6 papers
Neural Network Representation of Generalized Parton Distributions (NNGPD)
Jitao Xu, Ho Jang, Zaki Panjsheeri +10
We present a neural-network-based framework for modeling generalized parton distributions, referred to as NNGPD, in which GPDs are represented as flexible functions constrained thr…
Suppressed coarsening after an interaction quench in the Holstein chain
Ho Jang, Gia-Wei Chern
We investigate the nonequilibrium dynamics induced by an interaction quench in the semiclassical Holstein model within the Ehrenfest nonadiabatic framework, which describes an isol…
Transformer Learning of Chaotic Collective Dynamics in Many-Body Systems
Ho Jang, Gia-Wei Chern
Learning reduced descriptions of chaotic many-body dynamics is fundamentally challenging: although microscopic equations are Markovian, collective observables exhibit strong memory…
Pseudospin Formulation of Quench Dynamics in the Semiclassical Holstein Model
Lingyu Yang, Ho Jang, Sankha Subhra Bakshi +2
We present a pseudospin formulation for the post-quench dynamics of charge-density-wave (CDW) order in the half-filled spinless Holstein model on a square lattice, assuming spatial…
Anomalous coarsening and nonlinear diffusion of kinks in an one-dimensional quasi-classical Holstein model
Ho Jang, Yang Yang, Gia-Wei Chern
We study the phase-ordering dynamics of a quasi-classical Holstein model. At half-filling, the zero-temperature ground state is a commensurate charge-density-wave (CDW) with altern…
Kinetics of Peierls dimerization transition: Machine learning force-field approach
Ho Jang, Yang Yang, Gia-Wei Chern
We present a machine learning (ML) force-field framework for simulating the non-equilibrium dynamics of charge-density-wave (CDW) order driven by the Peierls instability. Since the…