RT Journal Article
T1 Nuclear Physics in the Era of Quantum Computing and Quantum Machine Learning
A1 García Ramos, José Enrique
A1 Sáiz, Álvaro
A1 Arias Carrasco, José Miguel
A1 Lamata, Lucas
A1 Pérez Fernández, Pedro
AB In this paper, the application of quantum simulations and quantum machine learning to solve low-nergy nuclear physics problems is explored. The use of quantum computing to deal with nuclear physics problems is, in general, in its infancy and, in particular, the use of quantum machine learning in the realm of nuclear physics at low energy is almost nonexistent. We present here three specific examples where the use of quantum computing and quantum machine learning provides, or could provide in the future, a possible computational advantage: i) the determination of the phase/shape in schematic nuclear models, ii) the calculation of the ground state energy of a nuclear shell model-type Hamiltonian and iii) the identification of particles or the determination of trajectories in nuclear physics experiments.
PB Wiley
SN 2511-9044 (electrónico)
YR 2024
FD 2024
LK https://hdl.handle.net/10272/22833
UL https://hdl.handle.net/10272/22833
LA eng
NO García‐Ramos, J., Sáiz, Á., Arias, J. M., Lamata, L., & Pérez‐Fernández, P. (2024). Nuclear Physics in the Era of Quantum Computing and Quantum Machine Learning. In Advanced Quantum Technologies. Wiley. https://doi.org/10.1002/qute.202300219
NO This work was partially supported by the Consejería de Universidad,Investigación e Innovación de la Junta de Andalucía (Spain) underGroups FQM-160, FQM-177, and FQM-370, and under projectsP20-00617, P20-00764, P20-01247, and US-1380840; by grants PID2019-104002GB-C21, PID2019-104002GB-C22, PID2020-114687GB-I00,PID2022-136228NB-C21 and PID2022-136228NB-C22 funded byMCIN/AEI/10.13039/50110001103 and “ERDF A way of making Europe”.This work has also been financially supported by the Ministry forDigital Transformation and of Civil Service of the Spanish Governmentthrough the QUANTUM ENIA project call - Quantum Spain project,and by the European Union through the Recovery, Transformation andResilience Plan - NextGenerationEU within the framework of the “DigitalSpain 2026 Agenda”. Funding for open access charge: Universidad de Huelva / CBUA
DS Repositorio Institucional de la Universidad de Huelva
RD 31 may 2026