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JAEA Reports

Report of nuclear data roadmap 2023

Nakayama, Shinsuke

JAEA-Review 2024-009, 16 Pages, 2024/05

JAEA-Review-2024-009.pdf:1.17MB

Nuclear data is fundamental data for nuclear energy research and development, and its importance has been widely recognized. On the other hand, for future nuclear data research, it is necessary to sort out which types of data (target nuclides, energies, physical quantities, etc.) should be prioritized. Therefore, a "Task Force (TF) for Nuclear Data Roadmap" was established within Investigation Committee on Nuclear Data in the Atomic Energy Society of Japan to discuss a roadmap for future nuclear data research and development. This document reports the results of the discussion in the TF.

JAEA Reports

Proceedings of the 2020 Symposium on Nuclear Data; November 26-27, 2020, RIKEN Nishina Center, RIKEN Wako Campus, Wako, Saitama, Japan

Imai, Nobuaki*; Otsu, Hideaki*

JAEA-Conf 2021-001, 236 Pages, 2022/03

JAEA-Conf-2021-001.pdf:48.06MB

The 2020 Symposium on Nuclear Data was held on-site at RIBF Conference Hall in RIKEN Wako campus on November 26 to 27, 2020, combined with on-line connection conference. The symposium was organized by the Nuclear Data Division of the Atomic Energy Society of Japan (AESJ) in cooperation with Sigma Investigative Advisory Committee of AESJ, Nuclear Science and Engineering Center of Japan Atomic Energy Agency (JAEA), RIKEN Nishina Center, Center for Nuclear Study, The University of Tokyo (CNS), KEK Wako Nuclear Science Center (WNSC), School of Science, The University of Tokyo. In the symposium, six sessions were proposed and held: "Reactor theory and experiments" as a tutorial, "Accelerator Facilities and Nuclear Data", "Deep/Machine Learning and Nuclear Physics, Application to Nuclear Data", "Nuclear Medicine and Nuclear Pharmacy", "Fission, Heavy Ion Nuclear Spectroscopy", and "Nuclear Reaction Data" as lecture and discussion sessions. In addition, recent research progress on experiments, nuclear theory, evaluation, benchmark and applications were presented in the poster session. The total number of participants was 119, of which 62 were on-site participants. Each oral and poster presentation was followed by an active question and answer session. This report consists of total 40 papers including 15 oral and 25 poster presentations.

JAEA Reports

JAEA-Tokai tandem annual report 2013; April 1, 2013 - March 31, 2014

Department of Research Reactor and Tandem Accelerator

JAEA-Review 2016-025, 101 Pages, 2016/12

JAEA-Review-2016-025.pdf:7.86MB

The JAEA-Tokai tandem accelerator complex has been used in various research fields such as nuclear science and material science by researchers not only of JAEA but also from universities, research institutes and industrial companies. This annual report covers developments of accelerators and research activities carried out using the tandem accelerator and superconducting booster from April 1, 2013 to March 31, 2014. Thirty-one summary reports were categorized into seven research/development fields:(1) accelerator operation and development, (2) nuclear structure, (3) nuclear reaction, (4) nuclear chemistry, (5) nuclear theory, (6) atomic physics and solid state physics (7) radiation effects in materials. This report also lists publications, meetings, personnel, committee members, cooperative researches and common use programs.

Journal Articles

GPGPU application to the computation of Hamiltonian matrix elements between non-orthogonal Slater determinants in the Monte Carlo shell model

Togashi, Tomoaki*; Shimizu, Noritaka*; Utsuno, Yutaka; Abe, Takashi*; Otsuka, Takaharu*

Procedia Computer Science, 29, p.1711 - 1721, 2014/06

https://doi.org/10.1016/j.procs.2014.05.156

Times Cited Count：1 Percentile：29.84(Computer Science, Theory & Methods)

Computing Hamiltonian matrix elements between non-orthogonal Slater determinants is often needed for nuclear-structure calculations, and it is the most time-consuming part in many cases. In this paper, we demonstrate that utilizing GPGPU is an efficient way to perform this calculation. In our earlier study, we showed that the calculation of the Hamiltonian matrix elements between non-orthogonal Slater determinants is transformed into the multiplication of matrices. This method is useful for the GPGPU calculation because of less memory access compared to the usual method. We implement the GPGPU computation in the Monte Carlo shell-model code and measure the elapsed time. The resulting performance is over 0.6 TFLOPS for the GPU that has 1.13 TFLOPS peak performance. This method is particularly effective for large-scale calculations because higher efficiency is obtained for the calculation of larger model spaces.

Journal Articles