Speaker
Saransh Malhotra
(University of Liverpool, Cockcroft Institute)
Description
Precise characterisation of photocathode mean transverse energy is critical for optimising electron beam quality. This paper presents a physics-informed image processing pipeline using Transverse Energy Spread Spectrometer data (231–291 nm), incorporating Gaussian PSF fitting, Wiener deconvolution, resolution equalisation, and noise-aware augmentation. A high-fidelity dataset of 6500 synthetic images was generated, achieving average SSIM = 0.997 and $ R^2 \approx 0.98 $, enabling robust MTE prediction and supporting future ML-based diagnostics for next-generation photoinjectors.
Funding Agency
This work was supported by STFC through the LIV.INNO CDT (ST/W006766/1), the ASTeC core grant, and the Cockcroft Institute core grant (ST/V001612/1).
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Author
Saransh Malhotra
(University of Liverpool, Cockcroft Institute)
Co-authors
Lee Jones
(Cockcroft Institute, ASTeC, STFC Daresbury Laboratory)
Narender Kumar
(University of Liverpool, Cockcroft Institute)
Carsten Welsch
(University of Liverpool, Cockcroft Institute)
