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research article

Quantum Tensor-Product Decomposition from Choi-State Tomography

Mansuroglu, Refik
•
Adil, Arsalan
•
Hartmann, Michael J.
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July 1, 2024
PRX Quantum

The Schmidt decomposition is the go-to tool for measuring bipartite entanglement of pure quantum states. Similarly, it is possible to study the entangling features of a quantum operation using its operator-Schmidt or tensor-product decomposition. While quantum technological implementations of the former are thoroughly studied, entangling properties on the operator level are harder to extract in the quantum computational framework because of the exponential nature of sample complexity. Here, we present an algorithm for unbalanced partitions into a small subsystem and a large one (the environment) to compute the tensor-product decomposition of a unitary the effect of which on the small subsystem is captured in classical memory, while the effect on the environment is accessible as a quantum resource. This quantum algorithm may be used to make predictions about operator nonlocality and effective open quantum dynamics on a subsystem, as well as for finding low-rank approximations and low-depth compilations of quantum circuit unitaries. We demonstrate the method and its applications on a time-evolution unitary of an isotropic Heisenberg model in two dimensions.

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Type
research article
DOI
10.1103/PRXQuantum.5.030306
Scopus ID

2-s2.0-85198568424

Author(s)
Mansuroglu, Refik

Friedrich-Alexander-Universität Erlangen-Nürnberg

Adil, Arsalan

University of California, Davis

Hartmann, Michael J.

Friedrich-Alexander-Universität Erlangen-Nürnberg

Holmes, Zoë  

École Polytechnique Fédérale de Lausanne

Sornborger, Andrew T.

Los Alamos National Laboratory

Date Issued

2024-07-01

Published in
PRX Quantum
Volume

5

Issue

3

Article Number

030306

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
QIC  
FunderFunding(s)Grant NumberGrant URL

Sandoz Family Foundation Monique de Meuron program for Academic Promotion

Office of High Energy Physics

Sandoz Family Foundation

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Available on Infoscience
January 24, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/243440
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