Removing the trend of drift induced from acceleration noise for LISA
Alf Tang, Timothy J. Sumner

TL;DR
This paper introduces a frequency domain method combining statistical techniques to effectively remove acceleration noise drift from LISA data, enabling accurate gravitational-wave background detection.
Contribution
A novel frequency domain approach using Fourier transforms and advanced algorithms to clean LISA data from acceleration noise drift, improving sensitivity.
Findings
LISA sensitivity can be recovered after noise removal.
The method effectively analyzes simulated LISA noise data.
Applicable to other space-borne interferometers.
Abstract
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…
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Taxonomy
TopicsCosmology and Gravitation Theories · Particle physics theoretical and experimental studies · Radio Astronomy Observations and Technology
