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Thermodynamic Fidelity of Generative Models for Ising System
Brian H. Lee, Kat Nykiel, Ava E. Hallberg +2
Machine learning has become a central technique for modeling in science and engineering, either complementing or as surrogates to physics-based models. Significant efforts have rec…
Accelerating active learning materials discovery with FAIR data and workflows: a case study for alloy melting temperatures
Mohnish Harwani, Juan C. Verduzco, Brian H. Lee +1
Active learning (AL) is a powerful sequential optimization approach that has shown great promise in the discovery of new materials. However, a major challenge remains the acquisiti…
Multi-Task Multi-Fidelity Learning of Properties for Energetic Materials
Robert J. Appleton, Daniel Klinger, Brian H. Lee +6
Data science and artificial intelligence are playing an increasingly important role in the physical sciences. Unfortunately, in the field of energetic materials data scarcity limit…
Shortcut to adiabaticity improvement of STIRAP based qubit rotation
Khayla Black, Xi Chen, Tim Byrnes
Robust quantum control is essential for the development of quantum computers, which rely on precise manipulation of qubits. One form of quantum control is stimulated Raman adiabati…
Graph neural network coarse-grain force field for the molecular crystal RDX
Brian H. Lee, James P. Larentzos, John K. Brennan +1
Condense phase molecular systems organize in wide range of distinct molecular configurations, including amorphous melt and glass as well as crystals often exhibiting polymorphism,…