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Nuclear Theory·nucl-th

Wednesday·February 10, 2021

3 papers—2 primary·1 cross-listed

All3Primary2Cross-lists1
  1. 01

    [Submitted on 9 Feb 2021]

    Two Li clusters connected with two valence neutrons in C

    Naoyuki Itagaki · Tokuro Fukui · Junki Tanaka · Yuma Kikuchi

    Many preceding works have shown in Li the presence of the halo structure comprised of the weakly bound two neutrons around Li, and it is intriguing to see how this halo structure changes when another Li approaches. In this study, we introduce a four-body model for C with two Li clusters and two valence neutrons. The recent development of the antisymmetrized quasi cluster model (AQCM) makes it possible to generate -coupling shell-model wave functions from cluster models. Here, -coupling shell model wave function of Li is regarded as a cluster, which corresponds to the subclosure configuration of for the neutrons, and we discuss how the two neutrons connect two Li clusters. Until now, most of the clusters in the conventional models have been limited to the closures of the three-dimensional harmonic oscillators, such as He, O, and Ca; however, owing to AQCM, it is feasible to utilize the -coupling shell model wave functions as plural subsystems quite easily. The appearance of a rotational band structure with a cluster structure around the four-body threshold energy is discussed.

    Comments:
    arXiv admin note: text overlap with arXiv:2011.12642
    Subjects:
    Nuclear Theory (nucl-th); Nuclear Experiment (nucl-ex)
    arXiv:
    2102.04589 [pdf]
    0 citations
  2. 02

    [Submitted on 9 Feb 2021]

    Quadrupole-octupole coupling and the onset of octupole deformation in actinides

    K. Nomura🇭🇷 · R. Rodríguez-Guzmán🇰🇼 · L. M. Robledo🇪🇸 · J. E. García-Ramos🇪🇸

    The evolution of quadrupole and octupole collectivity and their coupling is investigated in a series of even-even isotopes of the actinide Ra, Th, U, Pu, Cm, and Cf with neutron number in the interval . The Hartree-Fock-Bogoliubov approximation, based on the parametrization D1M of the Gogny energy density functional, is employed to generate potential energy surfaces depending upon the axially-symmetric quadrupole and octupole shape degrees of freedom. The mean-field energy surface is then mapped onto the expectation value of the interacting-boson-model Hamiltonian in the boson condensate state as to determine the strength parameters of the boson Hamiltonian. Spectroscopic properties related to the octupole degree of freedom are produced by diagonalizing the mapped Hamiltonian. Calculated low-energy negative-parity spectra, reduced transition rates, and effective octupole deformation suggest that the transition from nearly spherical to stable octupole-deformed, and to octupole vibrational states occurs systematically in the actinide region.

    Comments:
    12 pages, 12 figures
    Subjects:
    Nuclear Theory (nucl-th); Nuclear Experiment (nucl-ex)
    arXiv:
    2102.04641 [pdf]
    PRC(2021)·31 citations
  3. 03

    [Submitted on 9 Feb 2021] (cross-list from quant-ph)

    Morphology of three-body quantum states from machine learning

    David Huber · Oleksandr V. Marchukov · Hans-Werner Hammer · Artem G. Volosniev

    The relative motion of three impenetrable particles on a ring, in our case two identical fermions and one impurity, is isomorphic to a triangular quantum billiard. Depending on the ratio of the impurity and fermion masses, the billiards can be integrable or non-integrable (also referred to in the main text as chaotic). To set the stage, we first investigate the energy level distributions of the billiards as a function of and find no evidence of integrable cases beyond the limiting values and . Then, we use machine learning tools to analyze properties of probability distributions of individual quantum states. We find that convolutional neural networks can correctly classify integrable and non-integrable states.The decisive features of the wave functions are the normalization and a large number of zero elements, corresponding to the existence of a nodal line. The network achieves typical accuracies of 97%, suggesting that machine learning tools can be used to analyze and classify the morphology of probability densities obtained in theory or experiment.

    Comments:
    version accepted for publication in New Journal of Physics (Focus Issue on Machine Learning Across Physics)
    Subjects:
    Quantum Physics (quant-ph); Quantum Gases (cond-mat.quant-gas); nlin.SI (nlin.SI); Nuclear Theory (nucl-th)
    arXiv:
    2102.04961 [pdf]
    New J.Phys.(2021)·7 citations

Affiliations

first authorsco-authorsvia INSPIRE