Refine
Year of publication
Document Type
- Article (4188) (remove)
Keywords
- stars: massive (55)
- gamma rays: general (45)
- stars: early-type (44)
- stars: winds, outflows (42)
- Magellanic Clouds (38)
- cosmic rays (38)
- diffusion (38)
- X-rays: stars (37)
- radiation mechanisms: non-thermal (37)
- ISM: supernova remnants (33)
Institute
- Institut für Physik und Astronomie (4188) (remove)
Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.