Optimizing Jastrow factors for the transcorrelated method

被引:12
|
作者
Haupt, J. Philip [1 ]
Hosseini, Seyed Mohammadreza [1 ]
Rios, Pablo Lopez [1 ]
Dobrautz, Werner [2 ]
Cohen, Aron [3 ]
Alavi, Ali [1 ,2 ,4 ]
机构
[1] Max Planck Inst Solid State Res, Heisenbergstr 1, D-70569 Stuttgart, Germany
[2] Chalmers Univ Technol, Dept Chem & Chem Engn, S-41296 Gothenburg, Sweden
[3] DeepMind 6 Pancras Sq, London N1C 4AG, England
[4] Univ Cambridge, Yusuf Hamied Dept Chem, Lensfield Rd, Cambridge CB2 1EW, England
基金
欧盟地平线“2020”;
关键词
BATH CONFIGURATION-INTERACTION; WAVE-FUNCTIONS; CORRELATION CUSP; ENERGIES; TERMS; CARE; MINIMIZATION; VARIANCE; SYSTEMS; NEON;
D O I
10.1063/5.0147877
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
We investigate the optimization of flexible tailored real-space Jastrow factors for use in the transcorrelated (TC) method in combination with highly accurate quantum chemistry methods, such as initiator full configuration interaction quantum Monte Carlo (FCIQMC). Jastrow factors obtained by minimizing the variance of the TC reference energy are found to yield better, more consistent results than those obtained by minimizing the variational energy. We compute all-electron atomization energies for the challenging first-row molecules C-2, CN, N-2, and O-2 and find that the TC method yields chemically accurate results using only the cc-pVTZ basis set, roughly matching the accuracy of non-TC calculations with the much larger cc-pV5Z basis set. We also investigate an approximation in which pure three-body excitations are neglected from the TC-FCIQMC dynamics, saving storage and computational costs, and show that it affects relative energies negligibly. Our results demonstrate that the combination of tailored real-space Jastrow factors with the multi-configurational TC-FCIQMC method provides a route to obtaining chemical accuracy using modest basis sets, obviating the need for basis-set extrapolation and composite techniques.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] A method for optimizing waste collection using mathematical programming: a Buenos Aires case study
    Bonomo, Flavio
    Duran, Guillermo
    Larumbe, Frederico
    Marenco, Javier
    WASTE MANAGEMENT & RESEARCH, 2012, 30 (03) : 311 - 324
  • [32] Optimizing String Method's Reproducibility Using Generalized Solute Tempering Replica Exchange
    Shrivastav, Gourav
    Abrams, Cameron F.
    JOURNAL OF PHYSICAL CHEMISTRY B, 2021, 125 (24) : 6609 - 6616
  • [33] An accelerated linear method for optimizing non-linear wavefunctions in variational Monte Carlo
    Sabzevari, Iliya
    Mahajan, Ankit
    Sharma, Sandeep
    JOURNAL OF CHEMICAL PHYSICS, 2020, 152 (02)
  • [34] A Rapid Method for Optimizing Running Temperature of Electrophoresis through Repetitive On-Chip CE Operations
    Kaneda, Shohei
    Ono, Koichi
    Fukuba, Tatsuhiro
    Nojima, Takahiko
    Yamamoto, Takatoki
    Fujii, Teruo
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2011, 12 (07): : 4271 - 4281
  • [35] Enhancing sustainability in irrigation networks: A multicriteria method for optimizing flow distribution and reducing environmental impact
    Garcia-Espinal, Melvin Alfonso
    Sanchez-Romero, Francisco-Javier
    Sanchez, Modesto Perez -
    Lopez-Jimenez, P. Amparo
    RESULTS IN ENGINEERING, 2024, 23
  • [36] Efficiency in public transportation: a new flow direction method for optimizing multi-route networks
    Akgol, Kadir
    Demir, Emre
    Aydogdu, Ibrahim
    Murat, Yetis Sazi
    TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH, 2024,
  • [37] OPTIMIZING ROCK FRAGMENTATION IN OPEN-PIT MINES THROUGH FUZZY INTELLIGENT PREDICTION METHOD
    Masoumi, Isa
    Zabihi, Behrooz
    Masoumi, Shiba
    MINING SCIENCE, 2024, 31 : 21 - 38
  • [38] The Key Factors of an Active Learning Method in a Microprocessors Course
    Carpeno, Antonio
    Arriaga, Jesus
    Corredor, Javier
    Hernandez, Javier
    IEEE TRANSACTIONS ON EDUCATION, 2011, 54 (02) : 229 - 235
  • [39] Weak Factors Identification Method for Renewable Energy Accommodation
    Huang, Zonghong
    Wen, Shiyang
    Yan, Zhibin
    Dai, Wei
    Ge, Pengjiang
    Yu, Juan
    2020 5TH ASIA CONFERENCE ON POWER AND ELECTRICAL ENGINEERING (ACPEE 2020), 2020, : 2066 - 2070
  • [40] An intelligent diagnostic method based on optimizing B-cell pool clonal selection classification algorithm
    Lan, Chao
    Zhang, Hongli
    Sun, Xin
    Ren, Zhongyuan
    TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2020, 28 (06) : 3270 - 3284