Coincidence%20analysis%20between%20periodic%20source%20candidates%20in%20C6%20and%20C7%20Virgo%20data

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Coincidence analysis between periodic source
candidates in C6 and C7 Virgo data C.Palomba
(INFN Roma) for the Virgo Collaboration

• I report on the ongoing work done in
  collaboration with Pia Astone and Sergio Frasca
• Blind analysis of the data of runs C6 and C7 to
  search for gravitational signals emitted by
  isolated rotating neutron stars

• Selection of candidates in the two data sets and
  coincidences between them.
• Injection of simulated signals

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Blind search

• Assumes source position, frequency and spin-down
  are not known

• The vast majority of neutron stars is not
  visible in the EM band
• It is rather unlikely that known NS (pulsars)
  emit detectable signals

• Local population of neutron stars must be taken
  into account

• Blind searches cannot be performed with optimal
  methods due to the huge number of points in the
  parameter space
• Hierarchical procedures strongly cut the needed
  computing power at the cost of a small reduction
  in sensitivity

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Hierarchical method for blind searches
h-reconstructed data
Data quality SFDB Average spect rum
estimation
Data quality SFDB Average spect rum
estimation
Frasca, Astone, Palomba, CQG 22, S1013 2005
Astone, Frasca, Palomba, CQG 22, S1197 2005
Palomba, Astone, Frasca, CQG 22, S1255 2005
peak map
peak map
Presentation at MG11
hough transf.
hough transf.
The procedure involves two or more data sets
belonging to a single or more detectors
candidates
candidates
coincidences
coherent step
events
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Parameter space

• observation time
• frequency band
• frequency resolution
• number of FFTs
• sky resolution
• spin-down resolution

1013 points in the parameter space are explored
for each data set
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Candidates selection

• On each Hough map (corresponding to a given
  frequency and spin-down) candidates are selected
  putting a threshold on the CR
• The choice of the threshold is done according to
  the maximum number of candidates we can manage in
  the next steps of the analysis

• In this analysis we have used

• Number of candidates found
• C6 922,999,536 candidates
• C7 319,201,742 candidates

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• Effective (i.e. after selection of candidates)
  sensitivity loss respect to optimal analysis
  C6 2.4
  
  C7 1.8

• False alarm probability C6
  C7
  

MC 1st violin mode

• Still candidates excess at many frequencies,
  even if some cleaning has been done

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red line theoretical distribution
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disturbed band
Many candidates appear in bumps (at high
latitude), due to the short observation time, and
strips (at low latitude), due to the symmetry
of the problem
quiet band
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Coincidences

• To reduce the false alarm probability reduce
  also the computational load of the coherent
  follow-up

• Done comparing the set of parameter values
  identifying each candidate

• Coincidence windows

• Number of coincidences 2,700,232

• False alarm probability

band 1045-1050 Hz
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Detection of injected signals

• 66 signals injected in C7 data, with frequency
  in 50,550Hz and no spin-down, to study
  efficiency and accuracy in parameter estimation
  of the incoherent step

• We make coincidences between candidates found in
  C7 data injections and the injected signals

• Coincidence windows

1964 candidates
many sources undetected
green curve expected C7 sensitivity
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• To check if the short observation time plays a
  role, we dilate time by a factor 80 (and reduce
  spin-down of injected signals by the same amount)

5257 candidates

• Good agreement with the expected sensitivity.

• Accuracy in latitude is only slightly affected
  by the length of the observation time
• Longer time interval increases the detection
  efficiency

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• Given two or more data sets, we can suitable mix
  them in order to produce data sets covering a
  larger time interval

time

• If the two sets are created with nearly equal
  sensitivity, we have a further gain

time
See presentation at MG11 for more details
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Good correlation between signals amplitude and CR
of candidates Strongest sources are detected
with more accurate position Worse accuracy for
low frequency sources (due to lower resolution)
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• As already noted, sources at low ecliptic
  latitude are detected with worse accuracy. This
  is basically independent on the observation time.
• We expect to have an improvement by using the
  adaptive Hough transform, which breaks the
  symmetry respect to the ecliptic.

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• Conclusions
• Well established procedure for going from data
  to candidates
• We make coincidences to reduce false alarm and
  computational load of the coherent step
• Need for stretch of data covering a time
  interval as large as possible to have better
  detection efficiency
• Uncertainty in latitude will be reduced by using
  the adaptive Hough transform
• Need to extend the injections to non zero
  spin-down

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