Comparison of unfolding methods for the inference of runaway electron energy distribution from ­ŁťŞ-ray spectroscopic measurements

E. Panontin*, A. Dal Molin, M. Nocente, G. Croci, J. Eriksson, L. Giacomelli, G. Gorini, M. Iliasova, E. Khilkevitch, A. Muraro, D. Rigamonti, M. Salewski, J. Scionti, A. Shevelev, M. Tardocchi, the Eurofusion MST1 Team, ASDEX Upgrade Team

*Corresponding author for this work

Research output: Contribution to journal ÔÇ║ Conference article ÔÇ║ Research ÔÇ║ peer-review

Abstract

Unfolding techniques are employed to reconstruct the 1D energy distribution of runaway electrons from Bremsstrahlung hard X-ray spectrum emitted during plasma disruptions in tokamaks. Here we compare four inversion methods: truncated singular value decomposition, which is a linear algebra technique, maximum likelihood expectation maximization, which is an iterative method, and Tikhonov regularization applied to ¤ç2 and Poisson statistics, which are two minimization approaches. The reconstruction fidelity and the capability of estimating cumulative┬ástatistics, such as the mean and maximum energy, have been assessed on both synthetic and┬áexperimental spectra. The effect of measurements limitations, such as the low energy cut and few number of counts, on the final reconstruction has also been studied. We find that the iterative┬ámethod performs best as it better describes the statistics of the experimental data and is more robust┬áto noise in the recorded spectrum.
Original languageEnglish
Article numberC12005
JournalJournal of Instrumentation
Volume16
Number of pages9
ISSN1748-0221
DOIs
Publication statusPublished - 2021
Event4th European Conference on Plasma Diagnostics - Online
Duration: 7 Jun 2021 Ôćĺ 11 Jun 2021
Conference number: 4

Conference

Conference4th European Conference on Plasma Diagnostics
Number4
LocationOnline
Period07/06/2021 Ôćĺ 11/06/2021

Keywords

  • Nuclear instruments and methods for hot plasma diagnostics
  • Plasma diagnostics - interferometry, spectroscopy and imaging
  • Analysis and statistical methods
  • Plasma diagnostics- charged-particle spectroscopy

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