4 papers
Graph Neural Network Predictions of Carbon 1s Binding Energies with Near-Experimental Accuracy
Adam E. A. Fouda, Joshua Zhou, Rodrigo Ferreira +10
Graph neural networks are promising architectures for fast, accurate and transferable predictions of core-electron binding energies, which depend on the local bond environment. Her…
Multireference Embedding and Fragmentation Methods for Classical and Quantum Computers: from Model Systems to Realistic Applications
Shreya Verma, Abhishek Mitra, Qiaohong Wang +8
One of the primary challenges in quantum chemistry is the accurate modeling of strong electron correlation. While multireference methods effectively capture such correlation, their…
Enabling Multireference Calculations on Multi-Metallic Systems with Graphic Processing Units
Valay Agarawal, Rishu Khurana, Cong Liu +3
Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and design of new materials. This work describes an initial implementation for…
Pushing the Accuracy Limit of Foundation Neural Network Models with Quantum Monte Carlo Forces and Path Integrals
Anouar Benali, Thomas Plé, Olivier Adjoua +18
We propose an end-to-end integrated strategy to produce highly accurate quantum chemistry (QC) synthetic datasets (energies and forces) aimed at deriving Foundation Machine Learnin…