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General Relativity and Quantum Cosmology, gr-qc
Abstract:
We present data analysis methods used in detection and the estimation of
parameters of gravitational wave signals from the white dwarf binaries in the
mock LISA data challenge. Our main focus is on the analysis of challenge 3.1,
where the gravitational wave signals from more than 50 mln. Galactic binaries
were added to the simulated Gaussian instrumental noise. Majority of the
signals at low frequencies are not resolved individually. The confusion between
the signals is strongly reduced at frequencies above 5 mHz. Our basic data
analysis procedure is the maximum likelihood detection method. We filter the
data through the template bank at the first step of the search, then we refine
parameters using the Nelder-Mead algorithm, we remove the strongest signal
found and we repeat the procedure. We detect reliably and estimate parameters
accurately of more than ten thousand signals from white dwarf binaries.
