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  • Open Access

Spectrotemporal properties of the coherently emitted synchrotron radiation: A machine learning approach

Arjun Radha Krishnan*, Arne Held, Carsten Mai, Zohair Usfoor, Vivek Vijayan, and Shaukat Khan†

  • Center for Synchrotron Radiation (DELTA) and Department of Physics, TU Dortmund University, Maria-Goeppert-Mayer-Straße 2, 44227, Dortmund, Germany

  • *Contact author: arjun.krishnan@tu-dortmund.de
  • †Contact author: shaukat.khan@tu-dortmund.de
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Phys. Rev. Accel. Beams 29, 085101 – Published 13 August, 2026

DOI: https://doi.org/10.1103/znnk-swms

Abstract

At the 1.5-GeV synchrotron light source DELTA operated by TU Dortmund University, intense and ultrashort radiation pulses in the vacuum ultraviolet and terahertz regimes are generated by the interaction of femtosecond laser pulses with electron bunches in an undulator. The resulting periodic modulation of the electron energy is converted into a density modulation in a dispersive section, giving rise to coherent radiation emission at harmonics of the seed wavelength in a second undulator. This process is known as coherent harmonic generation (CHG). This paper describes the experimental setup and concentrates on the spectral aspects of CHG radiation under variation of properties of the seed laser pulse and the dispersive section. CHG spectra at the second harmonic of the 800 nm seed wavelength were recorded using a grating spectrometer equipped with an image-intensified CCD camera. Numerical simulations to model the CHG spectra for different group-delay dispersion and third-order dispersion were carried out, and a convolutional neural network was implemented to predict these parameters from measured CHG spectra. The results show that the tunable laser parameters directly translate into the spectrotemporal properties of the coherently emitted pulses.

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Phys. Rev. Accel. Beams 29, 085101– Published 13 August, 2026
  • Received 13 March 2026
  • Accepted 21 May 2026
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

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