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Title: Active learning approach to simulations of strongly correlated matter with the ghost Gutzwiller approximation

Journal Article · · Physical Review Research
ORCiD logo [1]; ORCiD logo [2];  [3]; ORCiD logo [4];  [5];  [1]; ORCiD logo [6]
  1. Aarhus Univ. (Denmark)
  2. Freie Univ., Berlin (Germany)
  3. National Chung Cheng Univ., Chiayi (Taiwan)
  4. Ames Laboratory (AMES), Ames, IA (United States); Iowa State Univ., Ames, IA (United States)
  5. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
  6. Rochester Inst. of Technology, Rochester, NY (United States); Flatiron Institute, New York, NY (United States)

Quantum embedding (QE) methods such as the ghost Gutzwiller approximation (gGA) offer a powerful approach to simulating strongly correlated systems, but come with the computational bottleneck of computing the ground state of an auxiliary embedding Hamiltonian (EH) iteratively. In this work, we introduce an active learning (AL) framework integrated within the gGA to address this challenge. The methodology is applied to the single-band Hubbard model and results in a significant reduction in the number of instances where the EH must be solved. Through a principal component analysis (PCA), we find that the EH parameters form a low-dimensional structure that is largely independent of the geometric specifics of the systems, especially in the strongly correlated regime. Our AL strategy enables us to discover this low-dimensionality structure on the fly, while leveraging it for reducing the computational cost of gGA, laying the groundwork for more efficient simulations of complex strongly correlated materials.

Research Organization:
Ames Laboratory (AMES), Ames, IA (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE); USDOE Laboratory Directed Research and Development (LDRD) Program; Simons Foundation; USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC02-07CH11358; 1030691; 89233218CNA000001
OSTI ID:
2318741
Alternate ID(s):
OSTI ID: 2323283; OSTI ID: 2406639
Report Number(s):
IS-J-11,280; LA-UR-23-33381; TRN: US2409648
Journal Information:
Physical Review Research, Vol. 6, Issue 1; ISSN 2643-1564
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English

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