Graphene-based, Frequency-Domain Self-Trigger for Low SNR Air Showers-induced Pulses

Abstract

In this paper we introduce a frequency-domain pulse detection method that is suitable for in-situ implementation at detector-level, for low-power, self-triggered air shower detectors. We propose a graphene-based architecture, and demonstrate its correct operation by means of SPICE simulations. The utilized graphene-based devices operate at low supply voltage, consume low energy per spike, and exhibit small footprints, which are essential properties for large-scale, energy-efficient implementations. The proposed method is particularly effective for very low (Signal-to-Noise Ratio) SNR scenarios, and is broadband noise resilient up to a certain extent, and (Radio Frequency) RF narrowband noise agnostic. Comparison results against time-domain signal-over-threshold trigger indicates that the proposed method can outperform its counterpart in terms of trigger efficiency by up to 26× and 47×, when using 1 and 2 frequency components, respectively, especially for very low SNR scenarios (up to -42 dB) where time-domain methods are largely impaired. Furthermore, the proposed method does not require RF filtering in advance, and can coexist with other noise pulses. Thus, high detection efficiency that goes in tandem with high purity (low number of false positives) becomes tenable with proposed approach.