Weller, M.E.; Beiersdorfer, P.; Soukhanovskii, V.; Magee, E.W.; Scotti, F.
Three extreme ultraviolet (EUV) spectrometers have been mounted on the National Spherical Torus Experiment-Upgrade (NSTX-U). All three are flat-field grazing-incidence spectrometers and are dubbed X-ray and Extreme Ultraviolet Spectrometer (8 ñ 70 ≈), Long-Wavelength Extreme Ultraviolet Spectrometer (190 ñ 440 ≈), and Metal Monitor and Lithium Spectrometer Assembly (MonaLisa, 50 ñ 220 ≈). XEUS and LoWEUS were previously implemented on NSTX to monitor impurities from low- to high-Z sources and to study impurity transport while MonaLisa is new and provides the system increased spectral coverage. The spectrometers will also be a critical diagnostic on the planned laser blow-off (LBO) system for NSTX-U, which will be used for impurity edge and core ion transport studies, edge-transport code development, and benchmarking atomic physics codes.
Bejjanki, Vikranth R.; da Silveira, Rava Azeredo; Cohen, Jonathan D.; Turk-Browne, Nicholas B.
Multivariate decoding methods, such as multivoxel pattern analysis (MVPA), are highly effective at extracting information from brain imaging data. Yet, the precise nature of the information that MVPA draws upon remains controversial. Most current theories emphasize the enhanced sensitivity imparted by aggregating across voxels that have mixed and weak selectivity. However, beyond the selectivity of individual voxels, neural variability is correlated across voxels, and such noise correlations may contribute importantly to accurate decoding. Indeed, a recent computational theory proposed that noise correlations enhance multivariate decoding from heterogeneous neural populations. Here we extend this theory from the scale of neurons to functional magnetic resonance imaging (fMRI) and show that noise correlations between heterogeneous populations of voxels (i.e., voxels selective for different stimulus variables) contribute to the success of MVPA. Specifically, decoding performance is enhanced when voxels with high vs. low noise correlations (measured during rest or in the background of the task) are selected during classifier training. Conversely, voxels that are strongly selective for one class in a GLM or that receive high classification weights in MVPA tend to exhibit high noise correlations with voxels selective for the other class being discriminated against. Furthermore, we use simulations to show that this is a general property of fMRI data and that selectivity and noise correlations can have distinguishable influences on decoding. Taken together, our findings demonstrate that if there is signal in the data, the resulting above-chance classification accuracy is modulated by the magnitude of noise correlations.
Kinetic modification of ideal stability theory from stabilizing resonances of mode-particle interaction has had success in explaining resistive wall mode (RWM) stability limits in tokamaks. With the goal of real-time stability forecasting, a reduced kinetic stability model has been implemented in the new Disruption Event Characterization and Forecasting (DECAF) code, which has been written to analyze disruptions in tokamaks. The reduced model incorporates parameterized models for ideal limits on beta, a ratio of plasma pressure to magnetic pressure, which are shown to be in good agreement with DCON code calculations. Increased beta between these ideal limits causes a shift in the unstable region of delta W_K space, where delta W_K is the change in potential energy due to kinetic effects that is solved for by the reduced model, such that it is possible for plasmas to be unstable at intermediate beta but stable at higher beta. Gaussian functions for delta W_K are defined as functions of E cross B frequency and collisionality, with parameters reflecting the experience of the National Spherical Torus Experiment (NSTX). The reduced model was tested on a database of discharges from NSTX and experimentally stable and unstable discharges were separated noticeably on a stability map in E cross B frequency, collisionality space. The reduced model only failed to predict an unstable RWM in 15.6% of cases with an experimentally unstable RWM and performed well on predicting stability for experimentally stable discharges as well.
A real-time velocity (RTV) diagnostic based on active charge-exchange recombination spectroscopy is now operational on the National Spherical Torus Experiment-Upgrade (NSTX-U) spherical torus (Menard et al 2012 Nucl. Fusion 52 083015). The system has been designed to supply plasma velocity data in real time to the NSTX-U plasma control system, as required for the implementation of toroidal rotation control. Measurements are available from four radii at a maximum sampling frequency of 5 kHz. Post-discharge analysis of RTV data provides additional information on ion temperature, toroidal velocity and density of carbon impurities. Examples of physics studies enabled by RTV measurements from initial operations of NSTX-U are discussed.
Transport analysis, ion-scale turbulence measurements, and initial linear and nonlinear gyrokinetic simulations are reported for a transport validation study based on low aspect ratio NSTX-U L-mode discharges. The relatively long, stationary L-modes enabled by the upgraded centerstack provide a more ideal target for transport validation studies that were not available during NSTX operation. Transport analysis shows that anomalous electron transport dominates energy loss while ion thermal transport is well described by neoclassical theory. Linear gyrokinetic GYRO analysis predicts that ion temperature gradient (ITG) modes are unstable around normalized radii $\rho$=0.6-0.8, although $E\timesB$ shearing rates are larger than the linear growth rates over much of that region. Deeper in the core ($\rho$=0.4-0.6), electromagnetic microtearing modes (MTM) are unstable as a consequence of the relatively high beta and collisionality in these particular discharges. Consistent with the linear analysis, local, nonlinear ion-scale GYRO simulations predict strong ITG transport at $\rho$=0.76, whereas electromagnetic MTM transport is important at $\rho$=0.47. The prediction of ion-scale turbulence is consistent with 2D beam emission spectroscopy (BES) that measures the presence of broadband ion-scale fluctuations. Interestingly, the BES measurements also indicate the presence of bi-modal poloidal phase velocity propagation that could be indicative of two different turbulence types. However, in the region between ($\rho$=0.56, 0.66), ion-scale simulations are strongly suppressed by the locally large $E\timesB$ shear. Instead, electron temperature gradient (ETG) turbulence simulations predict substantial transport, illustrating electron-scale contributions can be important in low aspect ratio L-modes, similar to recent analysis at conventional aspect ratio. However, agreement within experimental uncertainties has not been demonstrated, which requires additional simulations to test parametric sensitivities. The potential need to include profile-variation effects (due to the relatively large value of $\rho_*$=$\rho_i$/a at low aspect ratio), including electromagnetic and possibly multi-scale effects, is also discussed.
A matrix inversion technique is derived to calculate local ion temperature from line-integrated measurements of an extended emission source in an axisymmetric plasma which exactly corrects for both toroidal velocity and radial velocity components. Local emissivity and toroidal velocity can be directly recovered from line-integrated spectroscopic measurements, but an independent measurement of the radial velocity is necessary to complete the temperature inversion. The extension of this technique to handle the radial velocity is relevant for magnetic reconnection and merging compression devices where temperature inversion from spectroscopic measurements is desired. A simulation demonstrates the effects of radial velocity on the determination of ion temperature.