Data-driven optimal models for kinetic dynamos

The magnetic fields permeating the universe profoundly affect the development of astrophysical systems from stellar to cosmological scales, and play key roles in transport and particle acceleration processes.

The dynamo responsible for generating the cosmic magnetic fields—an inherently three-dimensional multi-scale process—is challenging to model; only in recent years has it become possible to account for its collisionless, kinetic nature.

The first steps in exploring the kinetic ion dynamics in dynamos have shown the essential role of instabilities facilitating magnetic field growth, while the electron dynamics remains unexplored due to numerical challenges.

This project will, for the first time, establish the role of kinetic electrons on the cosmic dynamo, by developing and employing powerful tools for high fidelity modeling of collisionless plasmas.

Recent data-driven methodology will be utilized to construct efficient but accurate simplified models, optimal in approximating the kinetic plasma system for given model complexity.

We will study critical stages of the field growth, such as the transition to the magnetized regime, thereby making a major step towards a comprehensive understanding of astrophysical dynamos.

The modeling capabilities developed will benefit the study of collisionless turbulent systems, from galaxy cluster scale down to our immediate space environment, as well as dynamo experiments moving towards astrophysically relevant parameter regimes.