A Temporal Retrieval Method for Modulated Electron Bunches via Adaptive Kernel Reconstruction

TL;DR

This paper introduces a new temporal retrieval algorithm for complex modulated electron beams using adaptive kernel reconstruction, improving diagnostics for XFELs and plasma accelerators.

Contribution

The paper presents a novel algorithm that separates and reconstructs high- and low-frequency components of electron beam signals from CTR diagnostics.

Findings

Successfully reconstructed temporal signals from complex electron bunch trains.

Achieved better performance than the Kramers-Kronig method.

Demonstrated applicability on multi-Gaussian and harmonic generation models.

Abstract

Femtosecond electron beams with complex modulation play a crucial role in applications such as X-ray Free Electron Lasers (XFELs) and plasma wakefield accelerators. However, diagnostics for the electron beam current profile still face challenges with complex structure. In this letter, we propose a novel temporal retrieval algorithm for the coherent transition radiation (CTR) diagnostics of complex modulated electron beams. Starting from the time-frequency analysis of the electron bunch train, the algorithm separates and reconstructs the high- and low-frequency components. A temporal kernel was derived from the inverse sampling of the measured spectrum to construct the high-frequency component, while the low-frequency envelope was composed of several basis functions. Tested on the electron bunch trains from the complex multi-gaussian model and bunching-enhanced coherent harmonic generation, the algorithm successfully reconstructed the temporal signals and achieves better performance than the Kramers-Kronig method. This method is expected to crucial provide temporal evidence for potential electron beam modulation schemes, and will enable broad prospects for future applications.