15–17 Jul 2026
SLAC
America/Los_Angeles timezone

Autonomous Tuning at FACET-II

16 Jul 2026, 14:00
20m
48/1-112A/B/C/D - Redwood A/B/C/D (SLAC)

48/1-112A/B/C/D - Redwood A/B/C/D

SLAC

90
AI/ML Applications: AI/ML and Accelerators AI/ML Applications

Speakers

Juan Pablo Gonzalez-Aguilera (SLAC National Accelerator Laboratory) Yiheng Ye (SLAC)

Description

FACET-II requires operators to conduct multiple tasks for both injector startup and optimal performance at the experimental area. Injector startup tasks consume hours of beamtime, a significant cost for a multi-purpose facility. Moreover, beam tuning for plasma wakefield acceleration at the experimental area is a challenging and time-consuming task due to the longitudinal-transverse coupling at the W-chicane compressor. In this work, we present recent developments in software tools to automate injector startup tasks and sextupole tuning at the W-chicane. First, we demonstrate automated tasks for laser alignment, Schottky scan phasing, emittance optimization, beam steering, and energy spread minimization at the injector using Xopt routines. Additionally, we show an autonomous injector startup that integrates these tasks using an AI agent. Finally, we present sextupole tuning in the W-chicane using Xopt. These demonstrations can save a significant amount of beamtime spent on tuning and have been successful in producing desired outcomes in beam quality.

Authors

Juan Pablo Gonzalez-Aguilera (SLAC National Accelerator Laboratory) Yiheng Ye (SLAC) Dylan Kennedy (SLAC National Accelerator Laboratory) Zhe Zhang (SLAC) Sheldon Rego (Institut Polytechnique de Paris) Zack Buschmann (SLAC National Accelerator Laboratory) Ryan Loney (SLAC National Accelerator Laboratory) Doug Storey (SLAC) Brendan O'Shea (SLAC) Auralee Edelen (SLAC) Ryan Roussel (SLAC)

Presentation materials