Experimental tests of astrophysical photoionized plasma models using the Z-machine at Sandia National Laboratories

ORAL

Abstract

The Z-machine at Sandia National Laboratories generates powerful X-ray radiation fluxes. This enables experiments to produce macroscopic plasmas at extreme conditions such as those found in accretion disk plasmas around black holes. Complex models for these non-Local-Thermodynamic-Equilibrium (non-LTE) plasmas remain mostly untested with laboratory data. We use a novel platform developed on the Z-machine to reach the same photon flux, density, and temperature conditions in black hole accretion disks. We will present model to data comparisons of the first ever high S/N iron L-shell x-ray emission spectra from a laboratory photoionized plasma. Such data have been a laboratory astrophysics goal for two decades but are even more critical now because of the “Super-Solar” iron abundance problem. Iron abundances inferred from x-ray spectra emitted by photoionized plasma around most black holes appear to contain 5-20 times more iron than the Sun. This contradicts the widely held expectation that most objects in the universe have the Sun’s composition. One prevailing theory is that effects of high electron density are not properly accounted for in the models. Reinterpreting the x-ray spectra with updated models resolved much of that discrepancy. However, a key question still remains: do photoionized plasma spectral models accurately account for x-ray emission? We will describe our progress in using this dataset to evaluate model accuracy and its potential to inform the super-solar iron abundance problem.

Presenters

  • Patricia B Cho

    University of Texas at Austin

Authors

  • Patricia B Cho

    University of Texas at Austin

  • Guillaume P Loisel

    Sandia National Laboratories

  • James Edward Bailey

    Sandia National Laboratories

  • Christopher J Fontes

    Los Alamos National Laboratory, Los Alamos National Laboratory (LANL)

  • Isaac D Huegel

    University of Michigan

  • Daniel C Mayes

    University of Texas at Austin

  • Javier Garcia

    NASA Goddard

  • Tim Kallman

    NASA Goddard

  • Taisuke N Nagayama

    Sandia National Laboratories

  • Stephanie B Hansen

    Sandia National Laboratories