Approximating quantum channels by completely positive maps with small Kraus rank

Fuente: arXiv
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Hauptverfasser: Lancien, Cécilia, Winter, Andreas
Format: Preprint
Veröffentlicht: 2017
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author Lancien, Cécilia
Winter, Andreas
author_facet Lancien, Cécilia
Winter, Andreas
contents We study the problem of approximating a quantum channel by one with as few Kraus operators as possible (in the sense that, for any input state, the output states of the two channels should be close to one another). Our main result is that any quantum channel mapping states on some input Hilbert space $\mathrm{A}$ to states on some output Hilbert space $\mathrm{B}$ can be compressed into one with order $d\log d$ Kraus operators, where $d=\max(|\mathrm{A}|,|\mathrm{B}|)$, hence much less than $|\mathrm{A}||\mathrm{B}|$. In the case where the channel's outputs are all very mixed, this can be improved to order $d$. We discuss the optimality of this result as well as some consequences.
format Preprint
id arxiv_https___arxiv_org_abs_1711_00697
institution arXiv
publishDate 2017
record_format arxiv
spellingShingle Approximating quantum channels by completely positive maps with small Kraus rank
Lancien, Cécilia
Winter, Andreas
Quantum Physics
Functional Analysis
Probability
We study the problem of approximating a quantum channel by one with as few Kraus operators as possible (in the sense that, for any input state, the output states of the two channels should be close to one another). Our main result is that any quantum channel mapping states on some input Hilbert space $\mathrm{A}$ to states on some output Hilbert space $\mathrm{B}$ can be compressed into one with order $d\log d$ Kraus operators, where $d=\max(|\mathrm{A}|,|\mathrm{B}|)$, hence much less than $|\mathrm{A}||\mathrm{B}|$. In the case where the channel's outputs are all very mixed, this can be improved to order $d$. We discuss the optimality of this result as well as some consequences.
title Approximating quantum channels by completely positive maps with small Kraus rank
topic Quantum Physics
Functional Analysis
Probability
url https://arxiv.org/abs/1711.00697