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Modeling partially-ionized dense plasma using wavepacket molecular dynamics
Daniel Plummer, Pontus Svensson, Wiktor Jasniak +3
We develop a wave packet molecular dynamics framework for modeling the structural properties of partially-ionized dense plasmas, based on a chemical model that explicitly includes…
Resolution-Independent Machine Learning Heat Flux Closure for ICF Plasmas
M. Luo, A. R. Bell, F. Miniati +2
Accurate modeling of heat flux in inertial confinement fusion plasmas requires closures that remain predictive far from local equilibrium and across disparate spatial and temporal…
Roadmap for warm dense matter physics
Jan Vorberger, Frank Graziani, David Riley +71
This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter physics. Originating from strongl…
Statistical theory of electronic degrees of freedom in wave packet molecular dynamics
Daniel Plummer, Pontus Svensson, Wiktor Jasniak +3
We derive statistical distributions for the degrees of freedom in wave packet molecular dynamics models. Specifically, a theory is developed for the width distributions of Gaussian…
Time-Embedded Convolutional Neural Networks for Modeling Plasma Heat Transport
Mufei Luo, Charles Heaton, Yizhen Wang +5
We introduce a time-embedded convolutional neural network (TCNN) for modeling spatiotemporal heat transport in plasmas, particularly under strongly nonlocal conditions. In our earl…
Learning Heat Transport Kernels Using a Nonlocal Heat Transport Theory-Informed Neural Network
Mufei Luo, Charles Heaton, Yizhen Wang +5
We present a data-driven framework for the modeling of nonlocal heat transport in plasmas using a nonlocal theory informed neural network trained on kinetic Particle-in-Cell simula…