Toward electron temperature profiles in hot-dense plasmas from x-ray spectral ensembles

High repetition rate laser systems enable new strategies for diagnosing plasma behavior with large datasets. Here, we define an ensemble technique that relies on randomized targeting of x-ray tracer micro-stripes. On each shot, a high-intensity laser pulse is focused on a solid target with Ti tracer stripes embedded in an Al foil, randomly targeting a micro-stripe, a portion of a stripe, or a gap between stripes. High-resolution, time-integrated x-ray spectrometers capture line emission from the portion of the micro-stripe that is heated to sufficiently high electron temperatures. Accumulation of many such cases is used to construct ensemble distributions of x-ray line intensities that encompass all relative offsets of the laser focus to the micro-stripe centers. Synthetic intensity distributions are likewise generated using collisional-radiative modeling. Bayesian fitting of modeled to measured intensity distributions establishes the most likely radial temperature profiles, enabling comparison to hydrodynamic models and calling into question the cylindrical symmetry of these micro-stripe-embedded systems. Ensemble techniques have significant potential for high-energy-density plasma diagnostics, especially with the advent of high repetition rate experiments.

Authors

Institutions

Publication Details

Journal
Physics of Plasmas
Published
2024-11-01
DOI
https://doi.org/10.1063/5.0214771
Citations
3
Primary Topic
Laser-induced spectroscopy and plasma
Type
article
Field-Weighted Citation Impact
0.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Toward electron temperature profiles in hot-dense plasmas from x-ray spectral ensembles

P. C. Efthimion, S. Zahedpour, S. N. Benjamin, R. Hollinger et al.
3 citations
Physics of Plasmas
Laser-induced spectroscopy and plasma
0.81
article

Toward electron temperature profiles in hot-dense plasmas from x-ray spectral ensembles

P. C. Efthimion, S. Zahedpour, S. N. Benjamin, R. Hollinger, Brian Kraus, S. Malko, Lan Gao, Shawn McPoyle, K. W. Hill, J. J. Rocca, Shoujun Wang, John G. King, E. Kriz, K. Atay, V. N. Shlyaptsev
article en
3 citations

Abstract

High repetition rate laser systems enable new strategies for diagnosing plasma behavior with large datasets. Here, we define an ensemble technique that relies on randomized targeting of x-ray tracer micro-stripes. On each shot, a high-intensity laser pulse is focused on a solid target with Ti tracer stripes embedded in an Al foil, randomly targeting a micro-stripe, a portion of a stripe, or a gap between stripes. High-resolution, time-integrated x-ray spectrometers capture line emission from the portion of the micro-stripe that is heated to sufficiently high electron temperatures. Accumulation of many such cases is used to construct ensemble distributions of x-ray line intensities that encompass all relative offsets of the laser focus to the micro-stripe centers. Synthetic intensity distributions are likewise generated using collisional-radiative modeling. Bayesian fitting of modeled to measured intensity distributions establishes the most likely radial temperature profiles, enabling comparison to hydrodynamic models and calling into question the cylindrical symmetry of these micro-stripe-embedded systems. Ensemble techniques have significant potential for high-energy-density plasma diagnostics, especially with the advent of high repetition rate experiments.

Physics of PlasmasVol. 31(11)
Princeton University (US), Princeton Plasma Physics Laboratory (US), Mercer County Community College (US), McGill University (CA), Colorado State University (US)
Fusion Energy Sciences, Princeton Plasma Physics Laboratory
Affordable and clean energy
Openalex Percentile: Top 32%
Laser-induced spectroscopy and plasma
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.