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Nuclear Theory·nucl-th

Monday·July 11, 2022

8 papers—5 primary·3 cross-listed

All8Primary5Cross-lists3
  1. 01

    Principal Component Analysis of Azimuthal Flow in Intermediate-Energy Heavy-Ion Reactions

    Bao-An Li🇺🇸 · Jake Richter🇺🇸

    Principal Component Analysis (PCA) via Singular Value Decomposition (SVD) of large datasets is an adaptive exploratory method to uncover natural patterns underlying the data. Several recent applications of the PCA-SVD to event-by-event single-particle azimuthal angle distribution matrices in ultra-relativistic heavy-ion collisions at RHIC-LHC energies indicate that the sine and cosine functions chosen {\it a priori} in the traditional Fourier analysis are naturally the most optimal basis for azimuthal flow studies according to the data itself. We perform PCA-SVD analyses of mid-central Au+Au collisions at =1.23 GeV simulated using an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model to address the following two questions: (1) if the principal components of the covariance matrix of nucleon azimuthal angle distributions in heavy-ion reactions around 1 GeV/nucleon are naturally sine and/or cosine functions and (2) what if any advantages the PCA-SVD may have over the traditional flow analysis using the Fourier expansion for studying the EOS of dense nuclear matter. We find that (1) in none of our analyses the principal components come out naturally as sine and/or cosine functions, (2) while both the eigenvectors and eigenvalues of the covariance matrix are appreciably EOS dependent, the PCA-SVD has no apparent advantage over the traditional Fourier analysis for studying the EOS of dense nuclear matter using the azimuthal collective flow in heavy-ion collisions.

    nucl-thnucl-exNPA(2023)·3 citations
  2. 02

    Neutron Single-particle States in 101Sn by Polynomial Fits and Shell Model Calculations for Light Sn Isotopes

    Abderrahmane Yakhelef · Serkan Akkoyun

    One of the main ingredients in nuclear structure studies using shell model are the single-particle energy (spe). In order to obtain these values accurately, experimental data is needed. The region around the doubly magic nuclide 100Sn is very interesting for nuclear studies in terms of structure, reaction and nuclear astrophysics. Experimental spectrum data for the 101Sn isotope is required for nuclear shell model studies to be carried out in this region. Since there is not enough experimental data in the literature, different approaches are used for the obtaining spes for the region such as using the hole excitation spectrum in 131Sn or using the lightest and closest isotope 107Sn which figures the model space orbitals. In this work, we have performed second order polynomial fits of the tree single-particle states s1/2, d3/2 and h11/2 in the light Sn isotopes up to 113Sn and 115Sn which are not determined yet experimentally. By an extrapolation toward light Sn isotopes, we can obtain the excitation energies of all the single-particle states in 101Sn. Subsequently, neutron spes of the model space orbitals are defined. Shell model calculations for even and odd 102-107Sn isotopes are carried out using the new interactions and the results are compared with the experimental data and results obtained using the widely used interaction sn100pn.

    nucl-thBraz.J.Phys.(2024)·1 citation
  3. 03

    On the proton-deuteron backward scattering

    S. Bondarenko · S. Yurev

    The article is devoted to the relativistic study of elastic backward scattering based on the one-nucleon exchange diagram. Calculations were performed using relativistic deuteron wave functions obtained by solving the Bethe-Salpeter equation in the Minkowski space with relativistic separable potentials. The unpolarized differential cross section as well as some polarization observables of the reaction for initial proton momentum up to 7.3 GeV were calculated. The obtained results are compared with the calculations of other authors.

    nucl-th0 citations
  4. 04

    Machine Learning for the Prediction of Converged Energies from Ab Initio Nuclear Structure Calculations

    Marco Knöll · Tobias Wolfgruber · Marc L. Agel · Cedric Wenz · Robert Roth

    The prediction of nuclear observables beyond the finite model spaces that are accessible through modern ab initio methods, such as the no-core shell model, pose a challenging task in nuclear structure theory. It requires reliable tools for the extrapolation of observables to infinite many-body Hilbert spaces along with reliable uncertainty estimates. In this work we present a universal machine learning tool capable of capturing observable-specific convergence patterns independent of nucleus and interaction. We show that, once trained on few-body systems, artificial neural networks can produce accurate predictions for a broad range of light nuclei. In particular, we discuss neural-network predictions of ground-state energies from no-core shell model calculations for 6Li, 12C and 16O based on training data for 2H, 3H and 4He and compare them to classical extrapolations.

    nucl-thPLB(2023)·23 citations
  5. 05

    Phase transitions and latent heat in magnetized matter

    M.R. Pelicer🇧🇷 · D.P. Menezes🇧🇷

    Based on the assumption that the QCD phase diagram gives a realistic picture of hadronic and quark matter under different regimes, it is possible to claim that a quark core may be present inside compact objects commonly named hybrid neutron stars or even that a pure strange star may exist. In this work we explore how the phase transition is modified by the presence of strong magnetic fields and how it is impacted by parameters of the quark phase, for which we use the MIT-model with vector interactions. The phase transition is assumed to conserve flavor when hadrons turn into deconfined quarks. The hadronic equation of state is calculated with the NL3 parametrization of quantum hadrodynamics. We find that the magnetic field slightly reduces the pressure and chemical potential of the phase transition and the latent heat, the latter being very model dependent.

    nucl-thEPJA(2022)·7 citations

Affiliations

first authorsco-authorsvia INSPIRE