Computational Methods for Quantum High-Energy-Density Physics
Abstract
Abstract High-energy-density (HED) science concerns the physics and chemistry of matter subjected to extreme conditions, with pressures ranging from millions to trillions of atmospheres. Experimental and computational studies of the quantum nature of HED matter have discovered many interesting phenomena, ranging from high-pressure induced superconductivity, hydrogen-helium de-mixing, diamond precipitation in carbon-bearing compounds, to a completely new high-pressure periodic table of elements. Better understanding quantum HED matter can have significant impacts on planetary science, astrophysics, and technological applications such as harnessing clean energy through inertial confinement fusion (ICF) and designing new quantum materials. Computational study of HED science, with quantum-mechanical methods, play a vital role in advancing this new field. These first-principles methods include finite-temperature density-functional theory (DFT), DFT-based quantum molecular dynamics (QMD), time-dependent DFT (TD-DFT), path-integral Monte Carlo (PIMC), path-integral molecular dynamics (PIMD), as well as machine-learning (ML) and artificial intelligence (AI) applications to HED science. The book presents practical procedures for calculating material properties of quantum HED matter—such as the equation of state (EOS), transport properties (including thermal and electrical conductivities, diffusion coefficients, viscosity, and stopping power), and radiative properties (opacity and…
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