4 papers
Deep Wave Network for Modeling Multi-Scale Physical Dynamics
Alexander I. Khrabry, Edward A. Startsev, Andrew T. Powis +1
Performance of deep learning models is strongly governed by architectural capacity, with width and depth as primary controls. However, in physical-science applications, models are…
Accelerating kinetic plasma simulations with machine learning generated initial conditions
Andrew T. Powis, Domenica Corona Rivera, Alexander Khrabry +1
Computer aided engineering of multi-time-scale plasma systems which exhibit a quasi-steady state solution are challenging due to the large number of time steps required to reach co…
Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems
Alexander Khrabry, Edward Startsev, Andrew Powis +1
We propose a novel efficient architecture for learning long-term evolution in complex multi-scale physical systems which is based on the idea of separation of scales. Structures of…
Size-dependent second-order-like phase transitions in Fe nanocluster melting from low-temperature structural isomerization
Louis E. S. Hoffenberg, Alexander Khrabry, Yuri Barsukov +2
In this work, the melting phase transitions of nanoclusters with atoms are investigated using classical many-body molecular dynamics simulations. For…