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Nuclear Theory·nucl-th

Tuesday·January 13, 2026

12 papers—6 primary·6 cross-listed

All12Primary6Cross-lists6
  1. 01

    Ab initio description of and systems in optical models

    Pierre-Yves Duerinck🇧🇪 · Rimantas Lazauskas🇫🇷

    In the context of the ongoing PUMA experiment (CERN), which investigates antiproton annihilation on atomic nuclei, we study the energy shifts and widths of Rydberg states in the and systems by performing ab initio calculations. The scattering lengths and scattering volumes are first determined by solving the Faddeev-Yakubovsky equations in configuration space. The level shifts and widths of the corresponding and hydrogen-like states are then obtained using the Trueman formula. A pronounced model dependence associated with the nucleon-antinucleon interaction is observed for certain states. Finally, annihilation densities are computed from the four-body wavefunctions. Comparison with the nuclear density distributions indicates that the nucleon-antinucleon annihilation is predominantly peripheral.

    nucl-thPRC(2026)·3 citations
  2. 02

    Entanglement study in the island of inversion region using \textit{ab initio} approach

    Rohit M. Shinde · Praveen C. Srivastava

    Quantum entanglement provides a unique perspective for probing nuclear structure. In this work, we employ quantum entanglement measures, including proton-neutron entanglement entropy, mutual information, and quantum relative entropy, to investigate the evolution of entanglement patterns as we approach neutron-rich nuclei. The study is carried out in the vicinity of the island of inversion region consisting of even- Ne, Mg, and Si isotopes, and also for isotones corresponding to . The state-of-the-art \textit{ab initio} valence space in-medium similarity renormalization group method has been used for this purpose. We have highlighted the role of proton-neutron entanglement entropy in the formation of the island of inversion region. Mutual information provides insight into the strength of correlations between proton-proton, neutron-neutron, and proton-neutron single-particle states. While these correlations are relatively weak between protons and neutrons in the ground states, they become comparable to like-particle correlations in excited states. The quantum relative entropy is also studied between and states of the Ne, Mg, and Si isotopes, as well as isotones, using the Kullback-Leibler divergence and Jensen-Shannon divergence. We have performed these calculations by expressing the nuclear wavefunctions in a Slater-determinant basis and analyzing them through complementary partitions, including proton-neutron and mode-resolved factorizations.

    nucl-thnucl-exPRC(2026)·3 citations
  3. 03

    Unfolding of exotic near-threshold structure and decay dynamics in B

    A. Volya🇺🇸 · S. M. Wang🇨🇳 · M. Płoszajczak🇫🇷 · Z. C. Xu🇨🇳

    Neutron-rich boron isotopes provide a valuable testing ground for threshold-driven structure and reaction phenomena, including halo formation and exotic decay modes. In particular, the structure of and its relation to unbound are of special interest. The nucleus is slightly unbound by approximately , while is bound with a neutron separation energy of about . The observation of a ray in , which we argue originates from a excited state, points to a remarkable situation in which decay and two-neutron decay can compete. We analyze and identify the main reasons for this competition: emission of the neutron pair, and structural realignment driven by the proximity of the one-body threshold, in particular the nearby -wave neutron decay channel. The decay is a unique near-threshold process in which multiple structural components contribute, each with coexisting direct and virtual sequential amplitudes whose interference governs the observables. Because threshold dynamics, continuum coupling, and interference of multiple quantum pathways are universal, closely related scenarios arise in ultracold atoms near Feshbach resonances, few-body atomic and molecular breakups, mesoscopic and photonic open systems, and other areas where open-quantum-system effects impact observables. We employ advanced theoretical models to study this first-of-its-kind case and provide a coherent theoretical perspective based on configuration interaction and complex-energy formalisms that incorporate both reaction continuum and structural effects near threshold.

    nucl-thPRResearch(2026)·0 citations
  4. 04

    Physics-Informed Neural Network for Solving the Heavy Quark Diffusion in the Expanding QCD Medium

