Abstract Details
Abstracts
Author: Evdokiya G. Kostadinova
Requested Type: Poster
Submitted: 2026-03-23 06:48:10
Co-authors: B. Andrew, J. Eskew, B. Elster, S. Ostermeier, D. M. Orlov, E. Howell
Contact Info:
Auburn University
380 Duncan Dr
Auburn, AL 36849
United States
Abstract Text:
In magnetized plasmas, such as those in fusion and astrophysical/space environments, microscopic correlations arise from interactions between the charged particles and electromagnetic fields. The resulting complex dynamics of these systems exhibit both long-range (non-local) interactions in space and memory effects in time. One of the most common cumulative manifestations of these effects is the observance of anomalous diffusion of particles and heat. Unlike Brownian motion which tends to smoothen gradients in space and encourage thermalization, anomalous diffusion allows particles to localize around attractors and/or make large scale jumps. As a result, the plasma species can be driven away from equilibrium leading to macroscopic effects, such as the onset of microturbulence and anomalous resistivity.
Here we discuss two complementary approaches to anomalous diffusion in magnetized plasmas: (i) a spectral approach [1], [2], where the diffusion regime is determined by the spectrum of the Hamiltonian and (ii) a non-extensive statistics approach [3] where diffusion is studied from explicit reconstruction of the probability distribution functions. Using scaling relations between the two methods [4], we aim to reconstruct collisional and correlation terms that can be used in kinetic and fluid models of magnetized plasma.
Work supported by NSF-PHY-2440328, NSF-PHY- 2515867, EPSCoR FTPP OIA-2148653, DE-SC0023061, DE-SC0024547, DE-FG02-05ER54809.
[1] C. D. Liaw, Journal of Statistical Physics, 2013, pp. 1022-38.
[2] J. L. Padgett, E. G. Kostadinova, C. D. Liaw, K. Busse, L. S. Matthews, and T. W. Hyde, Journal of Physics A: Mathematical and Theoretical, 2020, pp. 135205.
[3] C. Tsallis, Interdisciplinary Aspects of Turbulence, 2008, pp. 21-28.
[4] B. R. Andrew, Doctoral dissertation, Auburn University, 2025.
Characterization: 4.0
Comments: