status of stochastic background’s joint data analysis by virgo and infn resonant bars
DESCRIPTION
Status of stochastic background’s joint data analysis by Virgo and INFN resonant bars. G. Cella (INFN Pisa) For Auriga-ROG-Virgo collaborations. Prepared for the ILIAS-GWA Meeting. The collaboration. 3 groups involved: AURIGA ROG (Nautilus + Explorer) Virgo. - PowerPoint PPT PresentationTRANSCRIPT
Status of stochastic background’s joint data analysis by Virgo and INFN resonant bars
G. Cella (INFN Pisa)For Auriga-ROG-Virgo collaborations
Prepared for the ILIAS-GWA Meeting
The collaboration 3 groups involved:
AURIGA ROG (Nautilus + Explorer) Virgo
Common frequency range: 850-950 Hz
Bandwidth: 5-30 Hz
The project Joint data analysis experiment between Virgo,
Auriga, Explorer, Nautilus Detection of stochastic background signal Software injection of simulated data Analysis of real noise: 4 hours of
simultaneous data for the first phase
Exchange and preprocessing of data Signal simulation and injection
Gaussian, isotropic & non polarized model
Flat energy density power spectrum Detection
Standard cross correlation analysis
Purpose:
Steps:
Data exchange Purpose: test of independent procedures of data
generation and exchange. Each member of the collaboration was asked to
provide a small stream of data (4 hours) which was stored in a common repository in Bologna (CNAF).
A continuous time series with the reconstructed strain observed by the detector
A minimal data quality channel, which will consist in a simple boolean flag for each value of the time series (valid/not valid).
Valid means that the data can be safely used for processing. Not valid means that the data cannot be trusted for reasons that does not have to be specified (independent vetoing procedure).
Data content:
Signal injection A multiple stream of simulated stochastic background
signals was generated, taking into account the real orientation and position of each detector. SNR=0,5,10,20.
The signal is the one appropriate for a stationary, Gaussian and unpolarized stochastic background with a flat spectrum in
The problem to solve: generate N continuous streams of Gaussian data with a known cross correlation array:
Normalization Overlap Reduction Function
Signal simulation: some details on the approach
Generate streams with a flat spectrum in h but with the correct coherence:
• Square root of is obtained using SVD
• Vectorial filtering is implemented with Overlap and Add
• We know what is the correct padding to use in the flat case:
Filter all the streams to obtain the correct power spectrum (in our case, )
Simulated data: a cross check
Overlap reduction function reconstruction from simulated data
Detection (with standard cross correlation analysis)
Minimum detectable energy density:
Detector Reference Foreseen Improvement
Virgo (C5) 1.0x10-20 7.0x10-23 7.0x10-3
Auriga 1.5x10-21 2.1x10-22 1.4x10-1
Nautilus 2.0x10-21 8.6x10-23 4.3x10-2
Explorer 2.0x10-21 8.6x10-23 4.3x10-2
Expected outcomes
Test of data analysis software Test of syncronization issues Research on methods to deal with noisy periods and
dead times
No ambitions of finding upper limits, at least in this first methodological study. But:
Future steps
First phase of detection should be completed during this month
Finalization of first phase foreseen for november
Second phase: upper limit with longer stretches of data?