8,821 research outputs found
Strong skew commutativity preserving maps on von Neumann algebras
Let be a von Neumann algebra without central summands of type
. Assume that is a surjective
map. It is shown that is strong skew commutativity preserving (that is,
satisfies for all ) if and only if there exists some self-adjoint element in the center of
with such that for all .
The strong skew commutativity preserving maps on prime involution rings and
prime involution algebras are also characterized.Comment: 16 page
Detecting entanglement of states by entries of their density matrices
For any bipartite systems, a universal entanglement witness of rank-4 for
pure states is obtained and a class of finite rank entanglement witnesses is
constructed. In addition, a method of detecting entanglement of a state only by
entries of its density matrix with respect to some product basis is obtained.Comment: 14 page
Energy Functionals for the Parabolic Monge-Ampere Equation
We introduce certain energy functionals to the complex Monge-Ampere equation
over a bounded domain with inhomogeneous boundary condition, and use these
functionals to show the convergence of the solution to the parabolic
Monge-Ampere equation.Comment: 12 page
A characterization of optimal entanglement witnesses
In this paper, we present a characterization of optimal entanglement
witnesses in terms of positive maps and then provide a general method of
checking optimality of entanglement witnesses. Applying it, we obtain new
indecomposable optimal witnesses which have no spanning property. These also
provide new examples which support a recent conjecture saying that the
so-called structural physical approximations to optimal positive maps (optimal
entanglement witnesses) give entanglement breaking maps (separable states).Comment: 1
Fidelity of states in infinite dimensional quantum systems
In this paper we discuss the fidelity of states in infinite dimensional
systems, give an elementary proof of the infinite dimensional version of
Uhlmann's theorem, and then, apply it to generalize several properties of the
fidelity from finite dimensional case to infinite dimensional case. Some of
them are somewhat different from those for finite dimensional case.Comment: 12 page
Positive finite rank elementary operators and characterizing entanglement of states
In this paper, a class of indecomposable positive finite rank elementary
operators of order are constructed. This allows us to give a simple
necessary and sufficient criterion for separability of pure states in bipartite
systems of any dimension in terms of positive elementary operators of order
and get some new mixed entangled states that can not be detected by the
positive partial transpose (PPT) criterion and the realignment criterion.Comment: 26 page
Linear maps preserving separability of pure states
Linear maps preserving pure states of a quantum system of any dimension are
characterized. This is then used to establish a structure theorem for linear
maps that preserve separable pure states in multipartite systems. As an
application, a characterization of separable pure state preserving affine maps
is obtained.Comment: 16 page
Optimality of a class of entanglement witnesses for systems
Let be a linear
map defined by
,
where and is a permutation of . We show that the
Hermitian matrix induced by is an optimal
entanglement witness if and only if and is cyclic.Comment: 12 page
Convex Optimization Learning of Faithful Euclidean Distance Representations in Nonlinear Dimensionality Reduction
Classical multidimensional scaling only works well when the noisy distances
observed in a high dimensional space can be faithfully represented by Euclidean
distances in a low dimensional space. Advanced models such as Maximum Variance
Unfolding (MVU) and Minimum Volume Embedding (MVE) use Semi-Definite
Programming (SDP) to reconstruct such faithful representations. While those SDP
models are capable of producing high quality configuration numerically, they
suffer two major drawbacks. One is that there exist no theoretically guaranteed
bounds on the quality of the configuration. The other is that they are slow in
computation when the data points are beyond moderate size. In this paper, we
propose a convex optimization model of Euclidean distance matrices. We
establish a non-asymptotic error bound for the random graph model with
sub-Gaussian noise, and prove that our model produces a matrix estimator of
high accuracy when the order of the uniform sample size is roughly the degree
of freedom of a low-rank matrix up to a logarithmic factor. Our results
partially explain why MVU and MVE often work well. Moreover, we develop a fast
inexact accelerated proximal gradient method. Numerical experiments show that
the model can produce configurations of high quality on large data points that
the SDP approach would struggle to cope with.Comment: 44 pages, 10 figures, 1 tabl
-Deformed Chern Characters for Quantum Groups
In this paper, we introduce an matrix in
the quantum groups to transform the conjugate representation into
the standard form so that we are able to compute the explicit forms of the
important quantities in the bicovariant differential calculus on ,
such as the -deformed structure constant and the
-deformed transposition operator . From the -gauge covariant
condition we define the generalized -deformed Killing form and the -th
-deformed Chern class for the quantum groups . Some
useful relations of the generalized -deformed Killing form are presented. In
terms of the -deformed homotopy operator we are able to compute the
-deformed Chern-Simons by the condition ,
Furthermore, the -deformed cocycle hierarchy, the -deformed gauge
covariant Lagrangian, and the -deformed Yang-Mills equation are derived
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