A study of the performance of classical minimizers in the Quantum Approximate Optimization Algorithm
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Investigations on the impact of different classical optimizers for parameter optimization in general advocate for gradient-free global optimizers when dealing with real quantum hardware.
“Investigations on the impact of different classical optimizers for parameter optimization in general advocate for gradient-free global optimizers when dealing with real quantum hardware [37, 47, 100, 121].”
From Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study (2024) · cites this paper as [47]
Cites
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Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
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On the Convergence of Adam and Beyond
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Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study
Gemeinhardt, F., Garmendia, A., Wimmer, M., Weder, B., & Leymann, F. (2024) · ACM Computing Surveys · doi:10.1145/3620668 · Cited by 22 · see citing works
“Investigations on the impact of different classical optimizers for parameter optimization in general advocate for gradient-free global optimizers when dealing with real quantum hardware [37, 47, 100, 121].”
Background
- Authors
- Fernández-Pendás, M., Combarro, E. F., Vallecorsa, S., Ranilla, J., & Rúa, I. F.
- Affiliations
- University of the Basque Country (ES)
- Universidad de Oviedo (ES)
- European Organization for Nuclear Research (CH)
- Corresponding author
- Ranilla, José
- Venue
- Journal of Computational and Applied Mathematics
- Publisher
- Elsevier BV
- Published
- 2022-04
- Volume
- 404
- Pages
- 113388
- ISSN
- 0377-0427 (ISSN-L)
- OpenAlex
- W3120643606
- Cited by
- 52
- References
- 16
- Citations by year
- 2026: 8 · 2025: 16 · 2024: 10 · 2023: 12 · 2022: 5 · 2021: 1
- FWCI
- 2.47
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 1461 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Journal of Computational and Applied Mathematics (publishedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- Funders
- Ministerio de Ciencia, Innovación y Universidades (RTI2018-098085-B-C44)
- Ministerio de Economía y Competitividad (MTM-2017-83506-C2-2-P)
- Ministerio de Ciencia e Innovación
- Ministerio de Economía, Industria y Competitividad, Gobierno de España
- Gobierno del Principado de Asturias (FC-GRUPIN-IDI/2018/000193, FC-GRUPIN-IDI/2018/000226)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Physical Sciences › Mathematics › Numerical Analysis › Advanced Optimization Algorithms Research
- Keywords
- quantum approximate optimization algorithm, hybrid quantum-classical optimization, max-cut problem, combinatorial optimization, noisy quantum simulation, variational quantum algorithms
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