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LIGO Data Analysis: Status and Plans

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Title: LIGO Data Analysis: Status and Plans


1
LIGO Data Analysis Status and Plans
  • Patrick Brady
  • University of Wisconsin-Milwaukee
  • LIGO Scientific Collaboration

2
Outline of talk
  • First LIGO science data run (S1)
  • Summary of run
  • Organization of LIGO data analysis efforts
  • Status of each effort
  • Detailed discussion of burst/inspiral analysis
  • Emphasis because of TAMA/LIGO coincidence
    analysis
  • Plans for second LIGO science data run (S2)
  • Online analysis plans/status
  • Tools used in control room
  • Summary

3
LIGO Run Schedule
  • Science runs are interspersed with engineering
    runs and commissioning activities

strain noise per root Hz
Jul
Oct
Jul
Oct
Jun
Sep
Jun
Sep
Feb
Mar
Apr
Aug
Nov
Feb
Dec
Mar
Apr
Aug
Nov
May
May
Jan 2002
Jan 2003
E10,
S3
  • E7
  • E8

S2
  • S1
  • E9

Now
4
LIGO sensitivity at start of S1
  • S1 run
  • 23 Aug 9 Sep, 2002
  • Standard candle
  • 2 x 1.4 Msun optimally oriented binary
  • S1 reach includes
  • Milky Way
  • LMC
  • SMC

5
Data from S1 run
H1 235 Hours
H2 298 Hours
L1 170 Hours
3x 95.7 Hours
  • S1 total run time 408 hours 17 days
  • H1 (4km, Hanford) duty cycle 57.6
  • H2 (2km, Hanford) duty cycle 73.1
  • L1 (4km, Livingston) duty cycle 41.7
  • Triple coincidence duty cycle 23.4

Green bands with black borders indicate locked
segments
6
Data analysis groups
  • Burst and other transients
  • Sam Finn and Peter Saulson (co-chairs)
  • http//www.ligo.caltech.edu/ajw/bursts/bursts.htm
    l
  • Continuous Wave
  • Michael Landry and Mariallessandra Papa
    (co-chairs)
  • http//www.lsc-group.phys.uwm.edu/pulgroup/
  • Inspiral
  • Patrick Brady and Gabriel Gonzalez (co-chairs)
  • http//www.lsc-group.phys.uwm.edu/iulgroup/
  • Stochastic
  • Peter Fritschel and Joe Romano (co-chairs)
  • http//feynman.utb.edu/joe/research/stochastic/up
    perlimits

7
Burst Group Activities
  • Search for bursts of unknown origin/waveform
  • Generate event triggers using SLOPE, TFCLUSTERS,
    POWER
  • Veto triggers due to instrumental artifacts
  • Determine upper limit on rate as function of
    strain
  • Monte Carlo by simulated injections of
    astrophysical motivated signals (Zwerger et al)
    and other burst waveforms
  • Search for bursts associated with GRBs.
  • Triggered analysis of on-source times
  • Result by comparison of on-source versus
    off-source distributions
  • First EM triggered search with LIGO

8
Continuous Wave Group Analysis
  • Known pulsar searches
  • Catalog of known pulsars
  • Heterodyne narrow BW folding data
  • Coherent frequency domain search using Hough
    transform
  • All sky unbiased
  • Sum short power spectra (no doppler correction)
  • Wide area search
  • Hierarchical Hough transform code is under
    development
  • Demodulation is functioning and used in known
    pulsar search
  • Demodulation points on sky under control
  • Efficient positioning of spindown/sky points
    under development

9
Inspiral Group Activities
  • Binary Neutron Star Search
  • Bread n butter source for LIGO
  • Determined upper limit on the rate of BNS
    inspirals in the universe
  • Black hole MACHO binary search (0.5ltm1,m2lt1.0)
  • Speculative source
  • MACHO search will use same pipeline as BNS
  • Unbiased search and upper limit will follow
    neutron star result
  • Binary black hole search (m1,m2 gt 3.0 Msun)
  • An unbiased search will not be made due to
    proximity of S2
  • Will use the full S1 data set to explore
    techniques for S2
  • Need to better understand veto strategies for BBH

10
Stochastic Group Activities
  • Analytic calculation of expected upper limits
    (100 hrs)
  • W for LHO 2k-LHO 4k will provide the most
    stringent direct observational upper limit to
    date
  • Coherence measurements of GW channels show little
    coherence for LLO-LHO 2k correlations
  • Investigation of effect of line removal for LHO
    2km-LHO 4km correlations (e.g., reduction in
    instrumental correlated noise)
  • Injection of simulated stochastic signals into
    the data and extraction from the noise to
    validate end-to-end capability of analysis
  • Correlations between LLO with ALLEGRO bar
    detector
  • ALLEGRO was rotated into 3 different positions
    during earlier E7 run
  • Analysis in progress

11
Playground Data Set
  • Representative sample of data distributed over
    run
  • Not used in determining astrophysical results
  • Used to tune thresholds
  • Determine veto cuts
  • Gain experience without introducing bias into
    upper limit analyses
  • Characteristics
  • 9 hours of triple coincident data was selected
    for this purpose
  • Chosen by Gabriela Gonzalez in consultation with
    others on site
  • Representative of broad range of instrumental
    behavior
  • Which groups used it?
  • Inspiral group
  • Burst group
  • Stochastic group

