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Conferences > CLEO_SI > 2021 > STh1B > STh1B.7

Towards Real-time Adaptable Machine Learning-based Photoinjector Shaping

Jack Hirschman, Randy Lemons, Ryan Coffee, Federico Belli, and Sergio Carbajo

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Abstract

Hardware-based machine learning for photoinjector manipulation is a promising solution for real-time adaptive electron-beam manipulation. We present preliminary studies towards this goal including simulations of the optical system and early machine learning results.

© 2021 The Author(s)

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