Randomized low-rank decompositions of nuclear three-body interactions

被引:0
|
作者
Tichai, A. [1 ,2 ,3 ]
Arthuis, P. [1 ,2 ,4 ,5 ]
Hebeler, K. [1 ,2 ,3 ]
Heinz, M. [1 ,2 ,3 ,6 ]
Hoppe, J. [1 ,2 ]
Miyagi, T. [1 ,2 ,3 ,7 ]
Schwenk, A. [1 ,2 ,3 ]
Zurek, L. [8 ]
机构
[1] Tech Univ Darmstadt, Dept Phys, D-64289 Darmstadt, Germany
[2] GSI Helmholtzzentrum Schwerionenforsch GmbH, ExtreMe Matter Inst EMMI, D-64291 Darmstadt, Germany
[3] Max Planck Inst Kernphys, Saupfercheckweg 1, D-69117 Heidelberg, Germany
[4] GSI Helmholtzzentrum Schwerionenforsch GmbH, Helmholtz Forsch Akad Hessen FAIR HFHF, D-64291 Darmstadt, Germany
[5] Univ Paris Saclay, IJCLab, CNRS IN2P3, F-91405 Orsay, France
[6] Oak Ridge Natl Lab, Natl Ctr Computat Sci, Oak Ridge, TN 37830 USA
[7] Univ Tsukuba, Ctr Computat Sci, 1-1-1 Tennodai, Tsukuba, Ibaraki 3058577, Japan
[8] Univ Paris Saclay, CEA, Lab Matiere Condit Extremes, F-91680 Bruyeres Le Chatel, France
来源
PHYSICAL REVIEW RESEARCH | 2024年 / 6卷 / 04期
基金
欧洲研究理事会;
关键词
BODY PERTURBATION-THEORY; MATRIX RENORMALIZATION-GROUP; FORCES;
D O I
10.1103/PhysRevResearch.6.043331
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
First-principles simulations of many-fermion systems are commonly limited by the computational requirements of processing large data objects. As a remedy, we propose the use of low-rank approximations of three-body interactions, which are the dominant such limitation in nuclear physics. We introduce a randomized decomposition technique to handle the excessively large matrix dimensions and study the sensitivity of low-rank properties to interaction details. The developed low-rank three-nucleon interactions are benchmarked in ab initio simulations of few- and many-body systems. Exploiting low-rank properties provides a promising route to extend the microscopic description of atomic nuclei to large systems where storage requirements exceed the computational capacities of the most advanced high-performance computing facilities.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Low-rank matrix decompositions for ab initio nuclear structure
    Tichai, A.
    Arthuis, P.
    Hebeler, K.
    Heinz, M.
    Hoppe, J.
    Schwenk, A.
    PHYSICS LETTERS B, 2021, 821
  • [2] Compressed Randomized UTV Decompositions for Low-Rank Matrix Approximations
    Kaloorazi, Maboud F.
    de Lamare, Rodrigo C.
    IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2018, 12 (06) : 1155 - 1169
  • [3] Fast and Accurate Randomized Algorithms for Low-rank Tensor Decompositions
    Ma, Linjian
    Solomonik, Edgar
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 34 (NEURIPS 2021), 2021, 34
  • [4] Randomized Algorithms for Low-Rank Tensor Decompositions in the Tucker Format
    Minster, Rachel
    Saibaba, Arvind K.
    Kilmer, Misha E.
    SIAM JOURNAL ON MATHEMATICS OF DATA SCIENCE, 2020, 2 (01): : 189 - 215
  • [5] Low-rank revealing UTV decompositions
    Ricardo D. Fierro
    Per Christian Hansen
    Numerical Algorithms, 1997, 15 : 37 - 55
  • [6] Sparse and Low-Rank Matrix Decompositions
    Chandrasekaran, Venkat
    Sanghavi, Sujay
    Parrilo, Pablo A.
    Willsky, Alan S.
    2009 47TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING, VOLS 1 AND 2, 2009, : 962 - +
  • [7] Low-rank revealing UTV decompositions
    Fierro, RD
    Hansen, PC
    NUMERICAL ALGORITHMS, 1997, 15 (01) : 37 - 55
  • [8] COMPRESSED RANDOMIZED UTV DECOMPOSITIONS FOR LOW-RANK MATRIX APPROXIMATIONS IN DATA SCIENCE
    Kaloorazi, Maboud F.
    de Lamare, Rodrigo C.
    2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2019, : 7510 - 7514
  • [9] Accelerated Low-rank Updates to Tensor Decompositions
    Baskaran, Muthu
    Langston, M. Harper
    Ramananandro, Tahina
    Bruns-Smith, David
    Henretty, Tom
    Ezick, James
    Lethin, Richard
    2016 IEEE HIGH PERFORMANCE EXTREME COMPUTING CONFERENCE (HPEC), 2016,
  • [10] Three-body nuclear interactions in the QCD sum rules
    Drukarev E.G.
    Ryskin M.G.
    Sadovnikova V.A.
    Sadovnikova, V.A. (sadovnik@thd.pnpi.spb.ru), 1600, Allerton Press Incorporation (81): : 1192 - 1195