J/ApJ/746/170 Follow-up resources for high-redshift GRBs (Morgan+, 2012)
Rapid, machine-learned resource allocation: application to high-redshift
gamma-ray burst follow-up.
Morgan A.N., Long J., Richards J.W., Broderick T., Butler N.R., Bloom J.S.
<Astrophys. J., 746, 170 (2012)>
=2012ApJ...746..170M 2012ApJ...746..170M
ADC_Keywords: Gamma rays ; Redshifts
Keywords: gamma-ray burst: general - methods: data analysis -
methods: statistical
Abstract:
As the number of observed gamma-ray bursts (GRBs) continues to grow,
follow-up resources need to be used more efficiently in order to
maximize science output from limited telescope time. As such, it is
becoming increasingly important to rapidly identify bursts of interest
as soon as possible after the event, before the afterglows fade beyond
detectability. Studying the most distant (highest redshift) events,
for instance, remains a primary goal for many in the field. Here, we
present our Random Forest Automated Triage Estimator for GRB redshifts
(RATE GRB-z) for rapid identification of high-redshift candidates
using early-time metrics from the three telescopes onboard Swift.
While the basic RATE methodology is generalizable to a number of
resource allocation problems, here we demonstrate its utility for
telescope-constrained follow-up efforts with the primary goal to
identify and study high-z GRBs. For each new GRB, RATE GRB-z provides
a recommendation--based on the available telescope time--of whether
the event warrants additional follow-up resources. We train RATE GRB-z
using a set consisting of 135 Swift bursts with known redshifts, only
18 of which are z > 4. Cross-validated performance metrics on these
training data suggest that ∼56% of high-z bursts can be captured from
following up the top 20% of the ranked candidates, and ∼84% of high-z
bursts are identified after following up the top ∼40% of candidates.
We further use the method to rank 200 + Swift bursts with unknown
redshifts according to their likelihood of being high-z.
Description:
We collated data on all Swift GRBs with rapidly available BAT data up
to and including GRB 100621A - 471 in total. Specifically, this
excludes bursts which were not identified in real time due to the
event being below the standard triggering threshold or occurring while
the satellite was slewing to a new location. Of the remaining long
bursts in our sample, 135 had reliable redshifts (Table 2) and were
thus included in our training data set (Table 3). The additional 212
long bursts without secure redshift determinations are explored
further in Section 5.1 (Table 4).
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table2.dat 42 135 Training data redshifts
table3.dat 109 135 Training data
table4.dat 118 203 Test data
refs.dat 50 145 References
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See also:
J/MNRAS/421/2692 : Optical/NIR observations of GRB 080310 (Littlejohns+, 2012)
J/ApJ/731/103 : Redshift catalog for Swift long GRBs (Xiao+, 2011)
J/ApJS/195/2 : The second Swift BAT GRB catalog (BAT2) (Sakamoto+, 2011)
J/MNRAS/406/2473 : Photometry of GRB 071025 (Perley+, 2010)
J/ApJ/720/1513 : The afterglows of Swift-era GRBs. I. (Kann+, 2010)
J/ApJ/711/495 : Durations of Swift/BAT GRBs (Butler+, 2010)
J/ApJ/690/163 : The first Swift UV-Opt GRB afterglow catalog (Roming+, 2009)
J/ApJ/704/1405 : Testing the Epeak-Eiso relation for GRBs (Krimm+, 2009)
J/PAZh/35/10 : Gamma-ray bursts with known redshifts (Badjin+, 2009)
J/MNRAS/397/1177 : Swift-XRT observations of GRBs (Evans+, 2009)
J/ApJ/642/L99 : R-band photometry of GRB 060206 (Wozniak+, 2006)
J/A+A/427/87 : List of GRBs (Gorosabel+, 2004)
J/ApJ/609/935 : Gamma-ray burst formation rate (Yonetoku+, 2004)
Byte-by-byte Description of file: table2.dat
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Bytes Format Units Label Explanations
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1- 7 A7 --- GRB GRB identifier (YYMMDDA)
9- 16 E8.3 --- Qhat-tr [0/1] Training decision criterion (G1)
18- 24 F7.5 --- z [0.0331/8.2] Redshift
26- 42 A17 --- r_z Reference(s) for z (see refs.dat file)
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Byte-by-byte Description of file: table[34].dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 7 A7 --- GRB GRB identifier (YYMMDDA)
9- 17 E9.3 --- alpha [-2/5]? Power-law index α (1)
18 A1 --- f_alpha [?] Indicates unknown alpha
20- 27 E8.3 keV Epeak [11/1220] Energy at which most photons are
emitted (1)
29- 36 E8.3 mJ/m2 S Total gamma-ray (15-350 keV) fluence (1)
38- 45 E8.3 --- S/N [4.6/725] Maximum signal-to-noise (1)
47- 55 E9.3 10+22/cm2 NH ? Excess neutral hydrogen column (2)
56 A1 --- f_NH [?] Indicates unknown NH
58- 65 E8.3 s T90 [2.2/639] Burst duration (1)
67- 74 E8.3 --- sig [5.64/25.8] Significance of BAT image (3)
76- 83 E8.3 ct/s Rpeak [47/18400] BAT peak count rate
85- 87 A3 --- Trig [yes/no ] Rate trigger?
89- 96 E8.3 s tBAT [0.06/320] Early time estimate of burst
duration (4)
98-100 A3 --- UVOT [yes/no ] UVOT detection?
102-109 E8.3 --- Ppz [0/0.31] Fraction of posterior probability
at z>4 (5)
111-118 E8.3 --- Qhat [0/1]? Decision criterion (G1)
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Note (1): the parameters to model the are:
α = the power-law index before the peak of the band-function fit
Epeak = the energy at which most of the photons are emitted
S = the total γ-ray flux integrated over the duration of
the burst
S/N = the maximum signal to noise achieved over the duration of
the light curve
T90 = a measure of the burst duration (containing 90% of the total
background-subtracted flux)
Note (2): Excess above the galactic value, as inferred from XRT PC data.
Note (3): expressed in σ, from the on-board reconstruction of the image.
Note (4): Inferred from rapidly available BAT data.
Note (5): Posterior probability redshift distributions calculated
from Butler et al. (2010, Cat. J/ApJ/711/495).
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Byte-by-byte Description of file: refs.dat
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Bytes Format Units Label Explanations
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1- 5 A5 --- Ref Reference code
7- 25 A19 --- BibCode Bibcode
27- 50 A24 --- Aut Author's name(s)
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Global notes:
Note (G1): Follow-up would be recommended if this value is less than the
desired fraction of bursts to follow-up. See section 3.2 for further
explanations.
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History:
From electronic version of the journal
(End) Greg Schwarz [AAS], Emmanuelle Perret [CDS] 17-Sep-2013