Speaker
Description
The NUTRIG project is dedicated to the development of advanced radio self-trigger methods for large-scale arrays such as the Giant Radio Array for Neutrino Detection (GRAND). The developed techniques are based on features of the radio emission of air showers to perform an efficient online rejection of background. We first describe two independent first-level trigger (FLT) methods that target the shape of transient radio pulses measured at the detection-unit level: A template-fitting approach and a convolutional neural network. We present trigger efficiencies and throughput tests of both FLT methods in controlled laboratory conditions, as well as in-field tests at GRAND prototypes. Next, we describe the second-level trigger (SLT), which utilizes FLT times and corresponding voltage amplitudes measured at the detection units to construct a trigger at the array level. We present offline performances of the SLT, which performs a coarse reconstruction of timing, direction, and polarization of the air shower. Finally, we outline our plans to integrate the combined FLT and SLT logic at GRANDProto300.
| Collaboration(s) | GRAND |
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