Sprecher
Beschreibung
Abstract:
Applications in the field of laser ion acceleration demand stable and reproducible ion bunches with well-controlled properties. To facilitate this, most high-power laser systems allow manipulation of the laser’s physical properties, such as its temporal or focal shape, by adjusting the control parameters of specific hardware devices. However, the complex physical effects involved in the laser target interaction make it challenging to identify control parameter settings that support desired acceleration properties.
A method that can efficiently search for the optimum operation setting in large parameter spaces is Bayesian optimization (BO). This machine learning technique is specifically designed to find the optimum of unknown, multi-dimensional parameter spaces with a limited number of evaluations.
For laser-ion acceleration, BO has been proven to optimize the laser wavefront of a 12TW laser system [1]. We will present our plans to establish such methods at our multi-PW-capable ATLAS 3000 laser system. A preliminary study will showcase the first fully automated BO of our laser-driven ion source. This optimization aims at maximizing the number of accelerated protons with energy around 14±2MeV by finding the optimal target position along the optical axis. A specifically developed software framework manages the automated operation and performs user-specific scanning and optimization routines. As a prerequisite, we also study the influence of machine control parameters on the temporal and focal shape of the laser pulse and the accelerated ions' properties. Conducted work paves the way to perform a simultaneous and automated optimization of the laser’s temporal and spatial properties to identify promising acceleration regimes and to optimize the ion bunch properties towards an application’s specifications.
Our presentation will contain the results of this study, as well as our plans for the simultaneous optimization of the laser’s temporal and focal shape. Our work was supported by the Bundesministerium für Bildung und Forschung (BMBF) within project 01IS17048 and the Centre for Advanced Laser Applications (CALA).
[1] Loughran, B., et al. “Automated Control and Optimization of Laser-Driven Ion Acceleration.” High Power Laser Science and Engineering 11 (2023): e35. https://doi.org/10.1017/hpl.2023.23.
