BOLA – Optimization of Laser Plasma Wakefield Accelerators Using Bayesian Methods, Combining Numerical Simulation and Experimental Data
Programme / Call codes: S-IRA-25-8 (related projects: P-IRA-25-13, P-IRA-25-20)
Project type: ITP
Implementing organisation: Centre for Physical Sciences and Technology (FTMC)
Other country project No.: 101169117
Project duration: 01 September 2025 – 31 August 2027
FTMC Project Leader: Gediminas Račiukaitis
The aim of this project is to optimise the acceleration of high-energy electron beams in laser plasma wakefield accelerators while achieving minimal energy spread and beam divergence. This will be accomplished by applying Bayesian Optimisation (BO) to synthetic data generated from Particle-in-Cell (PIC) numerical simulations of electron acceleration, covering a wide range of laser and plasma parameters.
The simulations will include the following key variables:
– laser intensity,
– pulse duration,
– focal spot (beam) diameter,
– longitudinal plasma density profiles.
Bayesian optimisation will be integrated with PIC simulations and ANSYS Fluent gas flow modelling, enabling systematic exploration and optimisation of experimental parameters and improved control over the quality of the accelerated electron beams.
In addition, machine learning techniques will be employed to analyse and interpret experimental data, allowing model refinement and reduction of discrepancies between numerical predictions and real experimental results.
In the second phase of the project, PIC simulations will be performed using experimentally measured laser beam and plasma target profiles, and the results will be directly compared with experimental data obtained using high-repetition-rate terawatt (TW)-class lasers.
The ultimate scientific objective of the project is to contribute to the development of compact laser-driven particle accelerator technologies for applications in research, medicine and industry, and to achieve Very High Energy Electron (VHEE) beam parameters suitable for cancer radiotherapy.
This multidisciplinary approach, combining advanced numerical methods, Bayesian optimisation and experimental validation, represents a significant contribution to the programme objectives and to the advancement of cutting-edge laser–plasma acceleration technologies.
