discussed.
Quantum systems which interact with an unknown environment cannot be described in terms of a unitary evolution on the system alone. For such evolution one can use a map from one density operator to another and use any other known information to model the system. Such maps are required to be positive (at least on their domain) — they take positive density operators to positive density operators — so as to be physically reasonable. A map [Formula: see text] which is positive but not completely positive (CP) is one which takes positive operators to positive operators, but when extended by the identity [Formula: see text], i.e. [Formula: see text] does not give a positive map for some [Formula: see text]. The map is CP if and only if the extension is positive for all [Formula: see text]. Recently some effort has been put forth to try to understand if, and/or, under what circumstances one might utilize a non-CP map. Here, after a tutorial-type introduction to maps from one density operator to another, some examples which do not fit the standard prescription (SP) for deriving a CP map are given. In cases where the physical system is constrained by some knowledge of the interaction, it is possible that the SP cannot be used directly. Our example is robust to changes in the initial and final conditions.
The concept of the half density matrix is proposed. It unifies the quantum states that are described by density matrices and physical processes that are described by completely positive maps. With the help of the half-density-matrix representation of the Hermitian linear map, we show that every positive map that is not completely positive is a difference of two completely positive maps. A necessary and sufficient condition for a positive map that is not completely positive is also presented, which is illustrated by some examples.
The most general evolution of the density matrix of a quantum system with a finite-dimensional state space is by stochastic maps which take a density matrix linearly into the set of density matrices. These dynamical stochastic maps form a linear convex set that may be viewed as supermatrices. The property of Hermiticity of density matrices renders an associated supermatrix Hermitian and hence diagonalizable. The positivity of the density matrix does not make the associated supermatrix positive though. If the map itself is positive, it is called completely positive and it has a simple parametrization. This is extended to all positive (not completely positive) maps. A general dynamical map that does not preserve the norm of the density matrices it acts on can be thought of as the contraction of a norm-preserving map of an extended system. The reconstruction of such extended dynamics is also given.
In the simplest approximation, the reduced dynamics of a quantum system SSS interacting with its environment EEE is considered to be given by a completely positive map. But, in general, this is not the case. In fact, the reduced dynamics of the system in not even linear, in general. Whether the reduced dynamics is linear or not is determined by two factors: the set of possible initial states of the system-environment $\mathcal{S}=\left\lbrace ρ_{SE} \right\rbrace $, and the joint system-environment unitary evolution UUU. When UUU is factorisable as U=US⊗UEU=U_S\otimes U_EU=US​⊗UE​, then we can choose S=D\mathcal{S}=\mathcal{D}S=D, where D\mathcal{D}D is the set of all system-environment density operators. In other words, when UUU is factorisable, the reduced dynamics of the system SSS is linear (in fact unitary) for arbitrary initial state of the system-environment ρSEρ_{SE}ρSE​. We show that this result cannot be generalized to any non-factorisable UUU: For any non-factorisable unitary evolution of the whole system-environment UUU, the set S\mathcal{S}S must be chosen as a proper subset of D\mathcal{D}D to achieve linear reduced dynamics. As a byproduct, considering a convex set of possible initial states of the system-environment S\mathcal{S}S such that TrE S=TrE D\mathrm{Tr}_{E} \ \mathcal{S}=\mathrm{Tr}_{E} \ \mathcal{D}TrE​ S=TrE​ D, we show that when the reduced dynamics of the system, for one system-environment unitary evolution U1U_1U1​, is positive, but not completely positive, this implies that reduced dynamics is not linear for another U2U_2U2​.
The positive and not completely positive maps of density matrices, which are contractive maps, are discussed as elements of a semigroup. A new kind of positive map (the purification map), which is nonlinear map, is introduced. The density matrices are considered as vectors, linear maps among matrices are represented by superoperators given in the form of higher dimensional matrices. Probability representation of spin states (spin tomography) is reviewed and U ( N )-tomogram of spin states is presented. Properties of the tomograms as probability distribution functions are studied. Notion of tomographic purity of spin states is introduced. Entanglement and separability of density matrices are expressed in terms of properties of the tomographic joint probability distributions of random spin projections which depend also on unitary group parameters. A new positivity criterion for hermitian matrices is formulated. An entanglement criterion is given in terms of a function depending on unitary group paramete rs and semigroup of positive map parameters. The function is constructed as sum of moduli of U ( N )- tomographic symbols of the hermitian matrix obtained after action on the density matrix of composite system by a positive but not completely positive map of the subsystem density matrix. Some two-qubit and two-qutritt states are considered as examples of entangled states. The connection with the star-product quantisation is discussed. The structure of the set of density matrices and their relation to unitary group and Lie algebra of the unitary group are studied. Nonlinear quantum evolution of state vector obtained by means of applying purification rule of density matrices evolving via dynamical maps is considered. Some connection of positive maps and entanglement with random matrices is discussed and used.