Digitized-counterdiabatic quantum approximate optimization algorithm
dc.contributor.author | Chandarana, Pranav | |
dc.contributor.author | Hegade, Narendra N. | |
dc.contributor.author | Paul, Koushik | |
dc.contributor.author | Albarrán Arriagada, Francisco | |
dc.contributor.author | Solano Villanueva, Enrique Leónidas | |
dc.contributor.author | Del Campo, Adolfo | |
dc.contributor.author | Chen, Xi | |
dc.date.accessioned | 2022-05-12T07:48:08Z | |
dc.date.available | 2022-05-12T07:48:08Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Physical Review Research 4(1) : (2022) // Article ID 013141 | es_ES |
dc.identifier.issn | 2643-1564 | |
dc.identifier.uri | http://hdl.handle.net/10810/56521 | |
dc.description.abstract | [EN] The quantum approximate optimization algorithm (QAOA) has proved to be an effective classical-quantum algorithm serving multiple purposes, from solving combinatorial optimization problems to finding the ground state of many-body quantum systems. Since the QAOA is an Ansatz-dependent algorithm, there is always a need to design Ansatze for better optimization. To this end, we propose a digitized version of the QAOA enhanced via the use of shortcuts to adiabaticity. Specifically, we use a counterdiabatic (CD) driving term to design a better Ansatz, along with the Hamiltonian and mixing terms, enhancing the global performance. We apply our digitized-CD QAOA to Ising models, classical optimization problems, and the P-spin model, demonstrating that it outperforms the standard QAOA in all cases we study. | es_ES |
dc.description.sponsorship | This paper is supported by EU Future and Emerging Technologies (FET) Open Grants EPIQUS (899368) and Quromorphic (828826), the Basque Government IT986-16, the Spanish Government PGC2018-095113-B-I00 (MCIU/AEI/FEDER, UE), projects QMiCS (820505) and OpenSuperQ (820363) of the EU Flagship on Quantum Technologies, NSFC (12075145), and STCSM (2019SHZDZX01-ZX04). X.C. acknowledges the Ramon y Cajal program (RYC-2017-22482). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | American Physical Society | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/RYC-2017-22482 | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICIU/PGC2018-095113-B-I00 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | model | es_ES |
dc.title | Digitized-counterdiabatic quantum approximate optimization algorithm | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.4.013141 | es_ES |
dc.identifier.doi | 10.1103/PhysRevResearch.4.013141 | |
dc.departamentoes | Química física | es_ES |
dc.departamentoeu | Kimika fisikoa | es_ES |
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Except where otherwise noted, this item's license is described as Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.