4 papers
ML and AI for density functional theory: different priorities for Kohn-Sham and orbital-free DFT, for electronic and nuclear DFT
Xin-Hui Wu, Sergei Manzhos
We overview similarities and, importantly, differences in computational bottlenecks and accuracy requirements that can be addressed with machine learning (ML) and artificial intell…
Normal mode analysis within relativistic massive transport
Xin Lin, Qiu-Ze Sun, Xin-Hui Wu +1
In this paper, we address the normal mode analysis on the linearized Boltzmann equation for massive particles in the relaxation time approximation. One intriguing feature of massiv…
Basis Representation for Nuclear Densities from Principal Component Analysis
Chen-Jun Lv, Tian-Yu Wu, Xin-Hui Wu +2
We develop an efficient method to represent nuclear densities using basis functions extracted via Principal Component Analysis (PCA). Applying PCA to densities of 75 nuclei calcula…
Optimized adiabatic-impulse protocol preserving Kibble-Zurek scaling with attenuated anti-Kibble-Zurek behavior
Han-Chuan Kou, Zhi-Han Zhang, Xin-Hui Wu +3
We propose an optimized adiabatic-impulse (OAI) protocol that substantially reduces the evolution time for crossing a quantum phase transition while preserving Kibble-Zurek (KZ) sc…