Probability distribution functions for intermittent scrape-off layer plasma fluctuations
Audun Theodorsen, Odd Erik Garcia

TL;DR
This paper develops a stochastic model for plasma fluctuations in the scrape-off layer, exploring how different amplitude distributions affect statistical properties and proposing a parameter estimation method based on the empirical distribution function.
Contribution
It introduces a flexible amplitude distribution in the model and presents a new parameter estimation approach using the empirical distribution function.
Findings
Changing amplitude distributions impacts the moments and probability density functions.
The proposed parameter estimation method is effective on synthetic data.
The model helps describe intermittent plasma fluctuations in magnetized boundary regions.
Abstract
A stochastic model for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas has been constructed based on a super-position of uncorrelated pulses arriving according to a Poisson process. In the most common applications of the model, the pulse amplitudes are assumed exponentially distributed, supported by conditional averaging of large-amplitude fluctuations in experimental measurement data. This basic assumption has two potential limitations. First, statistical analysis of measurement data using conditional averaging only reveals the tail of the amplitude distribution to be exponentially distributed. Second, exponentially distributed amplitudes leads to a positive definite signal which cannot capture fluctuations in for example electric potential and radial velocity. Assuming pulse amplitudes which are not positive definite often make finding a closed form…
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