Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published September 13, 2021 | Accepted Version + Published
Journal Article Open

Fast tensor disentangling algorithm

Abstract

Many recent tensor network algorithms apply unitary operators to parts of a tensor network in order to reduce entanglement. However, many of the previously used iterative algorithms to minimize entanglement can be slow. We introduce an approximate, fast, and simple algorithm to optimize disentangling unitary tensors. Our algorithm is asymptotically faster than previous iterative algorithms and often results in a residual entanglement entropy that is within 10 to 40% of the minimum. For certain input tensors, our algorithm returns an optimal solution. When disentangling order-4 tensors with equal bond dimensions, our algorithm achieves an entanglement spectrum where nearly half of the singular values are zero. We further validate our algorithm by showing that it can efficiently disentangle random 1D states of qubits.

Additional Information

© 2021 K. Slagle. This work is licensed under the Creative Commons Attribution 4.0 International License. Published by the SciPost Foundation. Received 26-04-2021; Accepted 06-09-2021; Published 13-09-2021. We thank Miles Stoudenmire and Michael Lindsey for helpful discussions and suggestions. Funding information K.S. is supported by the Walter Burke Institute for Theoretical Physics at Caltech; and the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Science Center.

Attached Files

Published - SciPostPhys_11_3_056.pdf

Accepted Version - 2104.08283.pdf

Files

SciPostPhys_11_3_056.pdf
Files (744.1 kB)
Name Size Download all
md5:1b4e7a5a332d90b4dad84d1690670cb3
268.6 kB Preview Download
md5:56fde288c8ebd1b4465f6569b4b715d6
475.5 kB Preview Download

Additional details

Created:
August 20, 2023
Modified:
January 15, 2024