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Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence

A geometrical method for assessing stochastic processes in plasma turbulence is investigated in this study. The thermodynamic length methodology allows using a Riemannian metric on the phase space; thus, distances between thermodynamic states can be computed. It constitutes a geometric methodology t...

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Autores principales: Papadopoulos, Aristeides D., Anderson, Johan, Kim, Eun-jin, Mavridis, Michail, Isliker, Heinz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297455/
https://www.ncbi.nlm.nih.gov/pubmed/37372286
http://dx.doi.org/10.3390/e25060942
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author Papadopoulos, Aristeides D.
Anderson, Johan
Kim, Eun-jin
Mavridis, Michail
Isliker, Heinz
author_facet Papadopoulos, Aristeides D.
Anderson, Johan
Kim, Eun-jin
Mavridis, Michail
Isliker, Heinz
author_sort Papadopoulos, Aristeides D.
collection PubMed
description A geometrical method for assessing stochastic processes in plasma turbulence is investigated in this study. The thermodynamic length methodology allows using a Riemannian metric on the phase space; thus, distances between thermodynamic states can be computed. It constitutes a geometric methodology to understand stochastic processes involved in, e.g., order–disorder transitions, where a sudden increase in distance is expected. We consider gyrokinetic simulations of ion-temperature-gradient (ITG)-mode-driven turbulence in the core region of the stellarator W7-X with realistic quasi-isodynamic topologies. In gyrokinetic plasma turbulence simulations, avalanches, e.g., of heat and particles, are often found, and in this work, a novel method for detection is investigated. This new method combines the singular spectrum analysis algorithm with a hierarchical clustering method such that the time series is decomposed into two parts: useful physical information and noise. The informative component of the time series is used for the calculation of the Hurst exponent, the information length, and the dynamic time. Based on these measures, the physical properties of the time series are revealed.
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spelling pubmed-102974552023-06-28 Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence Papadopoulos, Aristeides D. Anderson, Johan Kim, Eun-jin Mavridis, Michail Isliker, Heinz Entropy (Basel) Article A geometrical method for assessing stochastic processes in plasma turbulence is investigated in this study. The thermodynamic length methodology allows using a Riemannian metric on the phase space; thus, distances between thermodynamic states can be computed. It constitutes a geometric methodology to understand stochastic processes involved in, e.g., order–disorder transitions, where a sudden increase in distance is expected. We consider gyrokinetic simulations of ion-temperature-gradient (ITG)-mode-driven turbulence in the core region of the stellarator W7-X with realistic quasi-isodynamic topologies. In gyrokinetic plasma turbulence simulations, avalanches, e.g., of heat and particles, are often found, and in this work, a novel method for detection is investigated. This new method combines the singular spectrum analysis algorithm with a hierarchical clustering method such that the time series is decomposed into two parts: useful physical information and noise. The informative component of the time series is used for the calculation of the Hurst exponent, the information length, and the dynamic time. Based on these measures, the physical properties of the time series are revealed. MDPI 2023-06-15 /pmc/articles/PMC10297455/ /pubmed/37372286 http://dx.doi.org/10.3390/e25060942 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Papadopoulos, Aristeides D.
Anderson, Johan
Kim, Eun-jin
Mavridis, Michail
Isliker, Heinz
Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence
title Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence
title_full Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence
title_fullStr Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence
title_full_unstemmed Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence
title_short Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence
title_sort statistical analysis of plasma dynamics in gyrokinetic simulations of stellarator turbulence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297455/
https://www.ncbi.nlm.nih.gov/pubmed/37372286
http://dx.doi.org/10.3390/e25060942
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