Author: Barber, S.K.
Paper Title Page
TUPOST009 Online Correction of Laser Focal Position Using FPGA-Based ML Models 857
 
  • J.A. Einstein-Curtis, S.J. Coleman, N.M. Cook, J.P. Edelen
    RadiaSoft LLC, Boulder, Colorado, USA
  • S.K. Barber, C.E. Berger, J. van Tilborg
    LBNL, Berkeley, California, USA
 
  Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics under Award Numbers DE-SC 00259037 and DE-AC02-05CH11231.
High repetition-rate, ultrafast laser systems play a critical role in a host of modern scientific and industrial applications. We present a prototype diagnostic and correction scheme for controlling and determining laser focal position at 10 s of Hz rate by utilizing fast wavefront sensor measurements from multiple positions to train a focal position predictor. This predictor is used to determine corrections for actuators along the beamline to provide the desired correction to the focal position on millisecond timescales. Our initial proof-of-principle demonstrations leverage pre-compiled data and pre-trained networks operating ex-situ from the laser system. We then discuss the application of a high-level synthesis framework for generating a low-level hardware description of ML-based correction algorithms on FPGA hardware coupled directly to the beamline. Lastly, we consider the use of remote computing resources, such as the Sirepo scientific framework* , to actively update these correction schemes and deploy models to a production environment.
* M.S. Rakitin et al., "Sirepo: an open-source cloud-based software interface for X-ray source and optics simulations", Journal of Synchrotron Radiation 25, 1877-1892 (Nov 2018).
 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST009  
About • Received ※ 20 May 2022 — Revised ※ 14 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 23 June 2022
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