Next generation direct RF sampling LLRF control and monitoring system for linear accelerators

MODR005
22 Sept 2025, 17:00
15m
Red Lacquer Room (Palmer House Hilton Chicago)

Red Lacquer Room

Palmer House Hilton Chicago

17 East Monroe Street Chicago, IL 60603, United States of America
Contributed Oral Presentation MC05: FPGA and Embedded Systems MODR MC05 FPGA and Embedded Systems

Speaker

Chao Liu (SLAC National Accelerator Laboratory)

Description

The low-level RF (LLRF) systems for linear accelerating structures are typically based on heterodyne architectures. The linear accelerators normally have many RF stations and multiple RF inputs and outputs for each station, so the complexity and size of the LLRF system grows rapidly when scaling up. To meet the design goals of being compact and affordable for future accelerators, or upgrade of existing ones, we have developed and characterized the next generation LLRF (NG-LLRF) platform based on the RF system-on-chip (RFSoC) for S-band and C-band accelerating structures. The integrated RF data converters in RFSoC sample and generate the RF signals directly without any analogue mixing circuits, which significantly simplified the architecture compared with the conventional LLRF systems. We have performed high-power tests for the NG-LLRF with the S-band accelerating structure in the Next Linear Collider Test Accelerator (NLCTA) test facility at SLAC National Accelerator Laboratory and a C-band structure prototyped for Cool Cooper Collider (CCC). The NG-LLRF platform demonstrated pulse-to-pulse fluctuation levels considerably better than the requirements of the targeted applications and high precision and flexibility in generating and measuring the RF pulses. In this paper, the characterization results of the platform with different system architectures will be summarized and a selection of high-power test results of the NG-LLRF will be presented and analyzed.

Author

Chao Liu (SLAC National Accelerator Laboratory)

Co-authors

Emilio Nanni (SLAC National Accelerator Laboratory) Emma Snively (SLAC National Accelerator Laboratory) Kukhee Kim (SLAC National Accelerator Laboratory) Ryan Herbst (SLAC National Accelerator Laboratory)

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