11–13 Jun 2024
CERN
Europe/Zurich timezone
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A Neural Network-based trigger for detecting ultra-high-energy neutrinos for RNO-G and IceCube-Gen2

12 Jun 2024, 11:15
30m
30/7-018 - Kjell Johnsen Auditorium (CERN)

30/7-018 - Kjell Johnsen Auditorium

CERN

190
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Algorithm implementation in HDL and HLS Algorithm implementation

Speakers

Pawel Marciniewski (Uppsala University)Mr Pawel Marciniewski (Uppsala University)

Description

Ultra-high-energy (UHE) neutrinos can be detected via radio antennas installed in polar ice sheets. In this work, we present a trigger system utilizing a convolutional neural network to process the antenna signals. This system can increase the neutrino detection rate by up to a factor of two at negligible additional costs, which would substantially advance UHE neutrino science. The trigger algorithm written in pure VHDL will be implemented in an existing digitizer hardware utilizing a 4-channel 500Msps flash ADC and a Cyclone V FPGA from Intel (Altera). Incoming data are processed in-flight by 45 DSP blocks, delivering trigger with a latency of a few clock cycles, thus meeting the main design requirement of low latency. We also present a relation between the clock speed and the power consumption, another critical factor. Finally, we give an outlook of new hardware development and expected performance gains from increased computing resources of more powerful FPGAs.

Talk's Q&A During the talk
Talk duration 20'+10'
Will you be able to present in person? Yes

Authors

Pawel Marciniewski (Uppsala University) Mr Pawel Marciniewski (Uppsala University)

Presentation materials