Tue·Oct 10, 2023Tuesday·October 10, 2023

1. 01*

   Candidate toroidal electric dipole mode in the spherical nucleus ${}^{58}$Ni

   P. von Neumann-Cosel (1)🇩🇪 · V.O. Nesterenko (2,3)🇷🇺 · I. Brandherm (1) · P.I. Vishnevskiy (2,4) · P.-G. Reinhard (5)🇩🇪 · J. Kvasil (6) · H. Matsubara (7,8)🇯🇵 · A. Repko (9)🇸🇰 · A. Richter (1)🇩🇪 · M. Scheck (10,11)🇬🇧 · A. Tamii (7) ((1) Institut für Kernphysik, Technische Universität Darmstadt, Darmstadt, Germany, (2) Laboratory of Theoretical Physics, Joint Institute for Nuclear Research, Dubna, Russia, (3) State University "Dubna", Dubna, Moscow region, Russia, (4) Institute of Nuclear Physics Almaty, Almaty Region, Kazakhstan, (5) Institut für Theoretische Physik II, Universität Erlangen, Erlangen, Germany, (6) Institute of Particle and Nuclear Physics, Charles University, Praha, Czech Republic, (7) Research Center for Nuclear Physics, Osaka University, Ibaraki, Osaka, Japan, (8) Faculty of Radiological Technology, Fujita Health University, Aichi, Japan, (9) Institute of Physics, Slovak Academy of Sciences, Bratislava, Slovakia, (10) School of Computing, Engineering, and Physical Sciences, University of the West of Scotland, Paisley, United Kingdom, (11) Scottish Universities Physics Alliance, United Kingdom)🇯🇵

   Dipole toroidal modes appear in many fields of physics. In nuclei, such a mode was predicted more than 50 years ago, but clear experimental evidence was lacking so far. Using a combination of high-resolution inelastic scattering experiments with photons, electrons and protons, we identify for the first time candidates for toroidal dipole excitations in the nucleus ${}^{58}$Ni and demonstrate that transverse electron scattering form factors represent a relevant experimental observable to prove their nature.

   nucl-exnucl-thPRL(2024)·18 citations
2. 02*

   Subthreshold production of $J/\psi$ mesons from the deuteron with SoLID

   T. Liu🇨🇳 · Z. W. Zhao🇺🇸 · M. Cai🇨🇳 · D. Byer🇺🇸 · H. Gao🇺🇸

   The electro- and photo-production of $J/\psi$ meson near the threshold from the proton is relevant to the search of hidden charm pentaquark candidates reported by the LHCb collaboration, and the study of the QCD trace anomaly's contribution to the proton mass. It is also expected to be sensitive to the QCD van der Waals interaction, that is mediated by multi-gluon exchanges and expected to dominate the interaction between two hadrons with no common valence quarks. Subthreshold production of $J/\psi$ from a nuclear target is expected to enhance such attractive interaction, and also allows for a direct probe of short range correlations inside a nucleus. With the high luminosity capability of the 12-GeV CEBAF facility at Jefferson Lab, high-precision data on $J/\psi$ meson production from the proton is becoming available, providing also a reference for subthreshold $J/\psi$ production from the deuteron. Data from the deuteron will establish the baseline for subthreshold $J/\psi$ production from other nuclear targets. In this paper, we present our findings from a feasibility study of subthreshold $J/\psi$ production from the deuteron using the proposed Solenoidal Large Intensity Device (SoLID), and discuss the potential physics impact of such data.

   nucl-exPRC(2024)·7 citations
3. 03*

   On the Microscopic Level Density Models for Nuclei Near Z=28 Shell Closure

   Surayya H.E (1) · Jesmi Sunny (1) · M.M Musthafa (1) · C.V Midhun (1) · S.V Suryanarayana (2) · Jyoti Pandey (3) · A Pal (2)🇮🇳 · P.C Rout (2) · S Santra (2)🇮🇳 · Antony Joseph (1) · S. Ganesan (4). (Department of Physics, University of Calicut, Kerala, India (1), Nuclear Physics Division, Bhabha Atomic Research Centre, Mumbai 400085, India (2), Inter University Accelerator Centre, New Delhi, Delhi 110067, India (3) and Formarly Raja Ramanna Fellow, Bhabha Atomic Research Centre, Mumbai 400085, India (4))

   A comprehensive test of level density models for explaining the decay of excited compound nuclei, 54 Mn, 56 Fe, 58 Co, 60 Ni, 61 Ni and 63 Cu, in the energy range of 28 - 36 MeV has been performed. The compound nuclei of interest in the desired ranges are populated using 6 Li based transfer reactions. The proton decay spectrum for each excitation energy bins has been measured. The measured proton spectrum has been reproduced using statistical model calculations with different level density models. A variance minimised approach has been employed for analysing the prediction capability of different level density models. This approach has been converged to Gogny Hartree-Fock-Bogoliubov(HFB) microscopic level density model and which is attributed as the most accurate model for the desired nuclei.

   nucl-exnucl-thPRC(2025)·0 citations
4. 04*

   Importance of physical information on the prediction of heavy-ion fusion cross section with machine learning

   Zhilong Li🇨🇳 · Zepeng Gao🇨🇳 · Ling Liu🇨🇳 · Yongjia Wang🇨🇳 · Long Zhu🇨🇳 · Qingfeng Li🇨🇳

   In this work, the Light Gradient Boosting Machine (LightGBM), which is a modern decision tree based machine-learning algorithm, is used to study the fusion cross section (CS) of heavy-ion reaction. Several basic quantities (e.g., mass number and proton number of projectile and target) and the CS obtained from phenomenological formula are fed into the LightGBM algorithm to predict the CS. It is found that, on the validation set, the mean absolute error (MAE) which measures the average magnitude of the absolute difference between $lo{g}_{10}$ of the predicted CS and experimental CS is 0.129 by only using the basic quantities as the input, this value is smaller than 0.154 obtained from the empirical coupled channel model. MAE can be further reduced to 0.08 by including an physical-informed input feature. The MAE on the test set (it consists of 280 data points from 18 reaction systems that not included in the training set) is about 0.19 and 0.53 by including and excluding the physical-informed feature, respectively. We further verify the LightGBM predictions by comparing the CS of ${}^{40,48}\mathrm{Ca}$+${}^{78}\mathrm{Ni}$ obtained from the density-constrained time-dependent Hartree-Fock approach. Our study demonstrates the importance of physical information in predicting fusion cross section of heavy-ion reaction with machine learning.

   ↳ nucl-thnucl-exPRC(2024)·17 citations

* Reconstructed cohort: no mailing for this day survives in the archive. Papers are grouped by their submission times and arXiv's announcement cut-off, assuming announcement without delay; positions follow identifier order. Validated at ~91% exact-day agreement against the archived era.