Related papers: Nuclear Physics in the Era of Quantum Computing and Quantum Machine Learning

Nuclear Physics in the Era of Quantum Computing and Quantum Machine Learning

URL: http://arxiv.org/abs/2307.07332v1
Date: Fri, 14 Jul 2023 13:18:32 GMT
Title: Nuclear Physics in the Era of Quantum Computing and Quantum Machine Learning
Authors: J.E. Garc\'ia-Ramos, A. S\'aiz, J.M. Arias, L. Lamata, P. P\'erez-Fern\'andez
Abstract summary: The use of quantum computing to deal with nuclear physics problems is, in general, in its infancy. We present here three specific examples where the use of quantum computing and quantum machine learning provides, or could provide in the future.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: In this paper, the application of quantum simulations and quantum machine learning to solve low-energy 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.

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