GARD RF Roadmap Update - RF Controls
It has been almost a decade since the publication of the decadal GARD RF Roadmap in 2017. In the intervening years, our community has made significant progress in advancing RF accelerator technologies, contributing to the HEP mission and benefiting the broader DOE mission.
The landscape of our community has also evolved considerably, notably with the recent release of a new P5 report at the end of 2023. In light of these changes, and under the direction of the GARD program manager Derun Li, we are launching an initiative to update the RF Roadmap aimed at identifying high impact R&D topics; near, mid and far term goals; and ascertain the community's most urgent priorities and workforce development needs.
This process will require strong engagement with the community. This indico page is for one of four virtual meetings focused on subtopics within GARD RF. This meeting will cover aspects of RF controls from current project needs to ongoing developments in hardware and software though machine learning and artificial intelligence.
LLRF Control. There will be a series of summary/overview talks on ongoing R&D, needs, and applications. The community will assess progress to date compared to the current DOE GARD RF Roadmap. Additionally, there will be time for contributed 5-min 1-2 slide talks to make sure we capture important topics. If you are interested in presenting a contributed talk, please email us.
At all stages we welcome your input and feedback. Please do not hesitate to reach out directly to us. Please also forward this page to your colleagues who may be interested.
Philip Varghese (FNAL)
Alessandro Ratti (LBNL)
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Notes from LLRF25 WorkshopSpeaker: Philip Varghese (Fermi National Accelerator Laboratory)
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-: Challenges in future accelerators and colliders
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EIC RF controls and challengesSpeaker: Kevin Mernick (BNL)
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LLRF Controls needs for PIP-II/LBNF-DUNESpeaker: Philip Varghese (Fermilab)
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Hardware Develpoment and signal processing
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Direct RF sampling based LLRF system for future acceleratorsSpeaker: Chao Liu (SLAC)
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Experience with CW SRF controls in the CEBAF acceleratorSpeaker: Tomasz Plawski (Jefferson Lab)
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Intelligent platforms for LLRFSpeaker: Qiang Du (LBNL)
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6
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10:30
Break
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Machine Learning and AI: Opportunities to improve performance
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Classical and AI-assisted Resonance Control for SRF CavitiesSpeaker: Crispin Contreras-Martinez (FNAL)
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Machine Learning and AI applications in Accelerator SystemsSpeaker: Jonathan Edelen (RadiaSoft)
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Bridge the Gap: Physics-Guided ML and Data-Driven Control for Lasers and AcceleratorsSpeaker: Dan Wang (LBNL)
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Anomaly Detection in the CERN Proton Synchrotron RF Systems Using Machine LearningSpeaker: Joel Wulff (CERN)
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RF Fault Prediction and Anomaly DetectionSpeaker: Adam Carpenter (JLAB)
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9
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12:05
Break
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Beyond Accelerators, Short Talks and Open Discussion
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14
LLRF technologies for quantum computingSpeaker: Gang Huang (LBNL)
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15
Qubit Measurements at Fermilab SQMSSpeaker: Paul Heidler (Fermilab)
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Report from the education session at the LLRF workshopSpeaker: Joshua Settle (JLAB)
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17
RF Control - Short Talks
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a) LLRF R&D at DESYSpeakers: Julien Branlard (DESY), Philip Varghese (Fermilab)
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b) RF Control challenges for the ILCSpeakers: Mathieu Omet (KEK), Philip Varghese (Fermilab), Toshihiro Matsumoto (KEK)
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c) Narrowband Active Noise Cancellation (NANC) at LCLS-IISpeakers: Andy Benwell (SLAC), Jorge Diaz-Cruz (SLAC)
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d) Leveraging AI Tools in RF OperationsSpeaker: Kunjir Shiriraj (FRIB)
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