Abstract
We investigate the turbulence statistics associated with low-to-high confinement (L-H) transitions and externally applied resonant magnetic perturbations (RMPs) in KSTAR. Time-series fluctuations of electron density ne (BES), electron temperature Te (ECEI), and the time derivative of the poloidal magnetic field dBθ/dt (Mirnov coils) are analysed using information-geometric measures (information rate Γ and information length L = R Γdt), together with kurtosis κ and variance σ2. In low-density upper single-null plasmas (ne ∼ 1.2 × 1019 m−3), a ∼ 80 kHz magnetic mode coupling ne, Te, and dBθ/dt emerges prior to the L-H transition and persists into the ELMy H-mode. Edge-localised RMPs (ERMPs) suppress this coherent mode but enhance intermittency, producing frequent bursts that abruptly reshape the time- dependent Probability Density Functions (PDFs) and generate large spikes in Γ (with smaller changes in κ), signalling ERMP-driven departures from quasi-stationarity. The impact of ERMPs on background fluctuation levels depends on density, radial location, and the fluctuating variable itself (n ̃, T ̃, B ̇θ), whereas L provides a robust, regime- agnostic measure of cumulative statistical reorganisation and spatial decorrelation. In particular, at low density we observe weaker coupling between n ̃ and T ̃, along with a tendency toward decreased radial correlation—most clearly for T ̃—under ERMPs. Overall, information geometry cleanly captures intermittent events, quantifies non- equilibrium PDF evolution, and offers a compact, cross-diagnostic metric for assessing RMP effects on edge transport and correlation across densities, radial locations, and confinement states.
| Original language | English |
|---|---|
| Article number | 105002 |
| Journal | Plasma Physics and Controlled Fusion |
| Volume | 67 |
| Issue number | 10 |
| Early online date | 29 Sept 2025 |
| DOIs | |
| Publication status | Published - 2025 |
Bibliographical note
Publisher Copyright:© 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Funding
This research is supported by Brain Pool Program funded by the Ministry of Science and ICT through the National Research Foundation of Korea (RS-2023-00284119). EK thanks Seoul National University for support and hospitality.
| Funders | Funder number |
|---|---|
| Ministry of Science and ICT | |
| Seoul National University | |
| National Research Foundation of Korea | RS-2023-00284119 |
Keywords
- ELMs
- KSTAR
- L-H transition
- RMPs
- information geometry
- statistical
- turbulence
ASJC Scopus subject areas
- Nuclear Energy and Engineering
- Condensed Matter Physics
Fingerprint
Dive into the research topics of 'Turbulence statistical analysis of the L-H transition and RMPs in KSTAR'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS