Juan Carlos Criado
Quantum fitting framework applied to effective field theories
Criado, Juan Carlos; Spannowsky, Michael; Kogler, Roman
Abstract
The use of experimental data to constrain the values of the Wilson coefficients of an effective field theory involves minimizing a χ2 function that may contain local minima. Classical optimization algorithms can become trapped in these minima, preventing the determination of the global minimum. The quantum annealing framework has the potential to overcome this limitation and reliably find the global minimum of nonconvex functions. We present QFitter, a quantum annealing method to perform effective field theory fits. Using a state-of-the-art quantum annealer, we show with concrete examples that QFitter can be used to fit sets of at least eight coefficients, including their quadratic contributions. An arbitrary number of observables can be included without changing the required number of qubits. We provide an example in which χ2 is nonconvex and show that QFitter can find the global minimum more accurately than its classical alternatives.
Citation
Criado, J. C., Spannowsky, M., & Kogler, R. (2023). Quantum fitting framework applied to effective field theories. Physical Review D, 107(1), Article 015023. https://doi.org/10.1103/physrevd.107.015023
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 5, 2023 |
Online Publication Date | Jan 25, 2023 |
Publication Date | 2023 |
Deposit Date | May 15, 2023 |
Publicly Available Date | May 15, 2023 |
Journal | Physical Review D |
Print ISSN | 2470-0010 |
Electronic ISSN | 2470-0029 |
Publisher | American Physical Society |
Peer Reviewed | Peer Reviewed |
Volume | 107 |
Issue | 1 |
Article Number | 015023 |
DOI | https://doi.org/10.1103/physrevd.107.015023 |
Public URL | https://durham-repository.worktribe.com/output/1172925 |
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Copyright Statement
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.
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