How electrons are arranged in materials gives rise to a large variety of different behaviors. We can observe these behaviors and use them in various technologies. However, the prediction of these behaviors is a serious challenge. This makes the successful design of new materials harder. The goal of the Materials Genome Initiative is to use computer simulations to model electrons according to the laws of quantum physics. This will allow researchers to design new materials with desired properties. This project aims to build fast and accurate computer programs which simulate those new materials. These programs combine advances in computer science, quantum chemistry, and condensed-matter physics. They will be implemented in an open-source Python-based community code. This distribution model allows other researchers to use this code and to contribute new features.
This research addresses gaps in existing software cyberinfrastructure in quantum materials simulation, by developing novel parallel implementations of low-scaling, high-accuracy methods. In particular, new techniques for mean-field calculations will be developed, which will act as groundwork for periodic coupled-cluster and quantum Monte Carlo methods. State-of-the-art techniques in sparsity and tensor decomposition will be employed to achieve good system-size scaling while retaining accuracy within each of these numerical schemes. Critically, the methods will be developed using efficient high-level software abstractions, implemented as Python-level modules within PySCF that leverage the Cyclops library for massively-parallel execution. The library software infrastructure will also be extended to maximize productivity via source-to-source automatic differentiation, as well as to enable execution of sparse kernels on emerging GPU-based supercomputing architectures.
This award is jointly supported by the NSF Office of Advanced Cyberinfrastructure, and the Division of Materials Research and the Division of Chemistry within the NSF Directorate of Mathematical and Physical Sciences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
