Data Quality in Gravitational Wave Burst and Inspiral ... - Florent Robinet
Omega for bursts, MBTA for CBC. Trigger rate variations. Follow-up of ... Omega scans. Environmental monitoring .... See T. Isogai's poster. All the strategies give ...
Commissioning People Unique knowledge of the interferometer Work on the detector on a day-by-day basis Strong interaction between the DQ group and the commissioning team
GWDAW-14
Florent Robinet
2-3
Tools for Investigations
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Online Analysis Pipelines
Omega for bursts, MBTA for CBC Trigger rate variations Follow-up of the loudest events
Commissioning People Unique knowledge of the interferometer Work on the detector on a day-by-day basis Strong interaction between the DQ group and the commissioning team
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Scientists on Shift Shift report in the logbook Weekly glitch investigation
GWDAW-14
Florent Robinet
2-4
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. Ex. : Missing h(t)
GWDAW-14
Florent Robinet
3-1
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. Ex. : Flags defined by hand in case of a serious malfunction of the detector Usually, these kind of flags are introduced offline later, based on observations of commissioners / shifters. Thermal Compensation System failure
GWDAW-14
Florent Robinet
3-2
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) Ex. : Magnetic glitches. A 50Hz glitch is seen by all the magnetometer at the same time.
GW channel
GWDAW-14
Florent Robinet
3-3
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) Ex. : Acoustic glitches.
Airplane event detected by a microphone
GW channel
GWDAW-14
Florent Robinet
3-4
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) Ex. : Acoustic glitches. Helicopter flying over the site Airplane event detected by a microphone
GW channel
NS/NS horizon
GWDAW-14
Florent Robinet
3-4
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) Ex. : Severe micro-seismic activity see I. Fiori's talk
Flagging of Omega triggers
GWDAW-14
GW channel
Florent Robinet
3-5
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) CAT 3 : Noisy periods where the coupling is not well understood. The validity of a GW candidate flagged by a CAT3 should be controlled carefully. Ex. : seismic glitches 2 seismic glitches of the same amplitude will not have the same impact on the GW channel. CAT3 vetoes plays a big role in the follow-up studies.
GW channel SNR ~ 25
Seismometer
GWDAW-14
Florent Robinet
3-6
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) CAT 3 : Noisy periods where the coupling is not well understood. The validity of a GW candidate flagged by a CAT3 should be controlled carefully. Ex. : seismic glitches 2 seismic glitches of the same amplitude will not have the same impact on the GW channel. CAT3 vetoes plays a big role in the follow-up studies.
GW channel
Seismometer
GWDAW-14
Florent Robinet
3-6
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) CAT 3 : Noisy periods where the coupling is not well understood. The validity of a GW candidate flagged by a CAT3 should be controlled carefully. Ex. : Same as CAT2 but with stricter threshold CAT2 micro-seismic flag
GWDAW-14
CAT3 micro-seismic flag with a lower threshold
Florent Robinet
3-7
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) CAT 3 : Noisy periods where the coupling is not well understood. The validity of a GW candidate flagged by a CAT3 should be controlled carefully. CAT 4 : Hardware injections used for sensitivity studies To be removed from the GW candidate list
GWDAW-14
Florent Robinet
3-8
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) CAT 3 : Noisy periods where the coupling is not well understood. The validity of a GW candidate flagged by a CAT3 should be controlled carefully. CAT 4 : Hardware injections used for sensitivity studies To be removed from the GW candidate list CAT5 : Advisory flags to track problems on the detector but no direct impact on the GW channel Ex. : 300sec after the lock starts the detector is known to be unstable. TOTAL ~ 70 DQ flags
GWDAW-14
Florent Robinet
3-9
