273 citations · 1.6k across the 86 of their papers we have counts for
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Self-learning Monte Carlo with equivariant Transformer
Yuki Nagai, Akio Tomiya
Machine learning and deep learning have revolutionized computational physics, particularly the simulation of complex systems. Equivariance is essential for simulating physical syst…
Sparse modeling of large-scale quantum impurity models with low symmetries
Hiroshi Shinaoka, Yuki Nagai
Quantum embedding theories provide a feasible route for obtaining quantitative descriptions of correlated materials. However, a critical challenge is solving an effective impurity…
Self-learning Monte Carlo method with Behler-Parrinello neural networks
Yuki Nagai, Masahiko Okumura, Akinori Tanaka
We propose a general way to construct an effective Hamiltonian in the Self-learning Monte Carlo method (SLMC), which speeds up Monte Carlo simulations by training an effective mode…
Smooth self-energy in the exact-diagonalization-based dynamical mean-field theory: Intermediate-representation filtering approach
Yuki Nagai, Hiroshi Shinaoka
We propose a method for estimating smooth real-frequency self-energy in the dynamical mean-field theory with the finite-temperature exact diagonalization (DMFT-ED). One of the bene…
Self-Learning Monte Carlo Method: Continuous-Time Algorithm
Yuki Nagai, Huitao Shen, Yang Qi +2
The recently-introduced self-learning Monte Carlo method is a general-purpose numerical method that speeds up Monte Carlo simulations by training an effective model to propose unco…