Search Results for author: Puhan Zhang

Found 7 papers, 1 papers with code

Machine learning predictions for local electronic properties of disordered correlated electron systems

no code implementations12 Apr 2022 Yi-Hsuan Liu, Sheng Zhang, Puhan Zhang, Ting-Kuo Lee, Gia-Wei Chern

We present a scalable machine learning (ML) model to predict local electronic properties such as on-site electron number and double occupation for disordered correlated electron systems.

BIG-bench Machine Learning Variational Monte Carlo

Descriptors for Machine Learning Model of Generalized Force Field in Condensed Matter Systems

no code implementations3 Jan 2022 Puhan Zhang, Sheng Zhang, Gia-Wei Chern

A general theory of the descriptor for the classical fields is formulated, and two types of models are distinguished depending on the presence or absence of an internal symmetry for the classical field.

BIG-bench Machine Learning

Machine learning nonequilibrium electron forces for adiabatic spin dynamics

no code implementations22 Dec 2021 Puhan Zhang, Gia-Wei Chern

We present a generalized potential theory of nonequilibrium torques for the Landau-Lifshitz equation.

BIG-bench Machine Learning

Anomalous phase separation dynamics in a correlated electron system: machine-learning enabled large-scale kinetic Monte Carlo simulations

no code implementations27 May 2021 Sheng Zhang, Puhan Zhang, Gia-Wei Chern

With the aid of modern machine learning methods, we demonstrate the first-ever large-scale kinetic Monte Carlo simulations of the phase separation process for the Falicov-Kimball model, which is one of the canonical strongly correlated electron systems.

BIG-bench Machine Learning

Arrested phase separation in double-exchange models: machine-learning enabled large-scale simulation

2 code implementations18 May 2021 Puhan Zhang, Gia-Wei Chern

We present large-scale dynamical simulations of electronic phase separation in the single-band double-exchange model based on deep-learning neural-network potentials trained from small-size exact diagonalization solutions.

BIG-bench Machine Learning

Machine learning dynamics of phase separation in correlated electron magnets

no code implementations7 Jun 2020 Puhan Zhang, Preetha Saha, Gia-Wei Chern

We demonstrate machine-learning enabled large-scale dynamical simulations of electronic phase separation in double-exchange system.

BIG-bench Machine Learning

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