NP Nonlinear Processes in Geosciences
The 2024 Division Outstanding Early Career Scientist Award is awarded to Simone Benella for his many original contributions in the field of stochastic processes, advancing the understanding space plasma dynamics.
Simone Benella, a very active early career scientist, specialises in the field of nonlinear processes in space physics. His research focuses on various aspects, such as studying space plasmas, investigating large-scale solar wind structures, turbulence, cosmic ray propagation, solar energetic particle events, and space weather.
Benella’s academic journey started with a degree course in theoretical physics, where he specialised in statistical mechanics. During this time, he conducted a thesis on the topic of self-organised criticality. In this context, he planned and analyzed the results of a sandpile model, studying its evolution on different types of networks.
During his PhD, he actively participated in the collaboration of the LISA Pathfinder space mission. He worked with data measured by the particle detector onboard the mission, conducting data analysis and model development. His focus was on understanding recurrent and transient variations observed in short-term cosmic ray flows. He employed advanced data analysis techniques, including the Wavelet transform, the Hilbert-Huang transform, and the Grad-Shafranov reconstruction. Additionally, he conducted numerical simulations to study cosmic ray trajectories within flux-rope magnetic field structures.
Since his postdoctoral work starting from 2020 until the present, Benella has been conducting studies on the statistical properties observed in magnetic field and velocity field fluctuations in space plasmas. His dual objective is to investigate the universality of space plasma dynamics at kinetic scales through the Markov property of fluctuations and to propose a new phenomenological model based on a generalised Langevin approach. His exploration of stochastic processes led him to formulate a method for studying and modelling the behaviour of different space plasmas as the solar wind, the terrestrial magnetosheath, and polar and equatorial near-Earth current systems using stochastic differential equations.