11 papers
Absorbing Many-Body Correlations into Core-Optimized Orbitals
Hao Zhang, Matthew Otten
The cost of simulating quantum many-body systems - on classical or quantum hardware - scales with the number of variational parameters, so progress at fixed computational budget hi…
Direct imaging of a Berry curvature nematic state in a spin-compensated magnet
Weihang Lu, Camron Farhang, Yuchuan Yao +6
Density waves conventionally describe the periodic modulation of charge or spin, yet the spatial modulation of electronic geometry has remained elusive. Here, we report subtle micr…
CycleChemist: A Dual-Pronged Machine Learning Framework for Organic Photovoltaic Discovery
Hou Hei Lam, Jiangjie Qiu, Xiuyuan Hu +5
Organic photovoltaic (OPV) materials offer a promising path toward sustainable energy generation, but their development is limited by the difficulty of identifying high performance…
Quantized SO(3)-Equivariant Graph Neural Networks for Efficient Molecular Property Prediction
Haoyu Zhou, Ping Xue, Hao Zhang +1
Deploying 3D graph neural networks (GNNs) that are equivariant to 3D rotations (the group SO(3)) on edge devices is challenging due to their high computational cost. This paper add…
Nonperturbative Semiclassical Spin Dynamics for Ordered Quantum Magnets
Hao Zhang, Tianyue Huang, Allen O. Scheie +7
In ordered quantum magnets where interactions between elementary excitations dominate over their kinetic energy, perturbative approaches often fail, making non-perturbative methods…
High-resolution wide-field magnetic imaging with sparse sampling using nitrogen-vacancy centers
Keqing Liu, Jiazhao Tian, Bokun Duan +7
Nitrogen-vacancy (NV) centers in diamond enable quantitative magnetic imaging, yet practical implementations must balance spatial resolution against acquisition time (and thus per-…