Computational Methods in High Energy Density Plasmas

March 12 - June 15, 2012

Overview

High energy density physics (HEDP) is a rapidly growing field.graphic for poster HEDP conditions are typically from Mbar to tens of Gbar pressures and temperatures ranging from eV to GeV. These are the conditions
seen in the interiors of Jovian planets, the core of the sun, Tokamaks and matter in the early stages of the universe. With the advent of experimental platforms like the Linear Coherent Light Source (LCLS), the National Ignition Facility (NIF), pulse power and the Relativistic Heavy Ion Collider (RHIC), the scientific community is beginning to obtain high quality data of matter at extreme conditions. In addition, new high performance computing hardware is providing exciting new massively parallel platforms that enable higher fidelity simulations.

This long program will focus on the computational approaches to the modeling of these extreme states of matter. It will address the scientific challenges facing the computational HEDP community and discuss the successes and failures of various methods. Algorithmic approaches such as Particle-In-Cell, Molecular Dynamics, Wave packet Molecular Dynamics and Wigner Trajectories will be compared and contrasted. The computer science challenges of writing and running massively parallel simulations is critical to the success of being able to simulate the various HEDP phenomena. Experimental data will play a key role in the long program as the scientific driver for the computational approaches, as well as a way of providing code validation.

Organizing Committee

Christina Back (General Atomics)
Andrew Christlieb (Michigan State University, Mathematics)
Jill Dahlburg (United States Naval Research Laboratory)
Michael Desjarlais (Sandia National Laboratories)
Frank Graziani (Lawrence Livermore National Laboratory)
Leslie Greengard (New York University)
David Levermore (University of Maryland, Department of Mathematics)
Warren Mori (University of California, Los Angeles (UCLA), Physics/Engineering)
Michael Murillo (Los Alamos National Laboratory)