Speaker
Description
In controlled laboratory setups, when lasers interact with solid or gaseous targets, various phenomena such as shock formation, plasma instability, and magnetic reconnection can be observed. Understanding the behavior of electromagnetic fields in plasmas is crucial in these experiments. To measure these fields, scientists utilize a method called ion radiography, also known as proton imaging. High-energy protons are generated from a point-like source and directed through the plasma system. As they travel through the plasma, they interact with electromagnetic fields, causing changes to their paths. When these protons reach a detector, they create an image that reveals the electromagnetic field patterns within the plasma. However, a major challenge in proton imaging techniques is determining the path-integrated electromagnetic fields based on the observed proton fluence. To address this challenge, we aim to use neural network techniques to reconstruct electric and magnetic fields for ion radiography applications. We will present the development plan and recent advancements in this context.