DQ Categories DQ flags have been divided into 5 categories for a better use by analyses : CAT 1 : Obvious problems on the detector. CAT1 periods have to be removed to redefine the science data. CAT 2 : Noisy periods where the coupling noise source / GW channel is well established. Triggers are removed before post-processing (coincidence, selection cuts...) CAT 3 : Noisy periods where the coupling is not well understood. The validity of a GW candidate flagged by a CAT3 should be controlled carefully. CAT 4 : Hardware injections used for sensitivity studies To be removed from the GW candidate list CAT5 : Advisory flags to track problems on the detector but no direct impact on the GW channel Ex. : 300sec after the lock starts the detector is known to be unstable. TOTAL ~ 70 DQ flags The safety of all DQ flags has been checked A flag is declared unsafe if the number of flagged hardware injections is larger than dead-time × total number of hardware injections
GWDAW-14
Florent Robinet
3-10
DQ Impact for Bursts Cumulative dead-time
Efficiency for SNR > 8 :
~1%
~ 25 %
~+3%
~ + 15 %
~+6%
~ + 15 %
8 first weeks of VSR2
GWDAW-14
Florent Robinet
4-1
DQ Impact for Bursts (Omega) Cumulative dead-time ~1% ~+3% ~+6%
Mostly due to bad weather conditions Cumulative dead-time ~5% ~+7% ~ + 16 %
8 first weeks of VSR2
PRELIMINARY GWDAW-14
Florent Robinet
19 last weeks of VSR2
4-2
DQ Impact for Inspirals (MBTA) Cumulative dead-time
Efficiency for SNR > 7 :
~1%
~ 14 %
~+3%
~ + 11 %
~+6%
~ + 12 %
8 first weeks of VSR2
GWDAW-14
Florent Robinet
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Veto Based on Auxiliary Channels
Kleine Welle is a fast filtering algorithm used to produce triggers on multiple channels (>200 at Virgo) : ● Environmental channels : seismic, magnetic, acoustic... ● Optical channels : photodiode signals, laser monitoring ● Control channels The most useful channels are selected by looking at the correlations with the GW triggers. 2 strategies are used to define the vetoes : Burst strategy : 1) Channels are ranked according to their efficiency to remove GW triggers. 2) - Only channels with a large statistical significance are used (LIGO). - Only channels with a large efficiency/use-percentage are used (Virgo). CBC Strategy : Only channels with a use-percentage > 50% are used (both for Virgo and LIGO) See T. Isogai's poster All the strategies give consistent results
GWDAW-14
Florent Robinet
6-1
Veto Based on Auxiliary Channels
Cumulative dead-time
Efficiency for SNR > 8 :
~1%
~ 25 %
~ + 0.06 %
~+8%
One of the main interest of the KW vetoes is the very low dead-time
PRELIMINARY 8 first weeks of VSR2
GWDAW-14
Florent Robinet
6-2
A Virgo Specificity : PQ Veto For VSR1, a specific veto was originally introduced for dust induced events. A genuine GW signal should create a signal in the in-phase channel (ACp) and not in the quadrature channel (ACq). The PQ veto is based on coincident KW triggers in ACp and ACq (EACq > EACp ). This veto can be defined only in Virgo since the demodulation phase is monitored and kept at a welltuned value.
ACq KW SNR
Very low dead-time ( < 0.5 % ).
ACp KW SNR
Safety is checked on hardware injections (green points). GWDAW-14
Florent Robinet
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DQ Storage
MySQL database to store DQ and veto segments. Web interface to retrieve and combine segment lists. Very practical tool for follow-up studies.
The Virgo database is frequently synchronized with the LIGO database.
GWDAW-14
Florent Robinet
8
Online Data Quality Online data
DQ monitors
To the control room
Monitor outputs are used in the control room by the shift crew.
Segments generation Database storage Transfer to network analyses
DQ monitors have been developed to produce DQ flags with a few seconds latency. (~70 flags)
Segments are generated and sent to the analysis computers within the minute. Candidate alerts (see Erik Katsavounidis's talk)
DQ applied to triggers
Alerts
GWDAW-14
Florent Robinet
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Conclusions The data quality work has become more and more crucial to aim at a GW detection. ● The Virgo Data Quality Group is an essential piece between the detector and the analyses groups. ●
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Large efforts have been made to understand the noise of the new VSR2 detector.
About 70 DQ flags have been defined and are produced online. ● Correlations with auxiliary channels have been studied and used to produce powerful vetoes (KW) ●
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Many checks have been performed to insure the veto reliability : - Segment checks - Safety against signal injections - Performance over analyses pipelines - Categorization of the flags
Application of the Virgo vetoes over the analyses triggers show that a large fraction of events can be flagged with a limited dead-time. ● Some glitches remain unexplained and are under investigation. ● More improvements are expected in the next few weeks. ●
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