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Register a new userAnalysis of Sub-threshold Short Gamma-ray Bursts in Fermi GBM Data
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The Fermi Gamma-ray Burst Monitor (GBM) is currently the most prolific detector of Gamma-Ray Bursts (GRBs). Recently the detection rate of short GRBs (SGRBs) has been dramatically increased through the use of ground-based searches that analyze GBM continuous time tagged event (CTTE) data. Here we examine the efficiency of a method developed to search CTTE data for sub-threshold transient events in temporal coincidence with LIGO/Virgo compact binary coalescence triggers. This targeted search operates by coherently combining data from all 14 GBM detectors by taking into account the complex spatial and energy dependent response of each detector. We use the method to examine a sample of SGRBs that were independently detected by the Burst Alert Telescope on board the Neil Gehrels Swift Observatory, but which were too intrinsically weak or viewed with unfavorable instrument geometry to initiate an on-board trigger of GBM. We find that the search can successfully recover a majority of the BAT detected sample in the CTTE data. We show that the targeted search of CTTE data will be crucial in increasing the GBM sensitivity, and hence the gamma-ray horizon, to weak events such as GRB 170817A. We also examine the properties of the GBM signal possibly associated with the LIGO detection of GW150914 and show that it is consistent with the observed properties of other sub-threshold SGRBs in our sample. We find that the targeted search is capable of recovering true astrophysical signals as weak as the signal associated with GW150914 in the untriggered data.
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We study the spectral evolution of 13 short duration Gamma Ray Bursts (GRBs) detected by the Gamma Burst Monitor (GBM) on board Fermi. We study spectra resolved in time at the level of 2-512 ms in the 8 keV-35 MeV energy range. We find a strong correlation between the observed peak energy Ep and the flux P within individual short GRBs. The slope of the Ep P^s correlation for individual bursts ranges between ~0.4 and ~1. There is no correlation between the low energy spectral index and the peak energy or the flux. Our results show that in our 13 short GRBs Ep evolves in time tracking the flux. This behavior is similar to what found in the population of long GRBs and it is in agreement with the evidence that long GRBs and (the still few) short GRBs with measured redshifts follow the same rest frame Ep-Liso correlation. Its origin is most likely to be found in the radiative mechanism that has to be the same in both classes of GRBs.
The Fermi GBM catalog provides a large database with many measured variables that can be used to explore and verify gamma-ray burst classification results. We have used Principal Component Analysis and statistical clustering techniques to look for clustering in a sample of 801 gamma-ray bursts described by sixteen classification variables. The analysis recovers what appears to be the Short class and two long-duration classes that differ from one another via peak flux, with negligible variations in fluence, duration and spectral hardness. Neither class has properties entirely consistent with the Intermediate GRB class. Spectral hardness has been a critical Intermediate class property. Rather than providing spectral hardness, Fermi GBM provides a range of fitting variables for four different spectral models; it is not intuitive how these variables can be used to support or disprove previous GRB classification results.
Some short GRBs are followed by longer extended emission, lasting anywhere from ~10 to ~100 s. These short GRBs with extended emission (EE) can possess observational characteristics of both short and long GRBs (as represented by GRB 060614), and the traditional classification based on the observed duration places some of them in the long GRB class. While GRBs with EE pose a challenge to the compact binary merger scenario, they may therefore provide an important link between short and long duration events. To identify the population of GRBs with EE regardless of their initial classifications, we performed a systematic search of short GRBs with EE using all available data (up to February 2013) of both Swift/BAT and Fermi/GBM. The search identified 16 BAT and 14 GBM detected GRBs with EE, several of which are common events observed with both detectors. We investigated their spectral and temporal properties for both the spikes and the EE, and examined correlations among these parameters. Here we present the results of the systematic search as well as the properties of the identified events. Finally, their properties are also compared with short GRBs with EE observed with BATSE, identified through our previous search effort. We found several strong correlations among parameters, especially when all of the samples were combined. Based on our results, a possible progenitor scenario of two-component jet is discussed.
The initial pulse complex (IPC) in short gamma-ray bursts is sometimes accompanied by a softer, low-intensity extended emission (EE) component. In cases where such a component is not observed, it is not clear if it is present but below the detection threshold. Using Bayesian Block (BB) methods, we measure the EE component and show that it is present in one quarter of a Swift/BAT sample of 51 short bursts, as was found for the Compton/BATSE sample. We simulate bursts with EE to calibrate the BAT threshold for EE detection and show that this component would have been detected in nearly half of BAT short bursts if it were present, to intensities ~ 10^-2 counts cm^-2 s^-1, a factor of five lower than actually observed in short bursts. In the BAT sample the ratio of average EE intensity to IPC peak intensity, Rint, ranges over a factor of 25, Rint ~ 3 x 10^-3 to 8 x 10^-2. In comparison, for the average of the 39 bursts without an EE component, the 2-sigma upper limit is Rint < 8 x 10^-4. These results suggest that a physical threshold effect operates near Rint ~ few x 10^-3, below which the EE component is not manifest.
The capability of the Fermi Gamma-ray Burst Monitor (GBM) to localize gamma-ray bursts (GRBs) is evaluated for two different automated algorithms: the GBM Teams RoboBA algorithm and the independently developed BALROG algorithm. Through a systematic study utilizing over 500 GRBs with known locations from instruments like Swift and the Fermi LAT, we directly compare the effectiveness of, and accurately estimate the systematic uncertainty for, both algorithms. We show simple adjustments to the GBM Teams RoboBA, in operation since early 2016, yields significant improvement in the systematic uncertainty, removing the long tail identified in the systematic, and improves the overall accuracy. The systematic uncertainty for the updated RoboBA localizations is $1.8^circ$ for 52% of GRBs and $4.1^circ$ for the remaining 48%. Both from public reporting by BALROG and our systematic study, we find the systematic uncertainty of $1-2^circ$ quoted in GCN circulars for bright GRBs localized by BALROG is an underestimate of the true magnitude of the systematic, which we find to be $2.7^circ$ for 74% of GRBs and $33^circ$ for the remaining 26%. We show that, once the systematic uncertainty is considered, the RoboBA 90% localization confidence regions can be more than an order of magnitude smaller in area than those produced by BALROG.
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