J/ApJ/777/132 A search for progenitors of short GRBs (Dichiara+, 2013) ================================================================================ A search for pulsations in short gamma-ray bursts to constrain their progenitors. Dichiara S., Guidorzi C., Frontera F., Amati L. =2013ApJ...777..132D ================================================================================ ADC_Keywords: Gamma rays Keywords: accretion, accretion disks; gamma-ray burst: general; methods: data analysis; techniques: photometric Abstract: We searched for periodic and quasi-periodic signals in the prompt emission of a sample of 44 bright short gamma-ray bursts (GRBs) detected with Fermi/GBM, Swift/BAT, and CGRO/BATSE. The aim was to look for the observational signature of quasi-periodic jet precession, which is expected from black hole (BH)-neutron star (NS) mergers, but not from double NS systems. Thus, this kind of search holds the key to identifying the progenitor systems of short GRBs and, in the interim before gravitational wave detectors become on-lines, represents the only direct way to constrain the progenitors. We tailored our search to the nature of the expected signal by properly stretching the observed light curves by an increasing factor with time, after calibrating the technique with synthetic curves. None of our GRBs showed evidence for periodic or quasi-periodic signals. In particular, for the seven unambiguously short GRBs with the best signal-to-noise ratios, we obtained significant upper limits to the amplitude of the possible oscillations. This result suggests that BH-NS systems do not dominate the population of short GRB progenitors, as described by the kinematic model of Stone et al. (2013PhRvD..87h4053S). Description: We took all the events observed by the Fermi/GBM from 2008 July to 2012 December. We selected the SGRBs by requiring T_90_<3s, and ended up with 160 GRBs, 18 of which have a minimum signal-to-noise ratio (S/N) of 20, as computed over the T_5{sigma}_ interval. See section 2.1 The same selection criteria were applied to the Swift/BAT sample using all the events detected up to early 2013 June (12 GRBs selected). 14 SGRBs whose profiles were extracted in the 20-2000keV energy range were selected from BATSE/CGRO (Paciesas+, 1999, IX/20). File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file table1.dat 152 74 Best-fitting model and parameters for each 44 short duration gamma-ray burst (SGRB) of the total sample -------------------------------------------------------------------------------- See also: IX/20 : The Fourth BATSE Burst Revised Catalog (Paciesas+ 1999) J/ApJS/216/32 : Localizations of GRBs with Fermi GBM (Connaughton+, 2015) J/ApJS/211/13 : The second Fermi/GBM GRB catalog (4yr) (von Kienlin+, 2014) J/ApJS/208/21 : The BATSE 5B GRB spectral catalog (Goldstein+, 2013) J/ApJS/207/38 : IPN localizations of Konus short GRBs (Pal'shin+, 2013) J/MNRAS/431/3608 : BeppoSAX/GRBM and Fermi/GBM long GRBs (Dichiara+, 2013) J/ApJS/207/39 : IPN supplement to the Fermi GBM (Hurley+, 2013) J/ApJ/756/112 : Fermi/GBM GRB time-resolved spectral analysis (Lu+, 2012) J/ApJ/748/134 : Variability in BATSE GRB light curves (Gao+, 2012) J/ApJS/199/18 : The Fermi GBM catalog (Paciesas+, 2012) J/ApJS/195/2 : The second Swift BAT GRB catalog (BAT2) (Sakamoto+, 2011) J/A+A/525/A53 : GBM parameters for detected FERMI bursts (Guetta+, 2011) J/ApJ/740/104 : BATSE GRB pulse catalog - preliminary data (Hakkila+, 2011) J/ApJ/711/495 : Durations of Swift/BAT GRBs (Butler+, 2010) J/ApJS/134/385 : Supplement to the BATSE GRB catalogs (Kommers+, 2001) J/ApJ/508/314 : Gamma-ray bursts types (Mukherjee+, 1998) Byte-by-byte Description of file: table1.