7 papers
A Global Spacetime Optimization Approach to the Real-Space Time-Dependent Schrödinger Equation
Enze Hou, Yuzhi Liu, Linxuan Zhang +3
The time-dependent Schrödinger equation (TDSE) in real space is fundamental to understanding the dynamics of many-electron quantum systems, with applications ranging from quantum…
Reinforcement Fine-Tuning for Materials Design
Zhendong Cao, Lei Wang
Reinforcement fine-tuning played an instrumental role in enhancing the instruction-following and reasoning abilities of large language models. In this work, we employ reinforcement…
Multi-Task Fine-Tuning Enables Robust Out-of-Distribution Generalization in Atomistic Models
Chengqian Zhang, Duo Zhang, Anyang Peng +7
Accurate de novo molecular and materials design requires structure-property models that generalize beyond known regimes. Although pretrained atomistic models achieve strong in-dist…
CrystalFormer-CSP: Thinking Fast and Slow for Crystal Structure Prediction
Zhendong Cao, Shigang Ou, Lei Wang
Crystal structure prediction is a fundamental problem in materials science. We present CrystalFormer-CSP, an efficient framework that unifies data-driven heuristic and physics-driv…
Space Group Informed Transformer for Crystalline Materials Generation
Zhendong Cao, Xiaoshan Luo, Jian Lv +1
We introduce CrystalFormer, a transformer-based autoregressive model specifically designed for space group-controlled generation of crystalline materials. By explicitly incorporati…
CrystalFlow: A Flow-Based Generative Model for Crystalline Materials
Xiaoshan Luo, Zhenyu Wang, Qingchang Wang +4
Deep learning-based generative models have emerged as powerful tools for modeling complex data distributions and generating high-fidelity samples, offering a transformative approac…