27,978 research outputs found
Group theoretical study of LOCC-detection of maximally entangled state using hypothesis testing
In the asymptotic setting, the optimal test for hypotheses testing of the
maximally entangled state is derived under several locality conditions for
measurements. The optimal test is obtained in several cases with the asymptotic
framework as well as the finite-sample framework. In addition, the experimental
scheme for the optimal test is presented
Unitary-process discrimination with error margin
We investigate a discrimination scheme between unitary processes. By
introducing a margin for the probability of erroneous guess, this scheme
interpolates the two standard discrimination schemes: minimum-error and
unambiguous discrimination. We present solutions for two cases. One is the case
of two unitary processes with general prior probabilities. The other is the
case with a group symmetry: the processes comprise a projective representation
of a finite group. In the latter case, we found that unambiguous discrimination
is a kind of "all or nothing": the maximum success probability is either 0 or
1. We also closely analyze how entanglement with an auxiliary system improves
discrimination performance.Comment: 9 pages, 3 figures, presentation improved, typos corrected, final
versio
Optimal estimation of a physical observable's expectation value for pure states
We study the optimal way to estimate the quantum expectation value of a
physical observable when a finite number of copies of a quantum pure state are
presented. The optimal estimation is determined by minimizing the squared error
averaged over all pure states distributed in a unitary invariant way. We find
that the optimal estimation is "biased", though the optimal measurement is
given by successive projective measurements of the observable. The optimal
estimate is not the sample average of observed data, but the arithmetic average
of observed and "default nonobserved" data, with the latter consisting of all
eigenvalues of the observable.Comment: v2: 5pages, typos corrected, journal versio
Comparison between the Cramer-Rao and the mini-max approaches in quantum channel estimation
In a unified viewpoint in quantum channel estimation, we compare the
Cramer-Rao and the mini-max approaches, which gives the Bayesian bound in the
group covariant model. For this purpose, we introduce the local asymptotic
mini-max bound, whose maximum is shown to be equal to the asymptotic limit of
the mini-max bound. It is shown that the local asymptotic mini-max bound is
strictly larger than the Cramer-Rao bound in the phase estimation case while
the both bounds coincide when the minimum mean square error decreases with the
order O(1/n). We also derive a sufficient condition for that the minimum mean
square error decreases with the order O(1/n).Comment: In this revision, some unlcear parts are clarifie
Two quantum analogues of Fisher information from a large deviation viewpoint of quantum estimation
We discuss two quantum analogues of Fisher information, symmetric logarithmic
derivative (SLD) Fisher information and Kubo-Mori-Bogoljubov (KMB) Fisher
information from a large deviation viewpoint of quantum estimation and prove
that the former gives the true bound and the latter gives the bound of
consistent superefficient estimators. In another comparison, it is shown that
the difference between them is characterized by the change of the order of
limits.Comment: LaTeX with iopart.cls, iopart12.clo, iopams.st
Quantum hypothesis testing with group symmetry
The asymptotic discrimination problem of two quantum states is studied in the
setting where measurements are required to be invariant under some symmetry
group of the system. We consider various asymptotic error exponents in
connection with the problems of the Chernoff bound, the Hoeffding bound and
Stein's lemma, and derive bounds on these quantities in terms of their
corresponding statistical distance measures. A special emphasis is put on the
comparison of the performances of group-invariant and unrestricted
measurements.Comment: 33 page
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