AI RESEARCH
Data-Driven Spectral Prediction for Accelerating Large-Scale Electronic Structure Calculations
arXiv CS.LG
•
ArXi:2606.00401v1 Announce Type: cross Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT) codes exhibit linear scaling, solving the associated large, sparse generalized eigenproblems remains a critical computational bottleneck on exascale architectures. In the context of the LimitX project, we propose a data-driven framework to accelerate these calculations.