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Adaptive optimal control of entangled qubits
Developing fast, robust, and accurate methods for optimal control of quantum systems comprising interacting particles is one of the most active areas of current science. Although a valuable repository of algorithms is available for numerical applications in quantum control, the high computational co...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9728963/ https://www.ncbi.nlm.nih.gov/pubmed/36475803 http://dx.doi.org/10.1126/sciadv.abq4244 |
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author | Goodwin, David L. Singh, Pranav Foroozandeh, Mohammadali |
author_facet | Goodwin, David L. Singh, Pranav Foroozandeh, Mohammadali |
author_sort | Goodwin, David L. |
collection | PubMed |
description | Developing fast, robust, and accurate methods for optimal control of quantum systems comprising interacting particles is one of the most active areas of current science. Although a valuable repository of algorithms is available for numerical applications in quantum control, the high computational cost is somewhat overlooked. Here, we present a fast and accurate optimal control algorithm for systems of interacting qubits, QOALA (quantum optimal control by adaptive low-cost algorithm), which is predicted to offer [Formula: see text] (M(2)) speedup for an M-qubit system, compared to the state-of-the-art exact methods, without compromising overall accuracy of the optimal solution. The method is general and compatible with diverse Hamiltonian structures. The proposed approach uses inexpensive low-accuracy approximations of propagators far from the optimum, adaptively switching to higher accuracy, higher-cost propagators when approaching the optimum. In addition, the utilization of analytical Lie algebraic derivatives that do not require computationally expensive matrix exponential brings even better performance. |
format | Online Article Text |
id | pubmed-9728963 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-97289632022-12-13 Adaptive optimal control of entangled qubits Goodwin, David L. Singh, Pranav Foroozandeh, Mohammadali Sci Adv Physical and Materials Sciences Developing fast, robust, and accurate methods for optimal control of quantum systems comprising interacting particles is one of the most active areas of current science. Although a valuable repository of algorithms is available for numerical applications in quantum control, the high computational cost is somewhat overlooked. Here, we present a fast and accurate optimal control algorithm for systems of interacting qubits, QOALA (quantum optimal control by adaptive low-cost algorithm), which is predicted to offer [Formula: see text] (M(2)) speedup for an M-qubit system, compared to the state-of-the-art exact methods, without compromising overall accuracy of the optimal solution. The method is general and compatible with diverse Hamiltonian structures. The proposed approach uses inexpensive low-accuracy approximations of propagators far from the optimum, adaptively switching to higher accuracy, higher-cost propagators when approaching the optimum. In addition, the utilization of analytical Lie algebraic derivatives that do not require computationally expensive matrix exponential brings even better performance. American Association for the Advancement of Science 2022-12-07 /pmc/articles/PMC9728963/ /pubmed/36475803 http://dx.doi.org/10.1126/sciadv.abq4244 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Physical and Materials Sciences Goodwin, David L. Singh, Pranav Foroozandeh, Mohammadali Adaptive optimal control of entangled qubits |
title | Adaptive optimal control of entangled qubits |
title_full | Adaptive optimal control of entangled qubits |
title_fullStr | Adaptive optimal control of entangled qubits |
title_full_unstemmed | Adaptive optimal control of entangled qubits |
title_short | Adaptive optimal control of entangled qubits |
title_sort | adaptive optimal control of entangled qubits |
topic | Physical and Materials Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9728963/ https://www.ncbi.nlm.nih.gov/pubmed/36475803 http://dx.doi.org/10.1126/sciadv.abq4244 |
work_keys_str_mv | AT goodwindavidl adaptiveoptimalcontrolofentangledqubits AT singhpranav adaptiveoptimalcontrolofentangledqubits AT foroozandehmohammadali adaptiveoptimalcontrolofentangledqubits |