Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userElucidating plasma dynamics in Hasegawa-Wakatani turbulence by information geometry
228
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
The impact of adiabatic electrons on drift-wave turbulence, modelled by the Hasegawa-Wakatani equations, is studied using information length. Information length is a novel theoretical method for measuring distances between statistical states represented by different probability distribution functions (PDFs) along the path of a system. Specifically, the time-dependent PDFs of turbulent fluctuations for a given adiabatic index $A$ is computed. The changes in fluctuation statistics are then quantified in time by using information length. The numerical results provide time traces exhibiting intermittent plasma dynamics, and such behaviour is identified by a rapid change in the information length. The effects of $A$ are discussed.
rate research
Read More
Resistive drift wave turbulence is a multipurpose paradigm that can be used to understand transport at the edge of fusion devices. The Hasegawa-Wakatani model captures the essential physics of drift turbulence while retaining the simplicity needed to gain a qualitative understanding of this process. We provide a theoretical interpretation of numerically generated probability density functions (PDFs) of intermittent events in Hasegawa-Wakatani turbulence with enforced equipartition of energy in large scale zonal flows and small scale drift turbulence. We find that for a wide range of adiabatic index values the stochastic component representing the small scale turbulent eddies of the flow, obtained from the ARIMA model, exhibits super-diffusive statistics, consistent with intermittent transport. The PDFs of large events (above one standard deviation) are well approximated by the Laplace distribution, while small events often exhibit a Gaussian character. Furthermore there exist a strong influence of zonal flows for example, via shearing and then viscous dissipation maintaining a sub-diffusive character of the fluxes.
We propose a new perspective on Turbulence using Information Theory. We compute the entropy rate of a turbulent velocity signal and we particularly focus on its dependence on the scale. We first report how the entropy rate is able to describe the distribution of information amongst scales, and how one can use it to isolate the injection, inertial and dissipative ranges, in perfect agreement with the Batchelor model and with a fBM model. In a second stage, we design a conditioning procedure in order to finely probe the asymmetries in the statistics that are responsible for the energy cascade. Our approach is very generic and can be applied to any multiscale complex system.
The generic question is considered: How can we determine the probability of an otherwise quasirandom event, having been triggered by an external influence? A specific problem is the quantification of the success of techniques to trigger, and hence control, edge-localised plasma instabilities (ELMs) in magnetically confined fusion (MCF) experiments. The development of such techniques is essential to ensure tolerable heat loads on components in large MCF fusion devices, and is necessary for their development into economically successful power plants. Bayesian probability theory is used to rigorously formulate the problem and to provide a formal solution. Accurate but pragmatic methods are developed to estimate triggering probabilities, and are illustrated with experimental data. These allow results from experiments to be quantitatively assessed, and rigorously quantified conclusions to be formed. Example applications include assessing whether triggering of ELMs is a statistical or deterministic process, and the establishment of thresholds to ensure that ELMs are reliably triggered.
Recently, two novel techniques for the extraction of the phase-shift map (Tomassini {it et.~al.}, Applied Optics {bf 40} 35 (2001)) and the electronic density map estimation (Tomassini P. and Giulietti A., Optics Communication {bf 199}, pp 143-148 (2001)) have been proposed. In this paper we apply both methods to a sample laser-plasma interferogram obtained with femtoseconds probe pulse, in an experimental setup devoted to laser particle acceleration studies.
Most information dynamics and statistical causal analysis frameworks rely on the common intuition that causal interactions are intrinsically pairwise -- every cause variable has an associated effect variable, so that a causal arrow can be drawn between them. However, analyses that depict interdependencies as directed graphs fail to discriminate the rich variety of modes of information flow that can coexist within a system. This, in turn, creates problems with attempts to operationalise the concepts of dynamical complexity or `integrated information. To address this shortcoming, we combine concepts of partial information decomposition and integrated information, and obtain what we call Integrated Information Decomposition, or $Phi$ID. We show how $Phi$ID paves the way for more detailed analyses of interdependencies in multivariate time series, and sheds light on collective modes of information dynamics that have not been reported before. Additionally, $Phi$ID reveals that what is typically referred to as integration is actually an aggregate of several heterogeneous phenomena. Furthermore, $Phi$ID can be used to formulate new, tailored measures of integrated information, as well as to understand and alleviate the limitations of existing measures.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
