Optimized matching conditions for self-guided laser wakefield accelerators
Abstract
Abstract We revisit the matching conditions for self-guided laser pulse propagation in plasma and refine their formulation to maximize the energy of electrons produced via laser wakefield acceleration. Bayesian optimization, combined with particle-in-cell simulations carried out in a quasi-three-dimensional geometry and a Lorentz-boosted frame, is employed. The optimization identifies the maximum electron energy that a self-guided laser wakefield accelerator, driven by a laser of a given energy, can produce, together with the corresponding acceleration distance. Our results further demonstrate that electrons with energies close to the maximum value can be obtained across a relatively wide range of input parameters and without the need for their precise tuning. This provides substantial flexibility for experimental implementation and significantly relaxes the operational constraints associated with self-guided laser wakefield accelerators.
Fields of Study & Subjects
Laser-Plasma Interactions and Diagnostics
Laser-Matter Interactions and Applications
Space Satellite Systems and Control
Publication details
- Journal / source
- Machine Learning Science and Technology
- Volume
- 7
- Issue
- 2
- Pages
- 025030–025030
- Publication date
- 13 March 2026