Quantum Algorithms for Computing Maximal Quantum $f$-divergence and Kubo-Ando means

Fuente: arXiv
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Main Authors: Dinh, Trung Hoa, Nghiem, Nhat A.
Format: Preprint
Published: 2025
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author Dinh, Trung Hoa
Nghiem, Nhat A.
author_facet Dinh, Trung Hoa
Nghiem, Nhat A.
contents The development of quantum computation has resulted in many quantum algorithms for a wide array of tasks. Recently, there is a growing interest in using quantum computing techniques to estimate or compute quantum information-theoretic quantities such as Renyi entropy, Von Neumann entropy, matrix means, etc. Motivated by these results, we present quantum algorithms for computing the maximal quantum $f$-divergences and the operator-theoretic matrix Kubo--Ando means. Both of them involve Renyi entropies, matrix means as special cases, thus implying the universality of our framework.
format Preprint
id arxiv_https___arxiv_org_abs_2511_10607
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Quantum Algorithms for Computing Maximal Quantum $f$-divergence and Kubo-Ando means
Dinh, Trung Hoa
Nghiem, Nhat A.
Quantum Physics
The development of quantum computation has resulted in many quantum algorithms for a wide array of tasks. Recently, there is a growing interest in using quantum computing techniques to estimate or compute quantum information-theoretic quantities such as Renyi entropy, Von Neumann entropy, matrix means, etc. Motivated by these results, we present quantum algorithms for computing the maximal quantum $f$-divergences and the operator-theoretic matrix Kubo--Ando means. Both of them involve Renyi entropies, matrix means as special cases, thus implying the universality of our framework.
title Quantum Algorithms for Computing Maximal Quantum $f$-divergence and Kubo-Ando means
topic Quantum Physics
url https://arxiv.org/abs/2511.10607