    Wenhua Fan🇨🇳 · Jiamin Liu🇨🇳 · Huansang Yang🇺🇸 · Baoyi Chen🇨🇳

    We employ Physics-Informed Neural Networks (PINNs) to investigate the dynamical evolution of heavy quarks within the expanding hot QCD medium generated in relativistic heavy-ion collisions. The heavy quark dynamics are first modeled under the assumption of complete kinetic thermalization, followed by a more realistic study of non-thermal diffusion governed by the Fokker-Planck (FP) equation. In both scenarios, the background evolution of the hot QCD medium is encoded into the coefficients of the diffusion equations. These equations are solved within the PINN framework, where the initial conditions, physical constraints from the dynamical equation, and probability conservation are incorporated into the loss function.We also compare the performance of the FP-PINN with a supervised five-dimensional DNN trained on labeled data generated from Langevin-based reference distributions.This work provides a valuable reference for applying PINN-based models to particle diffusion in phase space, laying the foundation for future studies of heavy quarkonium production via realistic non-thermal heavy-quark coalescence.

    nucl-thPRC(2026)·0 citations
  5. 05

    Multi-Physics Bayesian Analysis of Neutron Star Crust Using Relativistic Mean-Field Model

    Vishal Parmar🇮🇹 · Ignazio Bombaci🇮🇹

    We study the properties of neutron-star crust within a Bayesian framework based on a unified relativistic mean-field (RMF) description of dense matter. The analysis focuses on the posterior distributions of crust properties, constrained by nuclear experimental data, chiral effective field theory, and multimessenger neutron-star observations. In the inference, the outer crust is fixed using the AME2020 nuclear mass table, supplemented by Hartree--Fock--Bogoliubov mass models, while the inner crust is described using a compressible liquid-drop model consistently coupled to the RMF interaction. The same RMF framework is used to describe the uniform core, ensuring a unified treatment across all density regimes. From the resulting posteriors, we extract key crustal observables, including the crust--core transition density and pressure, crust thickness, crust mass, and the fractional crustal moment of inertia. We find that the transition density is primarily governed by the symmetry-energy slope and curvature evaluated at sub-saturation densities, while the transition pressure plays a central role in determining global crustal properties. The inner-crust equation of state reflects a collective interplay between isovector nuclear-matter properties rather than a dependence on any single parameter. We also assess the impact of using matched crust--core constructions and show that they can introduce systematic differences in predicted neutron-star properties when compared with fully unified treatments.

    nucl-thastro-ph.SRPRD(2026)·3 citations
  6. 06

    Learning the relations between neutron star and nuclear matter properties with symbolic regression

    N. K. Patra · Tuhin Malik · Kai Zhou · Constança Providência

    The equation of state (EOS) of dense matter in neutron stars (NSs) remains uncertain, particularly at supra-nuclear densities where complex nuclear interactions and the potential presence of exotic matter, like hyperons, come into play. The complex relationships existing between nuclear matter and neutron star properties are investigated. The focus is on their nonlinearities and interdependencies. In our analysis, we apply a machine learning algorithm known as symbolic regression, paired with principal component analysis, to datasets generated from Bayesian inference over relativistic mean-field models. A systematic Principal Component Analysis has allowed to break down the percentage contribution of each element or feature in the relationships obtained. This study examines two main models (datasets): the NL model, which includes nucleonic degrees of freedom; and the NL-hyp model, which includes hyperons in addition to nucleons. Our analysis confirms a robust correlation between the tidal deformability of a 1.4 \(M_\odot\) neutron star and -equilibrium pressure at twice the nuclear saturation density. This correlation remains once hyperons are included. The contribution of the different nuclear matter properties at saturation to the radius and tidal deformability was calculated. It was shown that the isovector properties have the largest impact, with a contribution of about 90\%. We also studied the relationship between the proton fraction at different densities and various symmetry energy parameters defined at saturation density. For the hyperon data set, we took into account the effects of the negatively charged hyperon in order to recover the relationships. Our study reveals the individual impact of various symmetry energy parameters on proton fractions at different densities.

    nucl-thastro-ph.SRgr-qchep-ph+10 citations

Affiliations

first authorsco-authorsvia INSPIRE