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physics.comp-ph2026
High-order tensor neural network for iteration-free structure relaxation
Shaobo Yu, Haoting Zhang, Yu Han +5
Structure relaxation is important for the discovery of new materials, yet conventional ab initio optimization remains a major bottleneck in high-throughput screening workflows. Mac…
physics.comp-ph2026
Differentiable Particle-Mesh Ewald with Cartesian Tensor Message Passing for Learning Long-Range Electrostatics and Dipole Response
Zhiyue Guo, Junjie Wang, Haoting Zhang +4
Machine learning interatomic potentials (MLIPs) can approach quantum accuracy for short-range chemistry, but most architectures remain local and fail to capture the long-range elec…
physics.comp-ph2026
NEPMaker: Active learning of neuroevolution machine learning potential for large cells
Junjie Wang, Shuning Pan, Haoting Zhang +4
Machine learning potentials (MLPs) achieve near first-principles accuracy but often fail for atomic environments outside the training distribution. Active learning can mitigate thi…