Convergence of statistical moments of particle density time series in scrape-off layer plasmas

Particle density fluctuations in the scrape-off layer of magnetically confined plasmas, as measured by gas-puff imaging or Langmuir probes, are modeled as the realization of a stochastic process in which a superposition of pulses with a fixed shape, an exponential distribution of waiting times and amplitudes represents the radial motion of blob-like structures. With an analytic formulation of the process at hand, we derive expressions for the mean-squared error on estimators of sample mean and sample variance as a function of sample length, sampling frequency, and the parameters of the stochastic process. % Employing that the probability distribution function of a particularly relevant shot noise process is given by the gamma distribution, we derive estimators for sample skewness and kurtosis, and expressions for the mean-squared error on these estimators. Numerically generated synthetic time series are used to verify the proposed estimators, the sample length dependency of their mean-squared errors, and their performance. We find that estimators for sample skewness and kurtosis based on the gamma distribution are more precise and more accurate than common estimators based on the method of moments.Comment: 31 pages, 10 figure

Allocating Interventions Based on Counterfactual Predictions: A Case Study on Homelessness Services

Modern statistical and machine learning methods are increasingly capable of modeling individual or personalized treatment effects by predicting counterfactual outcomes. These counterfactual predictions could be used to allocate different interventions across populations based on individual characteristics. In many domains, like social services, the availability of possible interventions can be severely resource limited. This thesis considers possible improvements to the allocation of such services in the context of homelessness service provision in a major metropolitan area. Using data from the homeless system, I show potential for substantial predicted benefits in terms of reducing the number of families who experience repeat episodes of homelessness by choosing optimal allocations (based on predicted outcomes) to a fixed number of beds in different types of homelessness service facilities. Such changes in the allocation mechanism would not be without tradeoffs, however; a significant fraction of households are predicted to have a higher probability of reentry in the optimal allocation than in the original one. I discuss the efficiency, equity and fairness issues that arise and consider potential implications for policy

Intermittent fluctuations in the Alcator C-Mod scrape-off layer for ohmic and high confinement mode plasmas

Plasma fluctuations in the scrape-off layer of the Alcator C-Mod tokamak in ohmic and high confinement modes have been analyzed using gas puff imaging data. In all cases investigated, the time series of emission from a single spatially-resolved view into the gas puff are dominated by large-amplitude bursts, attributed to blob-like filament structures moving radially outwards and poloidally. There is a remarkable similarity of the fluctuation statistics in ohmic plasmas and in edge localized mode-free and enhanced D-alpha high confinement mode plasmas. Conditionally averaged wave forms have a two-sided exponential shape with comparable temporal scales and asymmetry, while the burst amplitudes and the waiting times between them are exponentially distributed. The probability density functions and the frequency power spectral densities are self-similar for all these confinement modes. These results are strong evidence in support of a stochastic model describing the plasma fluctuations in the scrape-off layer as a super-position of uncorrelated exponential pulses. Predictions of this model are in excellent agreement with experimental measurements in both ohmic and high confinement mode plasmas. The stochastic model thus provides a valuable tool for predicting fluctuation-induced plasma-wall interactions in magnetically confined fusion plasmas.Comment: 17 pages, 10 figure

Vector chiral order in frustrated spin chains

By means of a numerical analysis using a non-Abelian symmetry realization of the density matrix renormalization group, we study the behavior of vector chirality correlations in isotropic frustrated chains of spin S=1 and S=1/2, subject to a strong external magnetic field. It is shown that the field induces a phase with spontaneously broken chiral symmetry, in line with earlier theoretical predictions. We present results on the field dependence of the order parameter and the critical exponents.Comment: 8 pages, 9 figure

Comparison between mirror Langmuir probe and gas puff imaging measurements of intermittent fluctuations in the Alcator C-Mod scrape-off layer

Statistical properties of the scrape-off layer (SOL) plasma fluctuations are studied in ohmically heated plasmas in the Alcator C-Mod tokamak. For the first time, plasma fluctuations as well as parameters that describe the fluctuations are compared across measurements from a mirror Langmuir probe (MLP) and from gas-puff imaging (GPI) that sample the same plasma discharge. This comparison is complemented by an analysis of line emission time-series data, synthesized from the MLP electron density and temperature measurements. The fluctuations observed by the MLP and GPI typically display relative fluctuation amplitudes of order unity together with positively skewed and flattened probability density functions. Such data time series are well described by an established stochastic framework which model the data as a superposition of uncorrelated, two-sided exponential pulses. The most important parameter of the process is the intermittency parameter, {\gamma} = {\tau}d / {\tau}w where {\tau}d denotes the duration time of a single pulse and {\tau}w gives the average waiting time between consecutive pulses. Here we show, using a new deconvolution method, that these parameters can be consistently estimated from different statistics of the data. We also show that the statistical properties of the data sampled by the MLP and GPI diagnostic are very similar. Finally, a comparison of the GPI signal to the synthetic line-emission time series suggests that the measured emission intensity can not be explained solely by a simplified model which neglects neutral particle dynamics

