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Nuclear Theory·nucl-th

Monday·October 11, 2021

11 papers—3 primary·8 cross-listed

All11Primary3Cross-lists8
  1. 01

    [Submitted on 8 Oct 2021]

    Evidence of a higher nodal band +Ca cluster state in fusion reactions and clustering in Ti

    S. Ohkubo

    In the nucleus Ti, whose structure is essential in evaluating the half-life of the neutrinoless double- decay () of Ca, the existence of the cluster structure is shown for the first time. A unified description of scattering and structure is performed for the +Ca system. By using a global potential, which reproduces experimental +Ca scattering over a wide range of incident energies, =18 - 100 MeV, it is shown that the observed +Ca fusion excitation function at =9 -18 MeV is described well. The bump at =10.2 MeV is found to be due to a resonance which is a state of the higher nodal band with the +Ca cluster structure in Ti. The local potential +Ca cluster model locates the ground band of Ti in agreement with experiment and reproduces the enhanced values in the ground band well. This shows that collectivity due to clustering in Ti should be taken into account in the evaluation of the nuclear matrix element in the double- decay of Ca.

    Comments:
    6 pages, 6 figures
    Subjects:
    Nuclear Theory (nucl-th); Nuclear Experiment (nucl-ex)
    arXiv:
    2110.03928 [pdf]
    PRC(2021)·1 citation
  2. 02

    [Submitted on 8 Oct 2021]

    Bayesian parameter estimation in EFT using Hamiltonian Monte Carlo

    Isak Svensson🇸🇪 · Andreas Ekström🇸🇪 · Christian Forssén🇸🇪

    The number of low-energy constants (LECs) in chiral effective field theory (EFT) grows rapidly with increasing chiral order, necessitating the use of Markov chain Monte Carlo techniques for sampling their posterior probability density function. For this we introduce a Hamiltonian Monte Carlo (HMC) algorithm and sample the LEC posterior up to next-to-next-to-leading order (NNLO) in the two-nucleon sector of EFT. We find that the sampling efficiency of HMC is three to six times higher compared to an affine-invariant sampling algorithm. We analyze the empirical coverage probability and validate that the NNLO model yields predictions for two-nucleon scattering data with largely reliable credible intervals, provided that one ignores the leading order EFT expansion parameter when inferring the variance of the truncation error. We also find that the NNLO truncation error dominates the error budget.

    Comments:
    22 pages, 12 figures
    Subjects:
    Nuclear Theory (nucl-th)
    arXiv:
    2110.04011 [pdf]
    PRC(2022)·24 citations
  3. 03

    [Submitted on 8 Oct 2021]

    Fast emulation of quantum three-body scattering

    Xilin Zhang🇺🇸 · R.J. Furnstahl🇺🇸

    We develop a class of emulators for solving quantum three-body scattering problems. They are based on combining the variational method for scattering observables and the recently proposed eigenvector continuation concept. The emulators are first trained by the exact scattering solutions of the governing Hamiltonian at a small number of points in its parameter space, and then employed to make interpolations and extrapolations in that space. Through a schematic nuclear-physics model with finite-range two and three-body interactions, we demonstrate the emulators to be extremely accurate and efficient. The computing time for emulation is on the scale of milliseconds (on a laptop), with relative errors ranging from to depending on the case. The emulators also require little memory. We argue that these emulators can be generalized to even more challenging scattering problems. Furthermore, this general strategy may be applicable for building the same type of emulators in other fields, wherever variational methods can be developed for evaluating physical models.

    Comments:
    21 pages, 15 figures, and 10-page supplemental material
    Subjects:
    Nuclear Theory (nucl-th); High Energy Physics — Lattice (hep-lat); Atomic Physics (physics.atom-ph); Computational Physics (physics.comp-ph); Data Analysis, Statistics and Probability (physics.data-an)
    arXiv:
    2110.04269 [pdf]
    PRC(2022)·45 citations

Affiliations

first authorsco-authorsvia INSPIRE