A demonstrator for a real-time AI-FPGA-based triggering system for sPHENIX at RHIC
2024
J. Kvapil, Giorgian Borca‐Tasciuc, Hannah Bossi, Kai Chen, Corrales Morales Yasser, H. Pereira Da Costa, C. L. Da Silva, J. M. Durham, X. Li, Youzuo Lin, M. X. Liu, Z. Shi, Dean Cameron, Harris Phil, Hen Or, Jheng Hao-Ren, Lee Yen-Jie, Roland Gunther, Y. Chen, Song Fu, Olvera Alejandro, Purschke Martin, Tran Nhan, Rigatti Micol, Schambach Joachim, Wuerfel Noah, Yu Dantong, Hao Callie, Pan Li, Xu Buqing, Zhang Hanqing
Abstract
The RHIC interaction rate at sPHENIX will reach around 3 MHz in pp collisions and requires the detector readout to reject events by a factor of over 200 to fit the DAQ bandwidth of 15 kHz. Some critical measurements, such as heavy flavor production in pp collisions, often require the analysis of particles produced at low momentum. This prohibits adopting the traditional approach, where data rates are reduced through triggering on rare high momentum probes. We explore a new approach based on real-time AI technology, adopt an FPGA-based implementation using a custom designed FELIX-712 board with the Xilinx Kintex Ultrascale FPGA, and deploy the system in the detector readout electronics loop for real-time trigger decision.
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