Search for gravitational wave ringdowns from perturbed black holes in LIGO S4 data
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Citations
Testing general relativity with present and future astrophysical observations
Testing the nature of dark compact objects: a status report
Gravitational Wave Detection by Interferometry (Ground and Space)
Tests for the existence of black holes through gravitational wave echoes
Testing the nature of dark compact objects: a status report
References
Extraction of Signals from Noise
Extraction of Signals from Noise
Intermediate-Mass Black Holes as LISA Sources
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Frequently Asked Questions (15)
Q2. How many simulated signals were added to the data?
The authors added 5701 simulated signals in the frequency range of 70 Hz–140 Hz and between 0.5M pc and 103 Mpc in distance to the data, over ten runs.
Q3. What is the way to find a black hole?
Numerical simulations [21–24] have demonstrated that the maximum spin attained by the final black hole in a binary black hole merger is less than 0.96, corresponding to a quality factor of 8.5.
Q4. How long after the innermost stable circular orbit of the binary?
For black holes in the LIGO band this is on the order of tens of milliseconds after the innermost stable circular orbit of the binary.
Q5. How many hours of data was collected from the 4th LIGO science run?
This yielded a total of 567.4 hours of analyzable data from the 4 km interferometer in Hanford, WA (H1), 571.3 hours from the 2 km interferometer in Hanford, WA (H2), and 514.7 hours from the 4 km interferometer in Livingston, LA (L1).
Q6. What is the error in the MC?
The second source of error is due to the limited number of simulated signals in their Monte Carlo (MC) simulations to evaluate the efficiency.
Q7. What is the sensitivity of the new LIGO?
A further increase in sensitivity will come with Advanced LIGO, allowing us to detect compact binary coalescence to cosmological distances, and the improved sensitivity at lower frequency will make us sensitive to black holes with masses up to 2000M or higher.
Q8. How do the authors determine the efficiency of the search?
The authors calculate an upper limit on the rate of ringdowns for a given population of black holes using simulated signals to evaluate the efficiency of the search, "ðrÞ, defined as the fraction of simulated signals detected in the analysis, as a function of physical distance.
Q9. How much confidence is given on the rate of the black hole?
The 90% confidence062001-7upper limit on the rate in these units is given byR90% ¼ 2:303TCL ; (15)which evaluates to 1:2 10 3 yr 1L 110 .
Q10. What is the method for detecting the signal?
LIGO data is non-Gaussian and while the method is still appropriate it is not sufficient to discriminate between signal and background.
Q11. How is the efficiency of the search determined?
Figure 4 shows that the efficiency is stronglydependent on the ringdown frequency f0, and thus for the purpose of setting an upper limit the authors restrict the calculation to the most sensitive frequency band, 70 Hz–140 Hz, corresponding to black hole masses in the range 85M –390M .
Q12. How many errors do the authors assign to the waveform?
the authors assign no error to the waveform: comparison with numerical relativity results has shown that exponentially-damped-sinusoid templates perform well at detecting the signal and characterizing the black hole parameters [7].
Q13. What is the angular frequency of the real part of the ringdown phase?
Each quasinormal mode has a characteristic complex angular frequency !lm; the real part is the angular frequency and the imaginary part is the inverse of the damping time .
Q14. What is the noise spectral density of the data?
Filtering the data gives a signal to noise ratio (SNR)ðhÞ ¼ hs; hiffiffiffiffiffiffiffiffiffiffiffihh; hip ; (8) wherehs; hi ¼ 2 Z 1 1 ~sðfÞ~h ðfÞ ShðjfjÞ df: (9)Here, the noise spectral density ShðfÞ is the one appropriate for the data segment in question.
Q15. How many errors can cause the SNR of a signal to be incorrectly quantified?
Errors in the calibration can cause the SNR of a signal to be incorrectly quantified, thereby introducing inaccuracies in the distance.