Window and inpainting: dealing with data gaps for TianQin

• DOI: 10.48550/arxiv.2405.14274
• Publication Date: 2024-05-23
• Authors: Lu Wang; Hongyu Chen; Xiangyu Lyu; En-Kun Li; Yi-Ming Hu
• Keywords: Inpainting

Space-borne gravitational wave detectors like TianQin might encounter data gaps due to factors micro-meteoroid collisions or hardware failures. Such glitches will cause discontinuity in the and have been observed LISA Pathfinder. The existence of such presents challenges analysis for TianQin, especially massive black hole binary mergers, since its signal-to-noise ratio (SNR) accumulates a non-linear way, gap near merger could lead significant loss SNR. It introduce bias estimate noise properties, furthermore results parameter estimation. In this work, using simulated with injected merger, we study window function method, first time, inpainting method cope gap, an iterative scheme is designed properly spectrum. We find that both methods can signal parameters. easy-to-implement already perform well, except it sacrifice some SNR adoption window. slower, but minimize impact gap.