Analyses of the vrl gene cluster in Desulfococcus multivorans: Homologous to the virulence-associated locus of the ovine footrot pathogen Dichelobacter nodosus strain A198

Major parts of the virulence-associated vrl locus known from the gammaproteobacterium Dichelobacter nodosus, the causative agent of ovine footrot, were analyzed in the genome of the sulfate-reducing deltaproteobacterium Desulfococcus multivorans. In the genome of D. multivorans 13 of the 19 vrl genes described for D. nodosus are present and highly conserved with respect to gene sequence and order. The vrl locus and its flanking regions suggest a bacteriophage-mediated transfer into the genome of D. multivorans. Comparative analysis of the deduced Vrl proteins reveals a wide distribution of parts of the virulence-associated vrl locus in distantly related bacteria. Horizontal transfer is suggested as driving mechanism for the circulation of the vrl genes in bacteria. Except for the vrlBMN genes D. multivorans and Desulfovibrio desulfuricans G20 together contain all vrl genes displaying a high degree of similarity. For D. multivorans it could be shown that guanine plus cytosine (GC) content, GC skew, di-, tri- or tetranucleotide distribution did not differ between the vrl locus and its flanking sequences. This could be a hint that the vrl locus originated from a related organism or at least a genome with similar characteristics. The conspicuous high degree of conservation of the analyzed vrl genes may result from a recent transfer event or reflect a function of the vrl genes, which is still unknown and not necessarily disease associated. The latter is supported by the evidence for expression of the vrl genes in D. multivorans, which has not been described as pathogen or to be associated to any disease pattern before

Outlier classification using Autoencoders: application for fluctuation driven flows in fusion plasmas

Understanding the statistics of fluctuation driven flows in the boundary layer of magnetically confined plasmas is desired to accurately model the lifetime of the vacuum vessel components. Mirror Langmuir probes (MLPs) are a novel diagnostic that uniquely allow to sample the plasma parameters on a time scale shorter than the characteristic time scale of their fluctuations. Sudden large-amplitude fluctuations in the plasma degrade the precision and accuracy of the plasma parameters reported by MLPs for cases in which the probe bias range is of insufficient amplitude. While some data samples can readily be classified as valid and invalid, we find that such a classification may be ambiguous for up to 40% of data sampled for the plasma parameters and bias voltages considered in this study. In this contribution we employ an autoencoder (AE) to learn a low-dimensional representation of valid data samples. By definition, the coordinates in this space are the features that mostly characterize valid data. Ambiguous data samples are classified in this space using standard classifiers for vectorial data. This way, we avoid to define complicate threshold rules to identify outliers, which requires strong assumptions and introduce biases in the analysis. Instead, these rules are learned from the data by statistical inference By removing the outliers that are identified in the latent low-dimensional space of the AE, we find that the average conductive and convective radial heat flux are between approximately 5 and 15% lower as when removing outliers identified by threshold values. For contributions to the radial heat flux due to triple correlations, the difference is up to 40%

Commuters route choice behaviour

The paper reports laboratory experiments with a two route choice scenario. In each session 18 subjects had to choose between a main road M and a side road S. The capacity of M was larger. Feedback was given in treatment I only on the subjects' own travel time and in treatment II on travel time for M and S. The main results are as follows: • Mean numbers on M and S are near to pure equilibrium. • Fluctuations persist until the end of the sessions. • The total number of changes is significantly greater in treatment I. • Subjects' road changes and payoffs are negatively correlated. • A direct response mode results in more changes for bad payoffs whereas a contrary response mode shows opposite reactions. • Simulations of an extended payoff sum learning model fits the main results of the statistical evaluation of the data

Burst statistics in Alcator C-Mod SOL turbulence

Bursty fluctuations in the scrape-off layer (SOL) of Alcator C-Mod have been analyzed using gas puff imaging data. This reveals many of the same fluctuation properties as Langmuir probe measurements, including normal distributed fluctuations in the near SOL region while the far SOL plasma is dominated by large amplitude bursts due to radial motion of blob-like structures. Conditional averaging reveals burst wave forms with a fast rise and slow decay and exponentially distributed waiting times. Based on this, a stochastic model of burst dynamics is constructed. The model predicts that fluctuation amplitudes should follow a Gamma distribution. This is shown to be a good description of the gas puff imaging data, validating this aspect of the model.Comment: 8 pages, 6 figure

Blob sizes and velocities in the Alcator C-Mod scrape-off layer

A new blob-tracking algorithm for the GPI diagnostic installed in the outboard-midplane of Alcator C-Mod is developed. I t tracks large-amplitude fluctuations propagating through the scrape-off layer and calculates blob sizes and velocities. We compare the results of this method to a blob velocity scaling from a simple blob-model for sheath-connected blobs. We further present initial results from a fully three-dimensional blob model that features plasma resistivity as a free parameter