An image-based array trigger for Imaging Atmospheric Cherenkov Telescope Arrays

TL;DR

This paper proposes a hardware-level distributed trigger system for next-generation atmospheric Cherenkov telescope arrays, using a novel image-based discriminator to efficiently differentiate gamma-ray events from background noise, reducing data rates.

Contribution

Introduction of a Distributed Intelligent Array Trigger (DIAT) that uses reduced imaging data and a parallax width discriminator for efficient event selection in Cherenkov telescope arrays.

Findings

Monte-Carlo simulations show high efficiency in background rejection.

The DIAT reduces data transmission by vetoing non-gamma events early.

The approach improves data handling for large, multi-telescope arrays.

Abstract

It is anticipated that forthcoming, next generation, atmospheric Cherenkov telescope arrays will include a number of medium-sized telescopes that are constructed using a dual-mirror Schwarzschild-Couder configuration. These telescopes will sample a wide ($8^{\circ}$) field of view using a densely pixelated camera comprising over $10^{4}$ individual readout channels. A readout frequency congruent with the expected single-telescope trigger rates would result in substantial data rates. To ameliorate these data rates, a novel, hardware-level Distributed Intelligent Array Trigger (DIAT) is envisioned. A copy of the DIAT operates autonomously at each telescope and uses reduced resolution imaging data from a limited subset of nearby telescopes to veto events prior to camera readout {and any subsequent network transmission of camera data that is required for centralized storage or aggregation}. We present the results of Monte-Carlo simulations that evaluate the efficacy of a "Parallax width" discriminator that can be used by the DIAT to efficiently distinguish between genuine gamma-ray initiated events and unwanted background events that are initiated by hadronic cosmic rays.