Langevin Equations, Fokker–Planck Equations and Entropic Analysis of a Model-Independent Classical Plasma

Plasma dynamics have been studied extensively and there is a fair amount of understanding where the scientific community has reached at. However, there is still a very big gap in completely explaining plasma physics at the classical as well as the quantum level. The dynamics of plasma from an entropic approach are not very well understood or explained. There is too much chaos to account for and even a small deviation in terms of perturbations of any kind makes a sizeable difference. This study is based on the entropic approach where we take a model independent classical plasma. Then we apply Langevin equations and Fokker–Planck equations to explain the entropy generated and entropy produced. Then we study various conditions in which we apply an electric field and a magnetic field and understand the various trends in entropy changes. When we apply the electric field and the magnetic fields independently of each other and together in the plasma model, we see that there is a very important change in the increase in entropy. There are also changes in the plasma flow, but the overall flow does not drastically change since we have considered a model independent plasma. Finally, we show that there are indeed changes to the entropy in a model-independent classical plasma in the various cases as mentioned in this study.

Modelling of Dynamic Behaviour in Magnetic Nanoparticles

The efficient development and utilisation of magnetic nanoparticles (MNPs) for applications in enhanced biosensing relies on the use of magnetisation dynamics, which are primarily governed by the time-dependent motion of the magnetisation due to externally applied magnetic fields. An accurate description of the physics involved is complex and not yet fully understood, especially in the frequency range where Néel and Brownian relaxation processes compete. However, even though it is well known that non-zero, non-static local fields significantly influence these magnetisation dynamics, the modelling of magnetic dynamics for MNPs often uses zero-field dynamics or a static Langevin approach. In this paper, we developed an approximation to model and evaluate its performance for MNPs exposed to a magnetic field with varying amplitude and frequency. This model was initially developed to predict superparamagnetic nanoparticle behaviour in differential magnetometry applications but it can also be applied to similar techniques such as magnetic particle imaging and frequency mixing. Our model was based upon the Fokker–Planck equations for the two relaxation mechanisms. The equations were solved through numerical approximation and they were then combined, while taking into account the particle size distribution and the respective anisotropy distribution. Our model was evaluated for Synomag®-D70, Synomag®-D50 and SHP-15, which resulted in an overall good agreement between measurement and simulation.

Diffusion with stochastic resetting of interacting particles emerging in a model of population genetics

In this paper we put forward a Generalized Ohta-Kimura ladder model (GOKM) which bears a strong liaison with the so-called jump-type Fleming-Viot process (JFVP). The novelty here, when we compare with the classical Ohta-Kimura model, is that we now have an operator which allows multiple interaction among the individuals. It has to do with a generalized branching mechanism: m individual types extinguish and one individual type splits into m copies. The system of evolution equations arising from GOKM can be seen as a system of n-dimensional Kolmogorov forward equations (or Fokker-Planck equations). Besides the interest in its own right a favorable feature of GOKM, vis-`a-vis JFVP, is that its analysis requires a more amenable armory of concepts and mathematical technique to analyze some relevant issues such as correlation, indistinguishability of individuals and stationarity. In addition, as a by product, we show that the connection between Ohta-Kimura Model and diffusion with resetting, as previously structured in [6], can be extended to our setting.