Automatic detection of long-duration transients in Fermi-GBM data

TL;DR

This paper presents a new automated method for detecting long-duration and weak transient events in Fermi-GBM data, improving sensitivity and coverage for multi-messenger astronomy.

Contribution

It introduces a novel trigger algorithm and analysis pipeline capable of identifying long-duration transients with high sensitivity, including previously undetectable signals.

Findings

Detected over 300 untriggered transient signals in real data

Successfully identified a long-duration pulsar emission from Vela X-1

Demonstrated sensitivity down to sub-Crab intensities

Abstract

In the era of time-domain, multi-messenger astronomy, the detection of transient events on the high-energy electromagnetic sky has become more important than ever. Previous attempts to systematically search for onboard-untriggered events in the data of Fermi-GBM have been limited to short-duration signals with variability time scales smaller than ~1 min due to the dominance of background variations on longer timescales. In this study, we aim at the detection of slowly rising or long-duration transient events with high sensitivity and full coverage of the GBM spectrum. We make use of our earlier developed physical background model, propose a novel trigger algorithm with a fully automatic data analysis pipeline. The results from extensive simulations demonstrate that the developed trigger algorithm is sensitive down to sub-Crab intensities, and has a near-optimal detection performance. During a two month test run on real Fermi-GBM data, the pipeline detected more than 300 untriggered transient signals. For one of these transient detections we verify that it originated from a known astrophysical source, namely the Vela X-1 pulsar, showing pulsed emission for more than seven hours. More generally, this method enables a systematic search for weak and/or long-duration transients.