Speaker
Description
At LCLS, delivering a stable X-ray beam to the experiment still depends on skilled operator time across a long chain of accelerator and beamline systems; and with LCLS-II-HE, manual setup is becoming harder to sustain. At MFX we are building autoMFX around three pieces that are starting to work together: BES-funded ILLUMINE for autonomous photon-beam tuning; language-model assistants that let operators ask questions and issue goals in natural language while tracking how upstream changes affect what the detectors actually measure; and online analysis workflows so tuning is judged against diffraction and spectroscopy quality, not instrument controls readbacks alone.
We have been exercising this stack during real operator shifts at MFX—testing agent tools for device access, shift logging, and analysis setup alongside ILLUMINE tuning runs. With MFX instrument colleagues we are now aiming for a July 2026 demonstration in which agents help carry beam delivery, alignment, geometry, and online crystallography analysis, keeping expert operators in the loop but spending less time on repetitive steps.
What is still difficult on scarce user beamtime is closing the loop between the accelerator and the photon side: fusing source, beamline, and science-side signals, and trying control strategies in a digital twin before actuating hardware. An AI/ML accelerator test facility is where we would iterate on that bridge: controlled detune-and-recover tests, shared controls across the delivery chain, and staged rollout from shadow operation to bounded closed-loop control, before scaling to MFX and LCLS-II-HE.
