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Description
Using advanced particle-in-cell simulation techniques combined with Bayesian optimization, we determine the maximum electron energy that a self-guided laser wakefield accelerator driven by a laser of a given energy and wavelength can produce [1, 2]. By systematically optimizing accelerator performance across a range of laser energies and wavelengths, we identify new scaling laws for both the maximum electron energy and the corresponding acceleration distance. These scaling laws (i) are expressed solely in terms of laser energy and wavelength, (ii) yield the highest electron energy over the shortest acceleration distance possible, and (iii) are accompanied by the complete set of laser and plasma parameters required to enable the scaling. The resulting scaling laws provide a practical guidance for designing state-of-the-art laser wakefield acceleration experiments operating at their fundamental performance limits.
[1] P. Valenta, T. Zh. Esirkepov, J. D. Ludwig, S. C. Wilks, and S. V. Bulanov, “Bayesian optimization of electron energy from laser wakefield accelerators”, Phys. Rev. Accel. Beams 28, 094601 (2025).
[2] P. Valenta, K. G. Miller, B. K. Russell, M. Lamač, M. Jech, G. M. Grittani, and S. V. Bulanov, “Optimized matching conditions for self-guided laser wakefield accelerators”, Mach. Learn.: Sci. Technol. 7, 025030 (2026).