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Journal of Physics G: Nuclear and Particle Physics - latest papers

Latest articles for Journal of Physics G: Nuclear and Particle Physics

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  • Corrigendum: Quantum number conservation: a tool in the design and analysis of high energy experiments (2024 J. Phys. G: Nucl. Part. Phys. 51 095002)
  • Variational inference of effective range parameters for 3He−4He scattering
    We use two different methods, Monte Carlo sampling and variational inference (VI), to perform a Bayesian calibration of the effective-range parameters in 3He–4He elastic scattering. The parameters are calibrated to data from a recent set of 3He–4He elastic scattering differential cross section measurements. Analysis of these data for Elab ≤ 4.3 MeV yields a unimodal posterior for which both methods obtain the same structure. However, the effective-range expansion amplitude does not account for the 7/2− state of 7Be so, even after calibration, the description of data at the upper end of this energy range is poor. The data up to Elab = 2.6 MeV can be well described, but calibration to this lower-energy subset of the data yields a bimodal posterior. After adapting VI to treat such a multi-modal posterior we find good agreement between the VI results and those obtained with parallel-tempered Monte Carlo sampling.

  • Charged pions asymmetry due to interference from the decay of light neutral axial mesons
    Effective three meson couplings, based in flavor U(3) quark–antiquark interactions, are considered to describe two light neutral axial meson strong decays, A ∼ f1(1285) and f1S(1420), and the charged rho meson decay in the following channels: A → ρ∓(770) + π±, and ρ± → π±π0. By considering neutral meson mixings, such as , and η − π0 for the channels investigated, the leading three-meson interactions may lead to decay amplitudes that undergo interference and a resulting ratio of decay rate into charged pions, , slightly smaller than one. For that it will be assumed that the produced charged vector mesons or charged scalar mesons undergo absorption, decay into channels without charged pions, or any other inelastic process that may suppress their decays into charged pions.

  • The finite volume effects of the Nambu–Jona–Lasinio model with the running coupling constant
    With Schwinger’s proper-time formalism of the Nambu–Jona–Lasinio model, we investigate the finite volume effects with the anti-periodic boundary condition in the presence of magnetic fields. The model is solved with a running coupling constant G(B), which is properly fitted by the lattice average (Σu + Σd)/2 and the difference Σu − Σd. For the model in a finite or infinite volume, the magnetic fields can increase the constituent quark mass M while the temperatures can decrease it. M is close to the infinite volume limit when the box length L is appropriately large. For a sufficiently small value of L, M is close to the chiral limit. The finite volume effects behave intensely in the narrow ranges of L where the partial derivative ∂M/∂L is greater than zero. These narrow ranges can be reduced by stronger magnetic fields and by higher temperatures. In addition, the chiral limit can be restored by a sufficiently small finite volume and be broken by sufficiently strong magnetic fields. Finally, we discuss the thermal susceptibility and the crossover phase transition depending on the temperature at finite volume in the presence of magnetic fields.

  • Machine learning the in-medium correction factor on nucleon–nucleon elastic cross section
    The nuclear equation of state cannot be directly measured in the heavy-ion collision experiments; it is usually inferred from the comparison between transport model simulations and experimental measurements. The in-medium correction factor (F, which is defined as the ratio of the cross section in the nuclear medium to that in free space) on the nucleon–nucleon elastic cross section is one of the important inputs of the transport model, and its magnitude is still debated. The advent of machine learning (ML) has profoundly influenced the way scientists study the natural world and has provided a new paradigm that merges traditional investigation with advanced data-driven techniques. The aim of this work is to present a ML-based method to study the in-medium correction factor F. The ultra-relativistic quantum molecular dynamics (UrQMD) transport model is used to simulate + collisions at beam energy of 0.27 GeV/nucleon with different impact parameters. The value of F is randomly selected from 0.4 to 0.8 for the simulation of each event. Several observables simulated by the UrQMD model with different F, which are thought to be probably sensitive to the in-medium nucleon–nucleon cross sections, are fed into the LightGBM (Light Gradient Boosting Machine, which is a modern decision tree-based ML algorithm) to establish the mapping between the observables and F. The mean absolute error (MAE), which is the absolute difference between the true and the predicted F, is about 0.080 and 0.021 by using event-by-event and 40-event summed observables, respectively. It indicates that ML can recognize information about the F factor. Furthermore, according to the results of Shapley Additive exPlanations, an interpretability analysis method in ML, features that have the greatest effect on the F are identified. ML combined with the transport model may open a new venue to study the F factor. In addition, the interpretability analysis of the ML algorithm may also offer valuable insights for subsequent research.