A digital quantum simulation of the Agassi model Pérez Fernández, Pedro Arias, José Miguel García Ramos, José Enrique Quantum simulation Agassi model This work was partially supported by the Consejería de Trans-formación Económica, Industria, Conocimiento y Universidades de la Junta de Andalucía (Spain) and ERDF under Groups FQM-160, FQM-177, and FQM-370, and under projects P20-00617, P20-00764, P20-01247, UHU-1262561, and US-1380840; by grants PGC2018-095113-B-I00, PID2019-104002GB-C21, PID2019-104002GB-C22, and PID2020-114687GB-I00 funded by MCIN/AEI/10.13039/50110001103 and “ERDF A way of making Europe” and by ERDF, ref. SOMM17/6105/UGR. Resources supporting this work were pro-vided by the CEAFMC and Universidad de Huelva High Performance Computer (HPC@UHU) funded by ERDF/MINECO project UNHU-15CE-2848. A digital quantum simulation of the Agassi model from nuclear physics is proposed and analyzed. The proposal is worked out for the case with four different sites. Numerical simulations and analytical estimations are presented to illustrate the feasibility of this proposal with current technology. The proposed approach is fully scalable to a larger number of sites. The use of a quantum correlation function as a probe to explore the quantum phases by quantum simulating the time dynamics, with no need of computing the ground state, is also studied. Evidence is given showing that the amplitude of the time dynamics of a correlation function in this quantum simulation is linked to the different quantum phases of the system. This approach establishes an avenue for the digital quantum simulation of useful models in nuclear physics. 2022-05-27T07:41:31Z 2022-05-27T07:41:31Z 2022-04-27 journal article Pedro Pérez-Fernández... [et al.]. A digital quantum simulation of the Agassi model, Physics Letters B, Volume 829, 2022, 137133, ISSN 0370-2693, [https://doi.org/10.1016/j.physletb.2022.137133] http://hdl.handle.net/10481/75010 10.1016/j.physletb.2022.137133 eng http://creativecommons.org/licenses/by/3.0/es/ open access Atribución 3.0 España Elsevier