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

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Abstract

Algorithms for extracting a burst gravitational wave signal embedded within the noise of resonant-mass gravitational wave antenna have been well characterized theoretically, bur 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, adaptiveWiener-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 ail events. A method of applying pulse excitations to Niobe by amplitude modulating the pump oscillator driving the parametric transducer is also describe. 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.
Original languageEnglish
Pages (from-to)1-18
JournalClassical and Quantum Gravity
Volume16
Issue numberN/A
DOIs
Publication statusPublished - 1999

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