J/A+A/589/A98 Swift GRBs individual power density spectra (Guidorzi+, 2016)
Individual power density spectra of Swift gamma-ray bursts.
Guidorzi C., Dichiara S., Amati L.
<Astron. Astrophys. 589, A98 (2016)>
=2016A&A...589A..98G 2016A&A...589A..98G (SIMBAD/NED BibCode)
ADC_Keywords: Gamma rays ; Spectroscopy
Keywords: gamma-ray burst: general - methods: statistical
Abstract:
Timing analysis can be a powerful tool for shading light on the still
obscure emission physics and geometry of the prompt emission of
gamma-ray bursts (GRBs).
Fourier power density spectra (PDS) characterise time series as
stochastic processes and can be used to search for coherent pulsations
and, more in general, to investigate the dominant variability
timescales in astrophysical sources. Because of the limited duration
and of the statistical properties involved, modelling the PDS of
individual GRBs is challenging, and only average PDS of large samples
have been discussed in the literature thus far. We aim at
characterising the individual PDS of GRBs to describe their
variability in terms of a stochastic process, to explore their
variety, and to carry out for the first time a systematic search for
periodic signals and for a link between PDS properties and other GRB
observables.
We present a Bayesian procedure which uses a Markov chain Monte Carlo
technique and apply it to study the individual power density spectra
of 215 bright long GRBs detected with the Swift Burst Alert Telescope
in the 15-150keV band from January 2005 to May 2015.
The PDS are modelled with a power-law either with or without a break.
Two classes of GRBs emerge: with or without a unique dominant time
scale.
A comparison with active galactic nuclei (AGNs) reveals similar
distributions of PDS slopes. Unexpectedly, GRBs with subsecond
dominant timescales and duration longer than a few ten seconds in the
source frame appear to be either very rare or altogether absent. Three
GRBs are found with possible evidence for periodic signal at
3.0-3.2σ (Gaussian) significance, corresponding to a multi-trial
chance probability of ∼1%. Thus, we found no compelling evidence for
periodic signal in GRBs.
The analogy between the PDS of GRBs and of AGNs could tentatively hint
at similar stochastic processes that rule BH accretion across
different BH mass scales and objects.
In addition, we find evidence that short dominant timescales and
duration are not completely independent of each other, in contrast
with commonly accepted paradigms.
Description:
Time intervals, redshifts, best-fit parameters of the power density
spectra (PDS) for 215 bright long GRBs observed with the Swift Burst
Alert Telescope (BAT) from January 2005 to May 2015.
Parameters refer to two alternative PDS models: either a power-law
(PL) or a bent power-law (BPL) plus a constant background.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table1.dat 70 215 Time intervals for calculating the PDS referred
to trigger times, T90, redshifts
refs.dat 47 59 References
table2.dat 126 215 Best fit model and parameters (1 sigma) for
total energy passband (15-150keV)
table3.dat 118 215 Best fit model and parameters (1 sigma) for
soft energy channel (15-50keV)
table4.dat 118 215 Best fit model and parameters (1 sigma) for
hard energy channel (50-150keV)
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See also:
J/ApJ/777/132 : A search for progenitors of short GRBs (Dichiara+, 2013)
J/A+A/589/A97 : GRBs Ep and Fourier PDS slope correlation (Dichiara+, 2016)
Byte-by-byte Description of file: table1.dat
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Bytes Format Units Label Explanations
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1- 7 A7 --- GRB GRB name
11- 18 F8.3 s Tstart Start since the trigger time
22- 29 F8.3 s Tstop Stop since the trigger time
33- 40 F8.3 s T7sigma Duration of T(7sigma) interval
44- 51 F8.3 s T90 Duration of T90 interval
55- 57 A3 --- Cat Catalogue name used for T90 (1)
60- 65 F6.4 --- z ?=- GRB Redshift (NA when not available)
69- 70 I2 --- r_z ?=- Reference for redshift, in refs.dat file
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Note (1): Code for Catalogue name used for T90 as follows:
S11 = from Sakamoto et al., 2011, Cat. J/ApJS/195/2
GCN = from Swift-BAT refined GCN circulars.