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 7 A7 --- GRB Gamma-ray Burst identifier (YYMMDDA) 10 A1 --- r_GRB [d-f] Detection origin (1) 12- 14 A3 --- Mod Best PDS fit model: "pl" or "bpl" (2) 16- 20 F5.3 [-] logN [0.9/5.3] Log of Power Density Spectrum (PDS) normalization (2) 22- 26 F5.3 [-] e_logN [0.1/1.5] Lower 90% confidence level on logN 28- 32 F5.3 [-] E_logN [0.1/7.8] Upper 90% confidence level on logN 34- 39 F6.3 [Hz] logfb [-0.8/1.5]? Log of PDS frequency break parameter f_b_ (2) 41- 45 F5.3 [Hz] e_logfb [0.09/5]? Lower 90% confidence level on logfb 47- 51 F5.3 [Hz] E_logfb [0.08/0.9]? Upper 90% confidence level on logfb 53- 57 F5.3 --- alpha [0.8/6.8] PDS slope {alpha} (2) 59- 63 F5.3 --- e_alpha [0.1/3] Lower 90% confidence level on alpha 65- 69 F5.3 --- E_alpha [0.1/7] Upper 90% confidence level on alpha 71- 75 F5.3 --- B [1.5/2.5] White (poissoinian) noise level parameter 77- 81 F5.3 --- e_B [0.05/1.3] Lower 90% confidence level on B 83- 87 F5.3 --- E_B [0.05/1] Upper 90% confidence level on B 89- 93 F5.3 --- pTR [0.01/1] Significance associated to T_R_ statistic 95- 99 F5.3 --- pAD [0.1/1] Significance of the Anderson-Darling test 101-105 F5.3 --- pKS [0.1/1] Significance of the Kolmogorov-Smirnov test 107-111 F5.3 --- Ratio [0.006/0.6] Ratio of Pulse amplitude A_2{sigma}_/A_peak_ 113-117 F5.3 s T90 [0.1/2.7] Burst duration 119-124 F6.3 s t0 [-3/0.03] Start time t_0_ 126-131 F6.3 s t1 [0.1/3] Stop time t_1_ 133 A1 --- f_HR [h] ODS extraction > T_5{sigma}_ (3) 135-140 F6.3 --- HR [0.6/10.8] Hardness ratio (4) 142-146 F5.3 --- e_HR [0.07/1.1] The 1{sigma} confidence level in HR 148-152 F5.3 --- pSh [0.006/1] Probability of belonging to short class of GRB -------------------------------------------------------------------------------- Note (1): Flag as follows: d = Detected by Swift/BAT (24 rows, 12 GRBs); e = Detected by Fermi/GBM (36 rows, 18 GRBs); f = Detected by CGRO/BATSE (14 GRBs). Note (2): We studied the power density spectrum (PDS) of each light curve in two different ways. PDSs were calculated adopting the Leahy normalization (Leahy et al. 1983ApJ...266..160L). To fit the PDSs, we used the technique set up by Vaughan (2010MNRAS.402..307V) based on a Bayesian treatment with Markov Chain Monte Carlo techniques. Two analytical models were assumed to describe the PDS continuum (section 3): * a simple power-law plus constant (pl) [Equation (1)]: S_PL_(f)=N.f^-{alpha}^+B * or a broken power-law plus constant (bpl) [Equation (2)] with low-frequency index fixed to zero: S_BPL_(f)=N[1+(f/f_b_)^{alpha}^]^-1^+B Note (3): In this case the time interval of PDS extraction is larger then the T_5{sigma}_ interval to fit properly the continuum shape. Note (4): Hardness ratio is defined as the fluence ratios: * S(50-100keV)/S(25-50keV) for Swift/BAT * S(100-300keV)/S(50-100keV) for Fermi/GBM and CGRO/BATSE -------------------------------------------------------------------------------- History: From electronic version of the journal ================================================================================ (End) Greg Schwarz [AAS], Emmanuelle Perret [CDS] 09-Apr-2015