PaperPanorama

Nuclear Theory·nucl-th

Wednesday·October 27, 2021

11 papers6 primary·5 cross-listed

  1. 07

    [Submitted on 22 Oct 2021] (cross-list from hep-ph)

    Hadron Production in terms of Green's Functions in Non-Equilibrium Matter

    A.V.Koshelkin🇷🇺

    Following the quark-hadron duality concept, we show that the number of hadrons generated in the deconfinement matter is entirely determined by the exact non-equilibrium Green's functions of partons in the medium and the vertex function governing the probability of the confinement-deconfinement phase transition. In such an approach, compactifying the standard (3+1) chromodynamics into , the rate of the hadrons produced in particle collisions is derived in the explicit form provided that the hadronization is the first order phase transition. The pion production is found to be in good agreement to the experimental results on the pion yield in pp collisions.

    Subjects:
    High Energy Physics — Phenomenology (hep-ph); High Energy Physics — Theory (hep-th); Nuclear Theory (nucl-th)
    arXiv:
    2110.13139 [pdf]
    SciPost Phys.Proc.(2022)·0 citations
  2. 08

    [Submitted on 26 Oct 2021] (cross-list from hep-lat)

    QCD viscosity by combining the gradient flow and sparse modeling methods

    Etsuko Itou🇯🇵 · Yuki Nagai🇯🇵

    We give a new description to obtain the shear viscosity in QCD at finite temperature. Firstly, we obtain the correlation function of the renormalized energy-momentum tensor using the gradient flow method. Secondly, we estimate the spectral function from the smeared correlation functions using the sparse modeling method. The combination of these two methods looks promising to determine the shear viscosity precisely.

    Comments:
    9pages, 3figures, Proceedings of The 38th International Symposium on Lattice Field Theory, LATTICE2021 26th-30th July, 2021, (ver2) Figure 1 is changed, reference is added
    Subjects:
    High Energy Physics — Lattice (hep-lat); High Energy Physics — Phenomenology (hep-ph); Nuclear Theory (nucl-th)
    arXiv:
    2110.13417 [pdf]
    PoS(2022)·4 citations
  3. 09

    [Submitted on 26 Oct 2021] (cross-list from hep-lat)

    Machine learning spectral functions in lattice QCD

    S.-Y. Chen🇨🇳 · H.-T. Ding🇨🇳 · F.-Y. Liu🇨🇳 · G. Papp🇭🇺 · C.-B. Yang🇨🇳

    We study the inverse problem of reconstructing spectral functions from Euclidean correlation functions via machine learning. We propose a novel neural network, SVAE, which is based on the variational autoencoder (VAE) and can be naturally applied to the inverse problem. The prominent feature of the SVAE is that a Shannon-Jaynes entropy term having the ground truth values of spectral functions as prior information is included in the loss function to be minimized. We train the network with general spectral functions produced from a Gaussian mixture model. As a test, we use correlators generated from four different types of physically motivated spectral functions made of one resonance peak, a continuum term and perturbative spectral function obtained using non-relativistic QCD. From the mock data test we find that the SVAE in most cases is comparable to the maximum entropy method (MEM) in the quality of reconstructing spectral functions and even outperforms the MEM in the case where the spectral function has sharp peaks with insufficient number of data points in the correlator. By applying to temporal correlation functions of charmonium in the pseudoscalar channel obtained in the quenched lattice QCD at 0.75 on lattices and on lattices, we find that the resonance peak of extracted from both the SVAE and MEM has a substantial dependence on the number of points in the temporal direction () adopted in the lattice simulation and larger than 48 is needed to resolve the fate of at 1.5 .

    Comments:
    25 pages, 14 figures. Investigations on the dependences of output spectral functions on the noise model of mock correlators, and detailed derivation of formulae for the output spectral function are added
    Subjects:
    High Energy Physics — Lattice (hep-lat); Machine Learning (cs.LG); High Energy Physics — Phenomenology (hep-ph); High Energy Physics — Theory (hep-th); Nuclear Theory (nucl-th)
    arXiv:
    2110.13521 [pdf]
    34 citations
  4. 10

    [Submitted on 26 Oct 2021] (cross-list from astro-ph.HE)

    The Impact of the New As(p,)Se Reaction Rate on the Two-Proton Sequential Capture of Ge, Weak GeAs Cycles, and Type-I X-Ray Bursts such as the Clocked Burster GS 182624

    Yi Hua Lam · Zi Xin Liu · Alexander Heger · Ning Lu · Adam Michael Jacobs · Zac Johnston

    We re-assess As(p,)Se reaction rates based on a set of proton thresholds of Se, (Se), estimated from the experimental mirror nuclear masses, theoretical mirror displacement energies, and full -model space shell-model calculation. The self-consistent relativistic Hartree-Bogoliubov theory is employed to obtain the mirror displacement energies with much reduced uncertainty, and thus reducing the proton-threshold uncertainty up to 161 keV compared to the AME2020 evaluation. Using the simulation instantiated by the one-dimensional multi-zone hydrodynamic code, KEPLER, that closely reproduces the observed GS 182624 clocked bursts, the present forward and reverse As(p,)Se reaction rates based on a selected (Se) = 2.4690.054 MeV, and the latest Mg(,p)Al, Ni(p,)Cu(p,)Zn, Ni(p,)Cu, and Ge(p,)As reaction rates, we find that though the GeAs cycles is weakly established in the rapid-proton capture process path, the As(p,)Se reaction still strongly characterizes the burst tail end due to the two-proton sequential capture on Ge, not found by Cyburt et al. (2016) sensitivity study. The As(p,)Se reaction influences the abundances of nuclei = 64, 68, 72, 76, and 80 up to a factor of 1.4. The new (Se) and the inclusion of the updated Mg(,p)Al reaction rate increases the production of C up to a factor of that is not observable and could be the main fuel for superburst. The waiting point status of and two-proton sequential capture on Ge, weak-cycle feature of GeAs at region heavier than Ge, and impact of other possible (Se) are also discussed.

    Comments:
    25 pages, 19 figures, 3 tables, accepted by The Astrophysical Journal on 10 January 2022
    Subjects:
    High Energy Astrophysical Phenomena (astro-ph.HE); Nuclear Experiment (nucl-ex); Nuclear Theory (nucl-th)
    arXiv:
    2110.13676 [pdf]
    ApJ(2022)·17 citations
  5. 11

    [Submitted on 26 Oct 2021] (cross-list from hep-ph)

    Deep Learning Exotic Hadrons

    JPAC Collaboration: L. Ng🇺🇸 · L. Bibrzycki🇵🇱 · J. Nys🇨🇭 · C. Fernandez-Ramirez🇲🇽 · A. Pilloni🇮🇹 · V. Mathieu🇪🇸 · A.J. Rasmusson🇺🇸 · A.P. Szczepaniak🇺🇸

    We perform the first model independent analysis of experimental data using Deep Neural Networks to determine the nature of an exotic hadron. Specifically, we study the line shape of the signal reported by the LHCb collaboration and we find that its most likely interpretation is that of a virtual state. This method can be applied to other near-threshold resonance candidates.

    Comments:
    Manuscript: 5 pages, 5 figures, 1 table; Supplemental material: 7 pages, 7 figures, 1 table
    Subjects:
    High Energy Physics — Phenomenology (hep-ph); High Energy Physics — Experiment (hep-ex); Nuclear Theory (nucl-th)
    arXiv:
    2110.13742 [pdf]
    PRD(2022)·30 citations

Affiliations

first authorsco-authorsvia INSPIRE