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Дата изменения: Mon Feb 7 21:59:18 2005
Дата индексирования: Tue Oct 2 10:51:43 2012
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Поисковые слова: south pole
Isabel Leonor University of Oregon


search for short-duration GW bursts coincident with gamma-ray burst triggers
~1 to 10 ms, e.g. supernova core-collapse models, end of inspiral merger

take advantage of readily-available and readilyaccessible GRB triggers use definite GRBs as triggers triggers are from Interplanetary Network (IPN) (KonusWind, Ulysses, Mars Odyssey, others), INTEGRAL , HETE prepare for Swift triggers
November 5, 2004 MIT Burst F2F Meeting I. Leonor 2


S2: 29 GRBs with at least double coincidence science segments
23 7 7 11 for for for for H1-H2 H1-L1 H2-L1 H1-H2-L1 (not all with well-defined positions)

S3: 11 GRBs with at least double coincidence science segments
11 for H1-H2 (only 8 if segments with seismic flags excluded) 0 for H1-L1 (one GRB eliminated due to bad timing flag) 0 for H2-L1 (one GRB eliminated due to bad timing flag)

time delay taken into consideration for H1-L1, H2-L1 search only well-localized GRBs considered for H1-L1, H2-L1 search

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date

z

GPS time

RA DEC

error

IFO

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!!
each search segment is 160-seconds long (less ~1.5 seconds at ends of segment) each 160-second segment pre-conditioned use crosscorrelation windows of length 25 ms each, windows overlapping by half a window length calculate normalized crosscorrelation for each 25-ms second find largest crosscorrelation within each 160-second search segment; find largest abs(cc) for H1-L1 and H2-L1 due to unknown polarization use playground data to test pipeline and estimate sensitivity ­ playground data was long science segment not coincident with any GRB trigger
November 5, 2004 MIT Burst F2F Meeting I. Leonor 5


"
DFT1 condition this segment

#
DFT2

data conditioning done in frequency domain data DFTed using 1-second Tukey windows adjacent 1-sec segments DFTed to determine factor for whitening in frequency domain whitening factor(f) = max(DFT1(f),DFT2(f)) use phase calibration to correct signal phase

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" ' (

#

$%

&

data conditioning process repeated for each second perform inverse DFT to convert back to time domain keep only time segment corresponding to unattenuated section of window crosscorrelation calculated in time domain

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)
S2 data, H2-L1 crosscorrelation effect of phase correction varies depending on time epoch and IFO pair large effect of phase on crosscorrelation not yet seen in S3 data

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*

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+ ,!

#, ! -*
S3 data

-

on-source distributions derived from playground data with injections off-source segments were shuffled ­ each search segment from one IFO paired with all segments from other IFO

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"

%. /0# 0 1
probability for getting median of on-source distribution, given off-source distribution probability takes into account trials in search probability is function of length of crosscorrelation window small window: 1/sqrt(N), more trials large window: more noise integrated

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%

!

S3

sine-gaussians, Q = 8.9 markers: hrss such that median of cc distribution with injections has a probability of 1/1000 given off-source distribution valid for 160-second search window, 25-ms crosscorrelation length

November 5, 2004 MIT

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!

*

# 20 2 !
local off-source distribution determined for each GRB trigger each distribution determined from searches within science segments occurring within a few hours of GRB trigger largest crosscorrelation found in each search included in distribution (indicated by black arrow) used data segments defined by burst group

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*

# 2030 !

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!

*

# 2 !30

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!

*

# 20 2 !
v03 segments list allowed flags: DUST, SEISMIC_ELEVATED, note that S3 off-source distributions are very similar to S2 distributions indicates robustness of crosscorrelation and pipeline

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!

*

# 20 2 !

all off-source segments come from "clean" segments (no error flags) see next slide
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)* 45 6

!
from playground data

from loud segment

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)*
H1

!

45 6
H2

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7
(outlier GPS in black, airplane GPS in blue) 7559 7559 7559 7559 7559 7559 7559 7559 7559 7559 7559 7559 201 222 223 272 273 276 288 292 293 295 301 305 43 23 60 11 71 91 40 10 70 60 37 20 (D (D (D (D (D (D (D (D (D (D (D (D ec ec ec ec ec ec ec ec ec ec ec ec 20 20 20 20 20 20 20 20 20 20 20 20 200 200 200 200 200 200 200 200 200 200 200 200 3 3 3 3 3 3 3 3 3 3 3 3 1: 2: 2: 3: 3: 3: 4: 4: 4: 4: 4: 4: 49) 23) 25) 46) 49) 54) 13) 20) 22) 25) 35) 41) *some days had plane flags at this time of day airplane flag

*some days had plane flags at this time of day airplane flag

airplane flag airplane flag
20

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8

9+
calculate after-trials probability using off-source distribution test sample distribution using K-S test (Kolmogorov-Smirnov) probability that measured statistic will be larger under null hypothesis: p = 0.81 consistent with null hypothesis

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)*

%

:

inject signals into playground, sine-gaussian, f = 554 Hz, Q = 8.9, hRss = 2.6E-21 K-S test: p = 0.15

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)*

%

:

inject signals into playground, sine-gaussian, f = 554 Hz, Q = 8.9, hRss = 2.6E-21 K-S test: p = 0.026

November 5, 2004 MIT

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%
performed search for short-duration GW bursts coincident with S2 and S3 GRBs using crosscorrelation method combined S2 and S3 results
there were much fewer S3 GRBs than S2 GRBs due to lockloss and also fewer triggers

sample probability distribution consistent with null hypothesis large outliers seen in one GRB off-source period
S3 segments list probably needs refinement

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