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arXiv:quant-ph/0101123

Relaxation Method For Calculating Quantum Entanglement

Robert R. Tucci

Published Jan 24, 2001• 11 citations
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Abstract

In a previous paper, we showed how entanglement of formation can be defined as a minimum of the quantum conditional mutual information (a.k.a. quantum conditional information transmission). In classical information theory, the Arimoto-Blahut method is one of the preferred methods for calculating extrema of mutual information. In this paper, we present a new method, akin to the Arimoto-Blahut method, for calculating entanglement of formation. We also present several examples computed with a computer program called Causa Comun that implements the ideas of this paper.

DOI
10.48550/arxiv.quant-ph/0101123

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In a previous paper, we showed how entanglement of formation can be defined as a minimum of the quantum conditional mutual information (a.k.a. quantum conditional information transmission). In classical information theory, the Arimoto-Blahut method is one of the preferred methods for calculating extrema of mutual information. In this paper, we present a new method, akin to the Arimoto-Blahut method, for calculating entanglement of formation. We also present several examples computed with a computer program called Causa Comun that implements the ideas of this paper.
We show that the separability of states in quantum mechanics has a close counterpart in classical physics, and that conditional mutual information (a.k.a. conditional information transmission) is a very useful quantity in the study of both quantum and classical separabilities. We also show how to define entanglement of formation in terms of conditional mutual information. This paper lays the theoretical foundations for a sequel paper which will present a computer program that can calculate a decomposition of any separable quantum or classical state.
We propose a new measure of quantum entanglement. Our measure is defined in terms of conditional information transmission for a Quantum Bayesian Net. We show that our measure is identically equal to the Entanglement of Formation in the case of a bipartite (two listener) system occupying a pure state. In the case of mixed states, the relationship between these two measures is not known yet. We discuss some properties of our measure. Our measure can be easily and naturally generalized to handle n-partite (n-listener) systems. It is non-negative for any n. It vanishes for conditionally separable states with n listeners. It is symmetric under permutations of the n listeners. It decreases if listeners are merged, pruned or removed. Most promising of all, it is intimately connected with the Data Processing Inequalities. We also find a new upper bound for classical mutual information which is of interest in its own right.
We develop a fast algorithm to calculate the entanglement of formation of a mixed state, which is defined as the minimum average entanglement of the pure states that form the mixed state. The algorithm combines conjugat-gradient and steepest-descent algorithms and outperforms both. Using this new algorithm, we obtain the statistics of the entanglement of formation on ensembles of random density matrices of higher dimensions than possible before. The correlation between the entanglement of formation and other quantities that are easier to compute, such as participation ratio and negativity are presented. Our results suggest a higher percentage of zero-entanglement states among zero-negativity states than previously reported.
The generalized quantum Arimoto--Blahut (QAB) algorithm is a powerful derivative-free iterative method in quantum information theory. A key obstacle to its broader use is that existing convergence guarantees typically rely on analytical conditions that are either overly restrictive or difficult to verify for concrete problems. We address this issue by introducing an a posteriori certification viewpoint: instead of requiring fully a priori verifiable assumptions, we provide convergence and error guarantees that can be validated directly from the iterates produced by the algorithm. Specifically, we prove a generalized global convergence theorem showing that, under convexity and a substantially weaker numerically verifiable condition, the QAB iteration converges to the global minimizer. This theorem yields a practical certification procedure: by checking explicit inequalities along the computed trajectory, one can certify global optimality and bound the suboptimality of the obtained value. As an application, we develop a certified iterative scheme for computing the quantum relative entropy of channels, a fundamental measure of distinguishability in quantum dynamics. This quantity is notoriously challenging to evaluate numerically: gradient-based methods are impeded by the complexity of matrix functions such as square roots and logarithms, while recent semidefinite programming approaches can become computationally and memory intensive at high precision. Our method avoids these bottlenecks by combining the QAB iteration with a posteriori certification, yielding an efficient and scalable algorithm. Numerical experiments demonstrate rapid convergence and improved scalability and adaptivity compared with SDP-based approaches.
Within the framework of Information Theory, the existence of correlations between two random variables means that we can obtain information about one of them, just by measuring or observing the other random variable. In certain cases, this kind of relationship allows obtaining information about a variable even when the other is separated by a very large distance, that is, the process of obtaining information is non-local, an example (if not the only) is the quantum entanglement. These features of correlations make it interesting and important to study, classify and quantify them. The correlations are classified into classical correlations and quantum correlations, in addition they are quantified through the mutual information. Here we will present a natural way to define classical mutual information and then we will generalize it to the quantum case. Furthermore, every term in the definitions of mutual information will be interpreted using the concepts of classical and quantum entropy.