Saved in:
Bibliographic Details
Main Authors: De Palma, Giacomo, Klein, Tristan, Pastorello, Davide
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2309.08426
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917792846970880
author De Palma, Giacomo
Klein, Tristan
Pastorello, Davide
author_facet De Palma, Giacomo
Klein, Tristan
Pastorello, Davide
contents Classical shadows constitute a protocol to estimate the expectation values of a collection of M observables acting on O(1) qubits of an unknown n-qubit state with a number of measurements that is independent of n and that grows only logarithmically with M. We propose a local variant of the quantum Wasserstein distance of order 1 of [De Palma et al., IEEE Trans. Inf. Theory 67, 6627 (2021)] and prove that the classical shadow obtained measuring O(log n) copies of the state to be learned constitutes an accurate estimate with respect to the proposed distance. We apply the results to quantum generative adversarial networks, showing that quantum access to the state to be learned can be useful only when some prior information on such state is available.
format Preprint
id arxiv_https___arxiv_org_abs_2309_08426
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Classical shadows meet quantum optimal mass transport
De Palma, Giacomo
Klein, Tristan
Pastorello, Davide
Quantum Physics
Mathematical Physics
Classical shadows constitute a protocol to estimate the expectation values of a collection of M observables acting on O(1) qubits of an unknown n-qubit state with a number of measurements that is independent of n and that grows only logarithmically with M. We propose a local variant of the quantum Wasserstein distance of order 1 of [De Palma et al., IEEE Trans. Inf. Theory 67, 6627 (2021)] and prove that the classical shadow obtained measuring O(log n) copies of the state to be learned constitutes an accurate estimate with respect to the proposed distance. We apply the results to quantum generative adversarial networks, showing that quantum access to the state to be learned can be useful only when some prior information on such state is available.
title Classical shadows meet quantum optimal mass transport
topic Quantum Physics
Mathematical Physics
url https://arxiv.org/abs/2309.08426