Stochastic Dynamics of Fusion Low-to-High Confinement Mode (L-H) Transition: Correlation and Causal Analyses Using...

Area of Science:

• Plasma Physics
• Fusion Energy
• Nonlinear Dynamics

Background:

• The Low-to-High (L-H) confinement mode transition is crucial for achieving sustained fusion reactions.
• Deterministic models predict a sharp L-H transition, but experimental observations show more gradual behavior.

Purpose of the Study:

• To investigate the stochastic dynamics governing the L-H transition in magnetically confined fusion plasmas.
• To understand the role of noise in turbulence, zonal flows, and input power on the L-H transition.
• To explore the self-regulation mechanisms and causal relationships involved in the L-H transition.

Main Methods:

• Stochastic simulations of a prey-predator model for L-H transition dynamics.
• Inclusion of stochastic noise in turbulence and zonal flows.
• Simulation of constant and time-varying input power (Q) across over a million trajectories using GPU computing.
• Analysis using information geometry to interpret self-regulation and causality.

Main Results:

• Stochastic noise leads to a mixture of H-mode and dithering states, resulting in a gradual L-H transition.
• H-mode characteristics emerge at lower input power (QQc).
• A prominent bimodal probability density function (PDF) near the critical power (Qc) indicates coexistence of states and input power uncertainty.
• Time-varying input power increases trajectory variability and enhances the bimodal PDF.

Conclusions:

• Stochasticity fundamentally alters the L-H transition, explaining gradual transitions and power uncertainty observed experimentally.
• Information geometry provides insights into the interplay between zonal flows, turbulence, and causal relationships governing the L-H transition.
• The findings highlight the importance of incorporating stochastic effects for accurate modeling of fusion plasma confinement.