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Ab initio calculations for dark matter detection and CEvNS

ORAL

Abstract

Over the past decades, ab initio nuclear calculation has made dramatic progress, especially reaching the heavy mass region as 208Pb [1]. This means that it becomes possible to obtain first-principles computation (with quantified uncertainties) of quantities which even reside in the heavy-mass region. The quantities include these relevant to astrophysics and searches for physics beyond the Standard Model. In this talk, I will present a conceptual introduction to modern ab initio theory. Then, I will focus on recent advances in ab initio calculations of nuclear responses for dark matter (DM) direct detection [2] and coherent elastic neutrino-nucleus scattering (CEvNS), including nuclei 19F, 23Na, 27Al, 28-30Si, 70,72-74,76Ge, 127I, 133Cs, and 128-132,134,136Xe.

[1]. Ab initio predictions link the neutron skin of 208Pb to nuclear forces. B.S. Hu, W.G. Jiang, T. Miyagi, Z.H, Sun, et al. Nat. Phys. 118, 1196 (2022) arXiv:2112.01125v1.

[2]. Ab initio structure factors for spin-dependent dark matter direct detection. B.S. Hu, et al. Phys. Rev. Lett. 128, 072502 (2022). arXiv:2109.00193.

* This work was supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, under Award No. DE-FG02-96ER40963 and by SciDAC-5 (NUCLEI collaboration). Computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) programme. This research used resources of the Oak Ridge Leadership Computing Facility located at Oak Ridge National Laboratory, which is supported by the Office of Science of the Department of Energy under contract No. DE-AC05-00OR22725.

Publication: [1]. Ab initio predictions link the neutron skin of 208Pb to nuclear forces. B.S. Hu, W.G. Jiang, T. Miyagi, Z.H, Sun, et al. Nat. Phys. 118, 1196 (2022) arXiv:2112.01125v1.
[2]. Ab initio structure factors for spin-dependent dark matter direct detection. B.S. Hu, et al. Phys. Rev. Lett. 128, 072502 (2022). arXiv:2109.00193.

Presenters

  • Baishan Hu

    Oak Ridge National Lab

Authors

  • Baishan Hu

    Oak Ridge National Lab