2011
DOI: 10.1142/s0129183111016683
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Singular Value Decomposition and Matrix Reorderings in Quantum Information Theory

Abstract: We review Schmidt and Kraus decompositions in the form of singular value decomposition using operations of reshaping, vectorization and reshuffling. We use the introduced notation to analyse the correspondence between quantum states and operations with the help of Jamio lkowski isomorphism. The presented matrix reorderings allow us to obtain simple formulae for the composition of quantum channels and partial operations used in quantum information theory. To provide examples of the discussed operations we utili… Show more

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Cited by 47 publications
(53 citation statements)
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“…and it can be calculated efficiently with Schmidt decomposition [70]. In the ergodic phase the entanglement entropy of a typical Hamiltonian eigenstate grows with the size of the subsystem A -a volume law scaling.…”
Section: A Bipartite Entanglement and Number Uncertaintymentioning
confidence: 99%
“…and it can be calculated efficiently with Schmidt decomposition [70]. In the ergodic phase the entanglement entropy of a typical Hamiltonian eigenstate grows with the size of the subsystem A -a volume law scaling.…”
Section: A Bipartite Entanglement and Number Uncertaintymentioning
confidence: 99%
“…Then, the Choi-Jamiołkowski state  is obtained from equation (25). Also, we can use reshaping operation [52,53], which is defined as, given an m × m matrix = A a [ ] ij with elements a ij ,…”
Section: Appendix B Simulation Example For Qutrit Channelsmentioning
confidence: 99%
“…2 the second-order expansion found using Eqs. (45) and (46) about an assortment of time points to show that our equations capture the negativity dynamics even in regions where negativity is constant, in intervals when ρ T B is positive semi-definite, and in the presence of bound entanglement. One may also use our method to analyze how negativity changes with respect to the system parameters ∆ and g in order to explore how entanglement in the JCM is sensitive to the entire parameter landscape.…”
Section: Negativity Growth In Various Systemsmentioning
confidence: 99%
“…A we show how (17) can be obtained through the action of the partial transposition map on the standard basis, and we also present a convenient form for K B by identifying its eigenvectors. For other representations of the transposition and partial transposition maps, see, for example, [46]. With this brief introduction to aspects of algebra on vectorized matrices, we now turn to calculus in order to identify ∂ ρ T B 1 /∂ vec T ρ T B , the remaining factor in (7).…”
Section: Perturbative Expansion Of Negativitymentioning
confidence: 99%