Alf Tang, Timothy J. Sumner
In this paper we demonstrate a methodology to remove the power of the drift
induced from random acceleration on LISA proof mass in the frequency domain.
The drift must be cleaned from LISA time series data in advance of any further
analysis. The cleaning is usually performed in the time domain by using a
quadratic function to fit the time series data, and then removing the fitted
part from the data. Having Fourier transformed the residuals, and then
convolved with LISA transfer function, LISA sensitivity curve can be obtained.
However, cosmic gravitational-wave background cannot be retrieved with this
approach due to its random nature. Here we provide a new representation of
power spectrum given by discrete Fourier transform, which is applied to find
the function of the drift power for the cleaning in the frequency domain. We
also give the probability distribution used to analyze the data in the
frequency domain. We combine several techniques, including Markov Chain Monte
Carlo method, simulated annealing, and Gelman & Rubin's method, with Baye's
theorem to build the algorithm. The algorithm is utilized to analyze 24
simulations of LISA instrumental noise. We prove that the LISA sensitivity can
be recovered through this approach. It can help us to build algorithms for some
tasks which are must accomplished in the frequency domain for LISA data
analysis. This method can be applied to other space-borne interferometers if
charges on their proof masses cannot be perfectly cancelled.
View original:
http://arxiv.org/abs/1202.2976
No comments:
Post a Comment