Journal Article PUBDB-2026-01341

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U-Net-based surrogate modeling for attosecond X-ray free-electron lasers

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2026
Springer Heidelberg

The European physical journal / D 80(5), 53 () [10.1140/epjd/s10053-026-01163-6]
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Report No.: arXiv:2601.10898

Abstract: Attosecond X-ray pulse generation in modern X-ray free-electron lasers relies on strongly compressed, precisely tailored electron bunches, making accurate diagnostics and control of the two-dimensional longitudinal phase space (LPS) essential. In the self-chirping scheme, collective effects in the linac generate a strong energy chirp that is converted into high peak current through pre-undulator compression, enabling isolated attosecond pulse generation. Reliable operation of this scheme depends on precise two-dimensional LPS control and fast diagnostics. In this work, we present a U-Net-based neural-network surrogate that predicts two-dimensional LPS distributions directly from accelerator settings. The model exhibits good agreement with start-to-end simulation results. These results demonstrate the potential of neural-network surrogates to facilitate fast virtual diagnostics and provide a step toward real-time tuning in attosecond XFEL operation.

Keyword(s): Accelerator Physics (physics.acc-ph) ; FOS: Physical sciences

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Contributing Institute(s):
  1. XFEL (MXL)
  2. FEL Physics (XFEL_E2_FP)
Research Program(s):
  1. 621 - Accelerator Research and Development (POF4-621) (POF4-621)
  2. 6G13 - Accelerator of European XFEL (POF4-6G13) (POF4-6G13)
Experiment(s):
  1. Facility (machine) XFEL

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U-Net-based surrogate modeling for attosecond X-ray free-electron lasers
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 Record created 2026-04-23, last modified 2026-11-13