3 papers
cond-mat.stat-mech2026
Preserving Hamiltonian Locality in Real-Space Coarse-Graining via Kernel Projection
Sun Haoyuan
Numerical simulations of critical lattice systems are fundamentally limited by critical slowing down, as long-range correlations are typically established through slow temporal equ…
cond-mat.mtrl-sci2025
Small-Cell-Based Fast Active Learning of Machine Learning Interatomic Potentials
Zijian Meng, Hao Sun, Edmanuel Torres +3
Machine learning interatomic potentials (MLIPs) are often trained with on-the-fly active learning, where sampled configurations from atomistic simulations are added to the training…
cond-mat.dis-nn2025
Amorphous silicon structures generated using a moment tensor potential and the activation relaxation technique nouveau
Karim Zongo, Hao Sun, Claudiane Ouellet-Plamondon +2
Preparing realistic atom-scale models of amorphous silicon (a-Si) is a decades-old condensed matter physics challenge. Herein, we combine the Activation Relaxation Technique nouvea…