Prof. Eun-jin Kim

Coventry University

Professor Kim obtained her PhD in Physics from the University of Chicago, USA. She held postdoctoral positions at the Universities of Leeds and Exeter in UK, National Center for Atmospheric Research in Boulder, USA and University of California, San Diego, USA and was an Associate Professor at the University of Sheffield, UK. She is currently a Professor in Applied Mathematics and Physics at Coventry University, UK and a Visiting Scientist at Seoul National University, South Korea. She has a track record of multidisciplinary research in plasmas, fluids and complex systems, and non-equilibrium statistical mechanics, with her notable contribution to understanding turbulent transport and self-organisation in magnetically confined nuclear fusion and astrophysical plasmas including the Low-to-High confinement transition. She was awarded the Leverhulme Trust Research Fellowship and published around 150 peer reviewed research papers.

Abstract:
Statistical approaches to fusion plasmas

There has been a growing number of experiments and simulations revealing ample evidence for turbulent and even non-equilibrium characteristics (e.g., anomalous transport, mini avalanches, intermittency) of fusion plasmas. In particular, while the Low-to-High confinement mode (L-H) transition – a novel self-organization in magnetically confined plasma - has been considered to be a deterministic bifurcation, there are observations of micro avalanches or transport events [5] occurring on time scales smaller than a typical L-H transition time of O(1) ms in edge plasmas, suggesting the importance of stochastic noise in the L-H transition. Furthermore, turbulence characteristics in Low confinement (L) mode are very variable, often with highly time-varying RMS values of fluctuating electron density and turbulence velocity. These point out the limited utility of stationary approach and mean-field type concepts based on small fluctuations with a short memory time such as mean values, variance, or transport coefficients.

This talk presents recent progress on a new statistical approach to fusion plasmas using a non-perturbative method [1,2,3,4] for improved characterization of the statistical property of fusion plasmas, which can help gain insights into data emerging from different tokamak experiments. For instance, moving away from a naïve picture of the deterministic bifurcation, a stochastic model of the L-H transition [1,2,3] elucidates how statistical properties change over the L-H transition with the help of time-dependent probability density functions (PDFs) and information geometric measures [5,6]. In particular, stochastic noises produce random trajectories of turbulence, zonal flows, and mean flows, leading to the L-H transition occurring at different times and uncertainty in power threshold. The latter can also result from different power ramping scenarios and initial conditions. Furthermore, our method is demonstrated to help quantifying correlation and causal relation among different variables, which is one of the outstanding issues in the L-H transition. Some of the theoretical findings are supported from experimental data analysis [7]. Effects of stochastic noises on edge localized modes (ELMs) [6] are further discussed.

References:
[1] Eun-jin Kim & Rainer Hollerbach, Physical Review Research 2, 023077 (2021).
[2] Eun-jin Kim & Abhiram Anand Thiruthummal, Stochastic Dynamics of Fusion Low-to-High Confinement Mode (L-H) Transition: Correlation and Causal Analyses Using Information Geometry, Entropy 26(17):1-21
[3] P Fuller, E Kim, R Hollerbach, and B Hnat, Time-dependent probability density functions, information geometry and entropy production in a stochastic prey–predator model of fusion plasmas, Physics of Plasmas 30(10) (2023).
[4] E Kim & R Hollerbach, A stochastic model of edge-localized modes in magnetically confined plasmas, Philosophical transactions. Series A, Mathematical, physical, and engineering sciences. 381, 2242, 16 p., 20210226 (2023).
[5] E Kim & A-J Guel-Cortez, Causal Information Rate, Entropy 23, 1087 (2021).
[6] E Kim, Information Geometry, Fluctuations, Non-Equilibrium Thermodynamics, and Geodesics in Complex Systems, Entropy. 23, 1393 (2021).
[7] HJ Farre-Kaga, Y Andrew, J Dunsmore, E Kim, TL Rhodes, L Schmitz, and Z Yan, Time-dependent probability density function analysis of H-mode transitions, Euro Phys Lett. 142, 64001 (2023).