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Predicting nucleon-nucleus scattering observables using nuclear structure theory

Journal Article · · EPJ Web of Conferences (Online)
 [1];  [1];  [2];  [3];  [3];  [1]
  1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
  2. Brookhaven National Laboratory (BNL), Upton, NY (United States)
  3. Alternative Energies and Atomic Energy Commission (CEA), Arpajon (France); Univ. Paris-Saclay, Gif-sur-Yvette (France)
Developing a predictive capability for inelastic scattering will find applications in multiple areas. Experimental data for neutron-nucleus inelastic scattering is limited and thus one needs a robust theoretical framework to complement it. Charged-particle inelastic scattering can be used as a surrogate for (n, γ) reactions to predict capture cross sections for unstable nuclei. Our work uses microscopic nuclear structure calculations for spherical nuclei to obtain nucleon-nucleus scattering potentials and calculate cross sections for these processes. We implement the Jeukenne, Lejeune, Mahaux (JLM) semi-microscopic folding approach, where the medium effects on nuclear interaction are parameterized in nuclear matter to obtain the nucleon-nucleon (NN) interaction in a medium at positive energies. We solve for the nuclear ground state using the Hartree-Fock-Bogliubov (HFB) many-body method, assuming the nucleons within the nucleus interact via the Gogny-D1M potential. The vibrational excited states of the target nucleus are calculated using the quasi-particle random phase approximation (QRPA). We demonstrate our approach for spherical nuclei in the medium-mass region, showing scattering results for the 90Zr nucleus.
Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Science (SC), Nuclear Physics (NP)
Grant/Contract Number:
AC02-98CH10886; SC0012704
OSTI ID:
2368834
Report Number(s):
BNL--225638-2024-JAAM
Journal Information:
EPJ Web of Conferences (Online), Journal Name: EPJ Web of Conferences (Online) Vol. 292; ISSN 2100-014X
Publisher:
EDP SciencesCopyright Statement
Country of Publication:
United States
Language:
English

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