Untriggered Swift-GRBs in Fermi/GBM data

The Fermi Gamma-Ray Burst Monitor (GBM) onboard the Fermi spacecraft currently operates on several trigger algorithms on various time scales and energy ranges. Motivated by the pursuit of faint Gamma-Ray Bursts (e.g. the elusive class of postulated low-luminosity GRBs), here we present the search for untriggered GRBs in the GBM data stream. To this end, I will demonstrate the methods and algorithms which have been developed by the GBM team. As a preliminary result, I am going to highlight the spectral analysis of GRBs which triggered the Swift satellite, but not GBM, and came from positions above the horizon, with a favorable orientation to at least one GBM detector. The properties of these GRBs are then compared to the full sample of GBM GRBs published in the GBM spectral catalogue. We estimate that the lower limit for untriggered GRBs in the GBM data is about 1.6 GRBs per month which corresponds to about 7% of the triggered GRBs

💡 Research Summary

The paper addresses the problem that the Fermi Gamma‑Ray Burst Monitor (GBM) may miss faint or low‑energy gamma‑ray bursts (GRBs) because its on‑board trigger algorithms are optimized for relatively bright, short‑timescale events. To explore the population of “untriggered” GRBs, the authors develop a ground‑based search pipeline that operates on the continuous CTIME data stream (0.256 s time resolution, coarse spectral resolution) recorded by GBM.

GBM consists of twelve NaI(Tl) detectors (8 keV–1 MeV) and two BGO detectors (150 keV–40 MeV). In flight, GBM runs 75 trigger algorithms defined by a combination of timescales (16 ms–4 s) and energy bands (25–50 keV, 50–300 keV, >100 keV, >300 keV). A trigger requires a statistically significant excess (typically 4 σ) in at least two detectors. Because the on‑board software can only model background over short intervals, it is vulnerable to rapid background changes caused by South Atlantic Anomaly (SAA) passages, Earth occultation, or high incident angles.

The authors focus on the period from 22 August 2008 to 6 January 2012, during which Swift detected 299 GRBs. Of these, 107 (36 %) were also triggered by GBM. After discarding events that occurred during SAA passages (30) or were Earth‑occulted or at incident angles > 60° (88), 74 Swift GRBs remained that could plausibly have been seen by GBM.

The ground‑based algorithm searches the CTIME data for excesses in the 50–300 keV band (the band where most GBM triggers occur) over timescales from 0.256 s to 8.192 s. It requires a 4 σ excess in one detector and a 3.8 σ excess in a second detector, mirroring the on‑board criteria but with a much more accurate background model. The background is fitted over the entire day using a spline, and the authors also model “occultation steps” caused by the rise and set of 92 known hard X‑ray/γ‑ray sources, folding each source’s photon spectrum through the detector response to predict the count‑rate change.

Applying this pipeline to the 74 candidate Swift bursts, the authors identify 17 untriggered GRBs (1 short, 16 long). Spectral analysis is performed on the long bursts using CSPEC data (1.024 s resolution, full 10–1000 keV coverage). Three spectral models are fitted: a simple power law (PL), a cutoff power law (COMP), and the Band function (BAND). The results show:

• Photon fluxes between 0.6 and 1.5 ph cm⁻² s⁻¹, placing these events at the faint end of the GBM flux distribution.
• Peak energies (Eₚ) ranging from ~64 keV to ~95 keV, i.e., in the lower tail of the GBM Eₚ distribution.
• Low‑energy photon indices (α) between –1.0 and –2.3, statistically indistinguishable from the full GBM sample.
• High‑energy indices (β) are only constrained for the few bursts fitted with COMP or BAND, and they also fall within the range of triggered GRBs.

The single short GRB (090305A) could not be spectrally characterized because its T₉₀ ≈ 0.3 s is shorter than the CSPEC time resolution. The authors note that GBM currently records Time‑Tagged Event (TTE) data only in limited sky regions; extending TTE to full‑time operation would improve detection of short, faint bursts and enable spectral analysis of such events.

Considering that Swift’s field of view is roughly four times smaller than GBM’s, the authors extrapolate that GBM’s on‑board trigger misses about 1.6 GRBs per month, corresponding to roughly 7 % of the GRBs it actually detects. This estimate highlights a non‑negligible population of faint, soft bursts that are invisible to the standard trigger but can be recovered with careful ground‑based analysis.

In summary, the study demonstrates that a refined ground‑based search of GBM CTIME data, equipped with a sophisticated background model and occultation corrections, can recover a modest but scientifically valuable sample of untriggered GRBs. These events populate the low‑flux, low‑Eₚ region of the GRB parameter space and provide a proof‑of‑concept for future systematic searches, especially once continuous TTE data become available. The work thus expands the effective sensitivity of GBM and contributes to a more complete census of the GRB population, including the elusive low‑luminosity class.