12
Burst Trigger Generation
  • One hour summary plot
  • Confidence
  • Log( probability that trigger is caused by
    Gaussian noise)
  • Large negative value is loud burst
  • Time-frequency plot
  • Green 0 gt confidence gt -100
  • Red confidence lt -100
  • No. of events
  • Triggers per 10 seconds
  • Event definition
  • Different for TFCLUSTER, SLOPE, POWER

Trigger in 200-400Hz band with duration 100 sec
13
Inspiral Trigger Generation Templates
  • Use template based matched filtering algorithm
  • Template waveforms for non-spinning binaries
  • 2.0 post-Newtonian approx.
  • Computational efficiency
  • Stationary phase approximation to Fourier
    Transform
  • Discrete set of templates labeled by M1, M2
  • 1.0 Msun lt m1, m2 lt 3.0 Msun
  • 2110 templates
  • At most 3 loss in SNR

14
Inspiral Trigger Generation
  • AS_Q processed in chunks of 256 seconds
    down-sampled to 4096Hz
  • Each chunk is divided into 7 segments of 64
    seconds overlapped by 32 seconds
  • For each template
  • Compute the SNR large values indicate that GW
    channel correlates well with the template
  • If SNR gt 6.5, compute a2 small values
    indicate that SNR was accumulated in a manner
    consistent with an inspiral signal.
  • If a2 lt 5.0, record trigger
  • Triggers are clustered within duration of each
    template, but multiple templates can trigger at
    same time.

15
Dealing with Non-Gaussian Spurions
  • Example at LIGO Louisianna
  • Cattle Guard
  • (Gonzalez, Chickarmane, Saulson during E7)
  • How to deal with them?
  • Auxiliary channels vetoes
  • Can physical cause be tracked?
  • Use PEM other channels
  • Potential vetoes
  • Evaluated vetoes generated by several tools

16
Veto Investigations
  • Tuned veto SNR thresholds and windows using the
    playground data focused on eliminating the
    highest-SNR candidates without introducing much
    deadtime
  • Best channels turned out to be auxilliary
    interferometer channels
  • Example from inspiral analysis (similar for
    burst)
  • Livingston 4km Net deadtime 2.8
  • Hanford 4km Net deadtime 0.3
  • Hanford 2km Net deadtime 3.2
  • Must check that veto conditions would not veto a
    real gravitational wave!
  • Studied coupling using hardware injections in
    differential control end mass excitations
  • Found some surprise couplings which may involve
    abandoning certain vetoes

17
Effectiveness of Vetoesfor S1 Playground Data
So, how do triggers vetoes fit together in
analysis pipeline?
18
GW Injections
Auxiliary Channels
Matched Filter
Filter
Triggers
Veto Triggers
-
H1 clean Not L1
L1 clean Not H1
L1 H1 clean
H1 Sees?
Yes
No
No
Coincidence?
Dump
Yes
Event Candidates
19
Sample Population Monte Carlo
  • Binary Neutron star population
  • Mass distribution derived from population
    synthesis models
  • Spatial distribution out to 200kpc including
    Milky Way, LMC and SMC
  • LMC and SMC contribute about 12 of a Milky Way
    equivalent Galaxy
  • Signals injected into data stream and used to
    determine efficiency of pipeline to detection of
    BNS population

20
Testing with Hardware Injection
Inspiral Injections into hardware
21
Testing with Hardware Injections
  • Pre-run 2 x 1.4 Msun into L1LSC-DARM_CTRL-EXC

Pre-run 2 x 1.4 Msun into L1LSC-ETMX-EXC
22
LIGO First Science Run Synopsis
  • Compact object inspiraling waveforms
  • BNS coverage will include the Milky Way, plus
    LMC, SMC
  • Black hole MACHO search under way
  • Bursts/transient events
  • 96 hours of 3X coincidence
  • 2 different (complementary) filters applied to
    data
  • frequency-time clustering algorithm, time-domain
    slope detector
  • Efficiency using astrophysically motivated SNe
    waveforms and other.
  • Continuous wave sources
  • Initial searches target known EM sources, e.g.
  • - PSR J19392134 (P 1.557 ms, search and
    analysis in progress)
  • Sco X-1 (in progress - 500 Hz - 600 Hz,
    multi-parameter search)
  • Stochastic background
  • Limiting sensitivity for W will be better than
    previous direct GW observational determinations
    with resonant bars (narrowband)

23
Plans for S2
  • S2 14 Feb 14 April 2003
  • Working groups
  • have well defined primary analysis path for S2
    data
  • Plan to extend/enhance methodology from S1
  • Some new tools are under development, e.g
    coherent multi-detector analysis
  • Veto development will be a major focus of the S2
    detector characterization effort
  • Desire to understand the instrumental origin of
    glitches
  • Significant effort has been put into hardware
    injection plan
  • Daily hardware injections of astrophysical
    signals to help calibrate systematics

24
Plans for S2
  • Trigger generators to run in real-time
  • Burst searches TFCLUSTERS, POWER, SLOPE
  • Inspiral searches
  • Known pulsar demodulation
  • External trigger searches
  • Issues that caused problems in S1 but have been
    fixed
  • Accurate, real-time calibration data available
  • On-line monitoring tool to provide alarms to
    control room

25
Conclusion
  • LIGO Scientific Operation
  • Started in Aug. 2002!
  • Analysis has been proceeding
  • First results should be announced in Mar 2003
  • Second run scheduled 14 Feb - 15 Apr 2003
  • Sensitivity should be almost 10x better than S1
  • Moving towards real-time analysis environment
  • Looking forward to the TAMA/LIGO coincidence
    effort
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