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Nuclear Theory·nucl-th

Wednesday·March 8, 2023

11 papers—4 primary·7 cross-listed

All11Primary4Cross-lists7
  1. 01

    [Submitted on 7 Mar 2023]

    Empirical neutron star mass formula based on experimental observables

    Hajime Sotani · Tomoya Naito

    We derive the empirical formulae expressing the mass and gravitational redshift of a neutron star, whose central density is less than threefold the nuclear saturation density, as a function of the neutron-skin thickness or the dipole polarizability of or , especially focusing on the 8 Skyrme-type effective interactions. The neutron star mass and its gravitational redshift can be estimated within errors with our formulae, while the neutron star radius is also expected within a few errors by combining the derived formulae. Owing to the resultant empirical formulae, we find that the neutron star mass and radius are more sensitive to the neutron-skin thickness of than the dipole polarizability of or .

    Comments:
    Accepted for publication in RPC
    Subjects:
    Nuclear Theory (nucl-th); High Energy Astrophysical Phenomena (astro-ph.HE)
    arXiv:
    2303.03631 [pdf]
    PRC(2023)·14 citations
  2. 02

    [Submitted on 7 Mar 2023]

    Search for jet quenching effects on the plain jet mass in Pb+Pb collisions at the LHC with a multiphase transport model

    Xiang-Pan Duan🇨🇳 · Guo-Liang Ma🇨🇳

    The plain jet mass distributions of reconstructed jets are investigated in p+p and 0-10 most central Pb+Pb collisions at using a dynamical multiphase transport model with a string melting mechanism. It is observed that the mean charged jet mass increases with increasing jet transverse momentum and jet radius in central Pb+Pb collisions. It is demonstrated that the plain jet mass of reconstructed partonic jet is shifted to a higher value after the evolution of partonic stage due to jet quenching in central Pb+Pb collisions. However, the jet mass shift effect is strongly weakened by non-perturbative effects from hadronization and hadron rescatterings. This makes it difficult to observe significant hot medium modification effects on the plain jet mass distribution in the final state of relativistic heavy-ion collisions.

    Comments:
    9 pages, 6 figures, accepted for publication in European Physical Journal A
    Subjects:
    Nuclear Theory (nucl-th); High Energy Physics — Phenomenology (hep-ph); Nuclear Experiment (nucl-ex)
    arXiv:
    2303.03773 [pdf]
    EPJA(2023)·3 citations
  3. 03

    [Submitted on 7 Mar 2023]

    Improved Superscaling in Quasielastic Electron Scattering with Relativistic Effective Mass

    P.R. Casale🇪🇸 · J.E. Amaro🇪🇸 · V.L. Martinez-Consentino🇪🇸 · I. Ruiz Simo🇪🇸

    Superscaling in electron scattering from nuclei is re-examined paying special attention to the definition of the averaged single-nucleon responses. The validity of the extrapolation of nucleon responses in the Fermi gas has been examined, which previously lacked a theoretical foundation. To address this issue, we introduce new averaged responses with a momentum distribution smeared around the Fermi surface, allowing for momenta above the Fermi momentum. This approach solves the problem of negativity in the extrapolation away from the scaling region and, at the same time, validates its use in the scaling analysis. This work has important implications for the interpretation of scaling data and contributes to the development of a more complete understanding of the scaling approach.

    Subjects:
    Nuclear Theory (nucl-th); High Energy Physics — Phenomenology (hep-ph)
    arXiv:
    2303.03890 [pdf]
    Universe(2023)·8 citations
  4. 04

    [Submitted on 7 Mar 2023]

    Solving Schrodinger equations using physically constrained neural network

    Kai-Fang Pu · Hanlin Li · Hong-Liang Lu · Long-Gang Pang

    Deep neural network (DNN) and auto differentiation have been widely used in computational physics to solve variational problems. When DNN is used to represent the wave function to solve quantum many-body problems using variational optimization, various physical constraints have to be injected into the neural network by construction, to increase the data and learning efficiency. We build the unitary constraint to the variational wave function using a monotonic neural network to represent the Cumulative Distribution Function (CDF) . Using this constrained neural network to represent the variational wave function, we solve Schrodinger equations using auto-differentiation and stochastic gradient descent (SGD), by minimizing the violation of the trial wave function to the Schrodinger equation. For several classical problems in quantum mechanics, we obtain their ground state wave function and energy with very low errors. The method developed in the present paper may pave a new way in solving nuclear many body problems in the future.

    Subjects:
    Nuclear Theory (nucl-th)
    arXiv:
    2303.03934 [pdf]
    CPC(2023)·10 citations

Affiliations

first authorsco-authorsvia INSPIRE