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2022 Fiscal Year Annual Research Report

Ab initio nuclear Density Functional Theory with uncertainty quantification from Functional Renormalization Group in Kohn-Sham scheme

Research Project

Project/Area Number 18K13549
Research InstitutionThe University of Tokyo

Principal Investigator

LIANG HAOZHAO  東京大学, 大学院理学系研究科(理学部), 准教授 (50729225)

Project Period (FY) 2018-04-01 – 2023-03-31
Keywords原子核密度汎関数理論 / 汎関数繰り込み群法
Outline of Annual Research Achievements

For the development of ab initio nuclear Density Functional Theory (DFT) from the Functional Renormalization Group (FRG) method, we started from the key strategies demonstrated by using the zero-dimensional phi^4 theory [Phys. Lett. B 779, 436 (2018)], to the application to the (1+1)-dimensional nuclear systems [master thesis by Hikaru Sakakibara (U. Tokyo)], to the application to the (3+1)-dimensional electron gas. At this stage, we are finalizing the formalism and numerical codes of the energy density functional (EDF) with the generalized gradient approximation.
In parallel, we have been investigating several other possible strategies for developing the ab initio nuclear DFT. This includes (i) the combination of the inverse Kohn-Sham method and the density functional perturbation theory [J. Phys. B 52, 245003 (2019)], (ii) the covariant ab initio calculations and the constraints on tensor force [Phys. Rev. C 97, 054312 (2018)], (iii) a series of studies on the ab initio charge symmetry breaking in nuclear EDF [Phys. Rev. C 105, L021304 (2022)], and (iv) the latest studies with the combinations of nuclear DFT, the Kohn-Sham scheme, and machine learning approaches [Phys. Lett. B 840, 137870 (2023); Phys. Rev. C 106, 024306 (2022); Phys. Rev. C 106, L021303 (2022)].
During the whole research period, we have published 28 peer-refereed papers, including 1 invited review in Progress in Particle and Nuclear Physics entitled “Towards an ab initio covariant density functional theory for nuclear structure”, presenting our ideas on ab initio nuclear DFT for the coming decade.

  • Research Products

    (12 results)

All 2023 2022 Other

All Int'l Joint Research (2 results) Journal Article (6 results) (of which Int'l Joint Research: 4 results,  Peer Reviewed: 6 results,  Open Access: 6 results) Presentation (4 results) (of which Int'l Joint Research: 2 results,  Invited: 3 results)

  • [Int'l Joint Research] Anhui University/Southwest University/Institute of Modern Physics, CAS(中国)

    • Country Name
      CHINA
    • Counterpart Institution
      Anhui University/Southwest University/Institute of Modern Physics, CAS
    • # of Other Institutions
      1
  • [Int'l Joint Research] Iowa State University(米国)

    • Country Name
      U.S.A.
    • Counterpart Institution
      Iowa State University
  • [Journal Article] A Kohn-Sham scheme based neural network for nuclear systems2023

    • Author(s)
      Yang Zu-Xing、Fan Xiao-Hua、Li Zhi-Pan、Liang Haozhao
    • Journal Title

      Physics Letters B

      Volume: 840 Pages: 137870

    • DOI

      10.1016/j.physletb.2023.137870

    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] A local-density-approximation description of high-momentum tails in isospin asymmetric nuclei2022

    • Author(s)
      Fan Xiao-Hua、Yang Zu-Xing、Yin Peng、Chen Peng-Hui、Dong Jian-Min、Li Zhi-Pan、Liang Haozhao
    • Journal Title

      Physics Letters B

      Volume: 834 Pages: 137482

    • DOI

      10.1016/j.physletb.2022.137482

    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Role of the effective range in the density-induced BEC-BCS crossover2022

    • Author(s)
      Tajima Hiroyuki、Liang Haozhao
    • Journal Title

      Physical Review A

      Volume: 106 Pages: 043308

    • DOI

      10.1103/PhysRevA.106.043308

    • Peer Reviewed / Open Access
  • [Journal Article] Calculation of beta-decay half-lives within a Skyrme-Hartree-Fock-Bogoliubov energy density functional with the proton-neutron quasiparticle random-phase approximation and isoscalar pairing strengths optimized by a Bayesian method2022

    • Author(s)
      Minato Futoshi、Niu Zhongming、Liang Haozhao
    • Journal Title

      Physical Review C

      Volume: 106 Pages: 024306

    • DOI

      10.1103/PhysRevC.106.024306

    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Nuclear mass predictions with machine learning reaching the accuracy required by r-process studies2022

    • Author(s)
      Niu Z. M.、Liang H. Z.
    • Journal Title

      Physical Review C

      Volume: 106 Pages: L021303

    • DOI

      10.1103/PhysRevC.106.L021303

    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Biexciton-like quartet condensates in an electron-hole liquid2022

    • Author(s)
      Guo Yixin、Tajima Hiroyuki、Liang Haozhao
    • Journal Title

      Physical Review Research

      Volume: 4 Pages: 023152

    • DOI

      10.1103/PhysRevResearch.4.023152

    • Peer Reviewed / Open Access
  • [Presentation] Exotic nuclear physics for astrophysics2022

    • Author(s)
      Liang Haozhao
    • Organizer
      International Workshop on Origin of Elements and Cosmic Evolution: From Big-Bang to Supernovae and Mergers
    • Int'l Joint Research / Invited
  • [Presentation] Towards ab initio Nuclear Density functional Theory2022

    • Author(s)
      Liang Haozhao
    • Organizer
      Summer School on Exotic Nuclei
    • Int'l Joint Research / Invited
  • [Presentation] Nuclear mass predictions with machine learning reaching the accuracy required by r-process studies2022

    • Author(s)
      Liang Haozhao
    • Organizer
      Workshop on combining nuclear theory and machine learning for fundamental studies and applications
  • [Presentation] Quantum computing for nuclear structure properties?2022

    • Author(s)
      Liang Haozhao
    • Organizer
      Workshop “Fundamentals in density functional theory”
    • Invited

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Published: 2023-12-25  

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