[email protected] | , october 12, 2011 a multiple signal classification method for directional...
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[email protected] | http://ligo.org.cn, October 12, 2011
A Multiple Signal Classification Method for Directional
Gravitational-wave Burst SearchJunwei Cao
LIGO Scientific Collaboration Research Group
Tsinghua University, Beijing, China
3rd Galileo - Xu Guangqi meeting
October 12, 2011
[email protected] | http://ligo.org.cn, October 12, 2011
Outline
• Introduction• Real-time / low-latency GW burst search• Motivation – running before data • Our method
» Multiple signal classification (MUSIC)
» Extension for GW DOA
» Performance metrics
» Performance evaluation
• Performance Comparison• Conclusions
[email protected] | http://ligo.org.cn, October 12, 2011
Our Group
• The LSC member group in China, including 3 faculty members and 3 students
• GW burst data analysis and computing infrastructure• Also involved in LCGT, AIGO and ASTROD• With close collaboration with MIT, Caltech and UWA• This talk provides an introduction to one of our
existing efforts on real-time / low latency GW burst search
[email protected] | http://ligo.org.cn, October 12, 2011
LSC Burst Group
• Mission: Detection of unmodeled bursts of gravitational radiation
• Three dedicated pipelines:» Coherent Wave Burst (CWB) Pipeline
– S. Klimenko et al, Class.Quant.Grav.25:114029,2008
» Kleine Welle for online detector characterization– LIGO Document, LIGO-G050158-00-Z, 2005
» Omega Pipeline– https://geco.phys.columbia.edu/omega
• One group-crossed pipeline:» X-Pipeline for directional search
– https://geco.phys.columbia.edu/xpipeline
[email protected] | http://ligo.org.cn, October 12, 2011
Real-time Search
Online Monitoring
Real-time Search
Offline Analysis
Data Streams
Data Streams+Data Production
Data Production
On-site
On-site+Off-site
Off-site
• Real-time: between online and offline mode for large-scale data analysis
[email protected] | http://ligo.org.cn, October 12, 2011
Motivation
• Prompt E/M follow-up by LIGO’s external collaborators– Detect astronomy events earlier than traditional
observation methods– Increase the confidence of the GW candidate
event– Obtain more information about GW candidate
event and its source: more accurate sky position, distance, …
• Rapid detector characterization
=> New algorithms, methods and computing technology to enable faster real-time search, in particular, directional search
[email protected] | http://ligo.org.cn, October 12, 2011
Challenges in AdvLIGO
• More potential IFOs: LCGT, AIGO, …» More data streams flood into central location
• Larger Data Volume
Cite from LIGO-G0900008
[email protected] | http://ligo.org.cn, October 12, 2011
MUSIC
• The multiple signal classification (MUSIC) algorithm is one of the most popular subspace-based techniques for estimating the directions-of-arrival (DOAs) from linearly arrayed signal detectors.
• Dividing eigenspace to noise and signal subspaces, which are perpendicular to each other
• Giving arbitrary locations and arbitrary directional characteristics in a noisy environment of arbitrary covariance matrix, MUSIC is capable of giving asymptotically unbiased estimates of» Number of signals» DOA» Strengths and cross correslations among the directional waveforms» Polarizations» Strength of noise or interference
[email protected] | http://ligo.org.cn, October 12, 2011
MUSIC Extensions
• MUSIC is widely used in periodic sine radio wave detection by antenna arrays in the plane condition. Several aspects are extended before applying MUSIC on GW burst search:» Using Spherical coordinates to extend from 2D to
3D» Using the concept of equal-phase to extend
linearly arrayed detectors to generally placed detectors
» Using linear transformation in time domain to extend the method to non-periodic signals
[email protected] | http://ligo.org.cn, October 12, 2011
MUSIC Steps
Collect data and form the covariance matrix S
Calculate the Eigen structure of S in the matrix S0
Assuming that there is one signal in a relatively long period of time, get the eigenvectors of the noise subspace with the
number of M-1 (M is the number of detectors)
Calculate the Pmu(θ) and put it in a figure
Find the peak of the signal
Get DOA and other information of interest
[email protected] | http://ligo.org.cn, October 12, 2011
Experiment Design
• Self-generated Gaussian-moderated sinusoidal GW is injected into simulated LIGO data background.
• IIR filtering + MUSIC vs. Omega + Bayesian
[email protected] | http://ligo.org.cn, October 12, 2011
Comparison Results
Parameters Low Limit of A Time Resolution
Time Consuming
Omega 2 0.015s 14s
MUSIC 200 0.03s 3200s
• The comparison result of MUSIC acting as the signal trigger versus Omega (Q transform).
(Define A as the relative signal strength, which comes from the parameter of Factor of LogFile of injection part. A typical GW has a strength A~1)
[email protected] | http://ligo.org.cn, October 12, 2011
Comparison Results
Parameters Low Limit of A Angel Resolution
Time Consuming
Bayesian 4 0.019rad 30s
MUSIC 1000 Complicated 4.2s
• The comparison result of MUSIC acting as DOA evaluator versus Bayesian.
[email protected] | http://ligo.org.cn, October 12, 2011
Conclusion
• Current burst real-time low latency search is successful, but not perfect
• Advanced computing technology and new signal processing methods can significantly boost real-time multi-messenger astronomy
• Multiple signal classification have potential to provide faster direction estimation, though current SNR ratio resolution and time resolution are not satisfactory