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Nuclear Theory·nucl-th

Friday·May 5, 2023

8 papers—4 primary·4 cross-listed

All8Primary4Cross-lists4
  1. 01

    Light nuclei production in Au+Au collisions at GeV from coalescence model

    Yue Xu🇨🇳 · Xionghong He🇨🇳 · Nu Xu🇨🇳

    The nucleon coalescence model is one of the most popular theoretical models for light nuclei production in high-energy heavy-ion collisions. The production of light nuclei , , He, and He is studied using the transport model JAM with a simplified afterburner coalescence at GeV Au+Au collisions. We scan the cut-off of phenomenological coalescence parameters, the relative spatial distance and momentum difference , for formation of light nuclei by nucleon coalescence to reproduce the light nuclei spectra measured by STAR experiment. The results indicate a potential connection between the coalescence parameters and the binding energy as well as the diameter of these light nuclei.

    nucl-thCPC(2023)·5 citations
  2. 02

    Probabilistic neural networks for improved analyses with phenomenological models

    C.H. Kim · K.Y. Chae · M.S. Smith · D.W. Bardayan · C.R. Brune · R.J. deBoer · D. Lu · D. Odell

    Physics models typically contain adjustable parameters to reproduce measured data. While some parameters correspond directly to measured features in the data, others are unobservable. These unobservables can, in some cases, cause ambiguities in the extraction of observables from measured data, or lead to questions on the physical interpretation of fits that require these extra parameters. We propose a method based on deep learning to extract values of observables directly from the data without the need for unobservables. The key to our approach is to label the training data for the deep learning model with only the observables. After training, the deep learning model can determine the values of observables from measured data with no ambiguities arising from unobservables. We demonstrate this method on the phenomenological R-matrix that is widely utilized in nuclear physics to extract resonance parameters from cross section data. Our deep learning model based on Transformers successfully predicts nuclear properties from measurements with no need for the channel radius and background pole parameters required in traditional R-matrix analyses. Details and limitations of this method, which may be useful for studies of a wide range of phenomena, are discussed.

    nucl-thPRC(2024)·3 citations
  3. 03

    Collapse of the shell closure in the newly discovered Na and the development of deformed halos towards the neutron dripline

    K. Y. Zhang · P. Papakonstantinou · M.-H. Mun · Y. Kim · H. Yan · X.-X. Sun

    Halos and changes of nuclear magicities have been extensively investigated in exotic nuclei during past decades. The newly discovered Na with the neutron number provides a new platform to explore such novel phenomena near the neutron dripline of the sodium isotopic chain. We study the shell property and the possible halo structure in Na within the deformed relativistic Hartree-Bogoliubov theory in continuum. It is found that the lowering of orbitals in the spherical limit results in the collapse of the shell closure in Na, and a well deformed ground state is established. The pairing correlations and the mixing of components driven by deformation lead to the occupation of weakly bound or continuum -wave neutron orbitals. An oblate halo is therefore formed around the prolate core in Na, making Na a single nucleus with the coexistence of several exotic structures, including the quenched shell closure, Borromean structure, deformed halo, and shape decoupling. The microscopic mechanisms behind the shape decoupling phenomenon and the development of halos towards dripline are revealed.

    nucl-thnucl-exPRC(2023)·58 citations
  4. 04

    Kinetic approach of light-nuclei production in intermediate-energy heavy-ion collisions

    Rui Wang · Yu-Gang Ma · Lie-Wen Chen · Che Ming Ko · Kai-Jia Sun · Zhen Zhang

    We develop a kinetic approach to the production of light nuclei up to mass number in intermediate-energy heavy-ion collisions by including them as dynamic degrees of freedom. The conversions between nucleons and light nuclei during the collisions are incorporated dynamically via the breakup of light nuclei by a nucleon and their inverse reactions. We also include the Mott effect on light nuclei, i.e., a light nucleus would no longer be bound if the phase-space density of its surrounding nucleons is too large. With this kinetic approach, we obtain a reasonable description of the measured yields of light nuclei in central Au+Au collisions at energies of - by the FOPI collaboration. Our study also indicates that the observed enhancement of the -particle yield at low incident energies can be attributed to a weaker Mott effect on the -particle, which makes it more difficult to dissolve in nuclear medium, as a result of its much larger binding energy.

    nucl-thPRC(2023)·48 citations

Affiliations

first authorsco-authorsvia INSPIRE