2014
DOI: 10.1088/0029-5515/54/8/083031
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Visible light tomography of MHD eigenmodes in the H-1NF stellarator using magnetic coordinates

Abstract: A tomographic reconstruction technique is described for the inversion of a set of limited-angle high-resolution 2D visible light emission projections of global MHD eigenmodes in the H-1NF heliac. The technique is well suited to limited viewing access in toroidal devices and the strong shaping of optimized stellarator/heliotron configurations. Fluctuations are represented as a finite sum of Fourier modes characterized by toroidal and poloidal mode numbers having fixed amplitude and phase in a set of nested flux… Show more

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Cited by 8 publications
(17 citation statements)
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“…Linear growth rate scans are also complemented with global kinetic calculations from EUTERPE in Fig. (13). These qualitatively confirm the findings from the LGRO study, and demonstrate that the inclusion of finite Larmor radius effects can reduce the growth rate by a factor of three, but do not affect marginal stability.…”
Section: Discussionsupporting
confidence: 80%
“…Linear growth rate scans are also complemented with global kinetic calculations from EUTERPE in Fig. (13). These qualitatively confirm the findings from the LGRO study, and demonstrate that the inclusion of finite Larmor radius effects can reduce the growth rate by a factor of three, but do not affect marginal stability.…”
Section: Discussionsupporting
confidence: 80%
“…In earlier work in tokamak physics, standing modes have been reconstructed from observed data using the standard least-squares method [2]. Here, we instead adopt a Bayesian approach to model-parameter estimation.…”
Section: Bayesian Inferencementioning
confidence: 99%
“…Bayes theorem is a fundamental result of probability theory which in our context can be written as P(I|D) = P(D|I)P(I) P(D) , (2) where: P(I), called the prior, is a probability distribution representing our underlying knowledge about the state of the currents; P(D|I), called the likelihood function, describes the probability of a particular measurement given the state and our knowledge of measurement errors; P(D), called the marginal probability, quantifies our belief that we will observe a particular piece of data in the case where we know as little as possible about the state. Note that we will usually ignore the marginal likelihood in what follows because in our context it is just a normalising constant which can be restored when needed.…”
Section: Bayesian Inferencementioning
confidence: 99%
“…Computed tomography is a promising approach for measuring the entire structure and the disparate scale of plasma fluctuations 12 . Tomography has been already used as plasma diagnostics to cylindrical and toroidal devices 13 25 , although the past and existing tomography applications have never detected the plasma fluctuations in sufficient temporal scales. Specifically, 2-D tomography has been constructed in the plasma assembly for nonlinear turbulence analysis (PANTA) device 26 .…”
Section: Introductionmentioning
confidence: 99%