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Byte-by-byte Description of file: refs.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 2 I2 --- Ref Reference code
4- 22 A19 --- BibCode BibCode
24- 47 A24 --- Aut Author's name
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Byte-by-byte Description of file: table2.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
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1- 7 A7 --- GRB GRB name
10- 12 A3 --- Model Best-fit model of the PDS
16- 21 F6.3 [-] logN Best-fit log10(normalisation) of the PDS
26- 30 F5.3 [-] e_logN Error (1 sigma) on logN
35- 40 F6.3 [Hz] logfb ?=- Best-fit log10(break frequency/Hz)
(--- when not available)
45- 49 F5.3 [Hz] e_logfb ? Error (1 sigma) on logfb
54- 58 F5.3 --- alpha Best-fit PDS slope (model parameter alpha)
63- 67 F5.3 --- e_alpha Error (1 sigma) on alpha
75- 79 F5.3 --- B Best-fit white noise level (model param B)
84- 88 F5.3 --- e_B Error (1 sigma) on B
94- 98 F5.3 --- pTR P-value of TR statistic
104-108 F5.3 --- pAD P-value of Anderson-Darling statistic
114-118 F5.3 --- pKS P-value of Kolmogorov-Smirnov statistic
125-126 I2 --- Np Number of pulses as determined with MEPSA
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Byte-by-byte Description of file: table3.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 7 A7 --- GRB GRB name
10- 12 A3 --- Model Best-fit model of the PDS
16- 21 F6.3 [-] logN Best-fit log10(normalisation) of the PDS
26- 30 F5.3 [-] e_logN Error (1 sigma) on logN
35- 40 F6.3 [Hz] logfb ?=- Best-fit log10(break frequency/Hz)
(--- when not available)
45- 49 F5.3 [Hz] e_logfb ? Error (1 sigma) on logfb
54- 58 F5.3 --- alpha Best-fit PDS slope (model parameter alpha)
63- 67 F5.3 --- e_alpha Error (1 sigma) on alpha
75- 79 F5.3 --- B Best-fit white noise level (model param B)
84- 88 F5.3 --- e_B Error (1 sigma) on B
94- 98 F5.3 --- pTR P-value of TR statistic
104-108 F5.3 --- pAD P-value of Anderson-Darling statistic
114-118 F5.3 --- pKS P-value of Kolmogorov-Smirnov statistic
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Byte-by-byte Description of file: table4.dat
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Bytes Format Units Label Explanations
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1- 7 A7 --- GRB GRB name
10- 12 A3 --- Model Best-fit model of the PDS
16- 21 F6.3 [-] logN Best-fit log10(normalisation) of the PDS
26- 30 F5.3 [-] e_logN Error (1 sigma) on logN
35- 40 F6.3 [Hz] logfb ?=- Best-fit log10(break frequency/Hz)
(--- when not available)
45- 49 F5.3 [Hz] e_logfb ? Error (1 sigma) on logfb
54- 58 F5.3 --- alpha Best-fit PDS slope (model parameter alpha)
63- 67 F5.3 --- e_alpha Error (1 sigma) on Alpha
75- 79 F5.3 --- B Best-fit white noise level (model param B)
84- 88 F5.3 --- e_B Error (1 sigma) on B
94- 98 F5.3 --- pTR P-value of TR statistic
104-108 F5.3 --- pAD P-value of Anderson-Darling statistic
114-118 F5.3 --- pKS P-value of Kolmogorov-Smirnov statistic
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Acknowledgements:
Cristiano Guidorzi, guidorzi(at)fe.infn.it
(End) C. Guidorzi [Ferrara Univ., Italy], P. Vannier [CDS] 21-Mar-2016