Filtering and calibration of data from a resonant-mass gravitational wave antenna

Details Filtering and calibration of data from a resonant-mass gravitational wave antenna Filtering and calibration of data from a resonant-mass gravitational wave antenna

Nov 1999

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1999cqgra..16.3439h&link_type=abstract

Classical and Quantum Gravity, Volume 16, Issue 11, pp. 3439-3456 (1999).

Computer Science

Performance

3

Scientific paper

Algorithms for extracting a burst gravitational wave signal embedded within the noise of resonant-mass gravitational wave antenna have been well characterized theoretically, but their effects on experimental data, which can be contaminated by non-stationary, non-Gaussian noise, are still being studied. In this paper, we study the effects of three such algorithms, the zero-order prediction, adaptive Wiener-Kolmogorov and non-adaptive Wiener-Kolmogorov algorithms, on data from the resonant-mass gravitational wave antenna, Niobe, at the University of Western Australia. By applying these filters to computer-simulated GW signals, we show that the adaptive Wiener-Kolmogorov filter gives the best noise performance and signal-to-noise ratio in the presence of non-Gaussian noise. By searching for coincidences between the simulated signals, we show that a window larger than the sampling time of the data is necessary to observe a coincidence between all events. A method of applying pulse excitations to Niobe by amplitude modulating the pump oscillator driving the parametric transducer is also described. This method has the potential to be a very accurate calibration technique but uncertainties in the input and output gains reduce its accuracy. Finally, the adaptive and non-adaptive Wiener-Kolmogorov filters are applied to pulses generated by the amplitude modulation method to determine the overall timing delays and energy uncertainties of Niobe and its data acquisition system.

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