From the 1 of 15 linked papers with an AI index.
15 papers
AutoHF: a general Hartree-Fock solver utilizing direct energy minimization with automatic differentiation
Ryan Levy, Brandon Eskridge, Lukas Weber +2
The paper introduces AutoHF, a general-purpose Hartree‑Fock solver that finds the optimal Slater determinant for quantum many‑fermion Hamiltonians by directly minimizing the variat…
Removing nodal and support-mismatch pathologies in Variational Monte Carlo via blurred sampling
Zhou-Quan Wan, Roeland Wiersema, Shiwei Zhang
Variational Monte Carlo (VMC) is a powerful and fast-growing method for optimizing and evolving parameterized many-body wave functions, especially with modern neural-network quantu…
Neural Network Discovery of Paired Wigner Crystals in Artificial Graphene
Conor Smith, Yubo Yang, Zhou-Quan Wan +3
Moiré systems have emerged as an exciting tunable platform for engineering and probing quantum matter. A large number of exotic states have been observed, stimulating intense effo…
Re-anchoring Quantum Monte Carlo with Tensor-Train Sketching
Ziang Yu, Shiwei Zhang, Yuehaw Khoo
We propose a novel algorithm for calculating the ground-state energy of quantum many-body systems by combining auxiliary-field quantum Monte Carlo (AFQMC) with tensor-train sketchi…
Engineering Hubbard models with gated two-dimensional moiré systems
Yiqi Yang, Yubo Yang, Miguel A. Morales +1
Lattice models are powerful tools for studying strongly correlated quantum many-body systems, but their general lack of exact solutions motivates efforts to simulate them in tunabl…
Addressing the Infinite Variance Problem in Fermionic Monte Carlo Simulations: Retrospective Error Remediation and the Exact Bridge Link Method
Zhou-Quan Wan, Shiwei Zhang
We revisit the infinite variance problem in fermionic Monte Carlo simulations, which is widely encountered in areas ranging from condensed matter to nuclear and high-energy physics…