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Title: Large-scale exact diagonalizations reveal low-momentum scales of nuclei

Journal Article · · Physical Review C
 [1];  [1];  [1];  [1];  [2];  [2];  [2]
  1. Chalmers Univ. of Technology, Göteborg (Sweden). Dept. of Physics
  2. Univ. of Tennessee, Knoxville, TN (United States). Dept. of Physics and Astronomy; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Physics Division

Ab initio methods aim to solve the nuclear many-body problem with controlled approximations. Virtually exact numerical solutions for realistic interactions can only be obtained for certain special cases such as few-nucleon systems. In this paper, we extend the reach of exact diagonalization methods to handle model spaces with dimension exceeding $${10}^{10}$$ on a single compute node. This allows us to perform no-core shell model (NCSM) calculations for $$^{6}\mathrm{Li}$$ in model spaces up to $${N}_{\mathrm{max}}=22$$ and to reveal the $$^{4}\mathrm{He}$$+d halo structure of this nucleus. Still, the use of a finite harmonic-oscillator basis implies truncations in both infrared (IR) and ultraviolet (UV) length scales. These truncations impose finite-size corrections on observables computed in this basis. We perform IR extrapolations of energies and radii computed in the NCSM and with the coupled-cluster method at several fixed UV cutoffs. It is shown that this strategy enables information gain also from data that is not fully UV converged. IR extrapolations improve the accuracy of relevant bound-state observables for a range of UV cutoffs, thus making them profitable tools. We relate the momentum scale that governs the exponential IR convergence to the threshold energy for the first open decay channel. Finally, using large-scale NCSM calculations we numerically verify this small-momentum scale of finite nuclei.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States); Chalmers Univ. of Technology, Göteborg (Sweden)
Sponsoring Organization:
USDOE Office of Science (SC), Nuclear Physics (NP); Swedish Foundation for International Cooperation in Research and Higher Education (STINT)
Grant/Contract Number:
AC05-00OR22725; FG02-96ER40963; SC0008499; SC0018223; IG2012-5158
OSTI ID:
1471876
Alternate ID(s):
OSTI ID: 1430150
Journal Information:
Physical Review C, Vol. 97, Issue 3; ISSN 2469-9985
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 32 works
Citation information provided by
Web of Science

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Cited By (3)

Deep learning: Extrapolation tool for ab initio nuclear theory journal May 2019
Simulations of Subatomic Many-Body Physics on a Quantum Frequency Processor text January 2018
Deep learning: Extrapolation tool for ab initio nuclear theory text January 2018

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