Time-dependent probability density functions and information geometry in a stochastic prey–predator model of fusion plasmas

A stochastic, prey–predator model of the low to high confinement transition is presented. The model concerns the interaction of a turbulent fluctuation amplitude, zonal flow shear, and the ion density gradient. Delta-correlated noise terms are used to construct Langevin equations for each of the three variables, and a Fokker–Planck equation is subsequently derived. A time-dependent probability distribution function is solved and a number of diagnostic quantities are calculated from it, including the information rate and length. We find the marginal probability distribution functions to be strongly non-Gaussian and frequently multi-modal, showing the coexistence of dithering and H-mode solutions over time. The information rate and length are shown to be useful diagnostics to investigate self-regulation between the variables, particularly the turbulence and zonal flow shear.

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Publication Details

Journal
Physics of Plasmas
Published
2024-09-01
DOI
https://doi.org/10.1063/5.0193622
Citations
6
Primary Topic
Magnetic confinement fusion research
Type
article
Field-Weighted Citation Impact
3.96

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article

Time-dependent probability density functions and information geometry in a stochastic prey–predator model of fusion plasmas

B. Hnat, Rainer Hollerbach, Eun‐jin Kim, Patrick Fuller
6 citations
Physics of Plasmas
Magnetic confinement fusion research
3.96
article

Time-dependent probability density functions and information geometry in a stochastic prey–predator model of fusion plasmas

B. Hnat, Rainer Hollerbach, Eun‐jin Kim, Patrick Fuller
article en
6 citations

Abstract

A stochastic, prey–predator model of the low to high confinement transition is presented. The model concerns the interaction of a turbulent fluctuation amplitude, zonal flow shear, and the ion density gradient. Delta-correlated noise terms are used to construct Langevin equations for each of the three variables, and a Fokker–Planck equation is subsequently derived. A time-dependent probability distribution function is solved and a number of diagnostic quantities are calculated from it, including the information rate and length. We find the marginal probability distribution functions to be strongly non-Gaussian and frequently multi-modal, showing the coexistence of dithering and H-mode solutions over time. The information rate and length are shown to be useful diagnostics to investigate self-regulation between the variables, particularly the turbulence and zonal flow shear.

Physics of PlasmasVol. 31(9)
University of Leeds (GB), Seoul National University (KR), University of Warwick (GB), Coventry University (GB)
National Research Foundation, Seoul National University, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 5%
Magnetic confinement fusion research
3.96
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Time-dependent probability density functions and information geometry in a stochastic prey–predator model of fusion plasmas — B. Hnat, Rainer Hollerbach, et al. · Physics of Plasmas (2024) | TGRS Research Map | TGRS