Time-Delay Interferometry: The Key Technique in Data Pre-Processing Analysis of Space-Based Gravitational Waves

Space gravitational wave detection primarily focuses on the rich wave sources corresponding to the millihertz frequency band, which provide key information for studying the fundamental physics of cosmology and astrophysics. However, gravitational wave signals are extremely weak, and any noise during the detection process could potentially overwhelm the gravitational wave signals. Therefore, data pre-processing is necessary to suppress the main noise sources. Among the various noise sources, laser phase noise is dominant, approximately seven orders of magnitude larger in strength than typical gravitational wave signals, and requires suppression using time-delay interferometry (TDI) techniques, which involve combining raw data with time delays. This paper will be based on the basic principles of TDI to present methods for obtaining multi-type TDI combinations, including algebraic methods for solving indeterminate equations and geometric methods for symbolic search. Furthermore, the applicability of TDI under actual operating conditions will be considered, such as the arm locking in conjunction with the TDI algorithm. Finally, the sensitivity functions for different types of TDI combinations will be provided, which can be used to evaluate the signal-to-noise ratio (SNRs) of different TDI combinations.

Authors

Institutions

Publication Details

Journal
Universe
Published
2024-10-16
DOI
https://doi.org/10.3390/universe10100398
Citations
2
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
0.66
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Time-Delay Interferometry: The Key Technique in Data Pre-Processing Analysis of Space-Based Gravitational Waves

Cheng-Gang Shao, Panpan Wang
2 citations
Universe
Pulsars and Gravitational Waves Research
0.66
article

Time-Delay Interferometry: The Key Technique in Data Pre-Processing Analysis of Space-Based Gravitational Waves

Cheng-Gang Shao, Panpan Wang
article en
2 citations

Abstract

Space gravitational wave detection primarily focuses on the rich wave sources corresponding to the millihertz frequency band, which provide key information for studying the fundamental physics of cosmology and astrophysics. However, gravitational wave signals are extremely weak, and any noise during the detection process could potentially overwhelm the gravitational wave signals. Therefore, data pre-processing is necessary to suppress the main noise sources. Among the various noise sources, laser phase noise is dominant, approximately seven orders of magnitude larger in strength than typical gravitational wave signals, and requires suppression using time-delay interferometry (TDI) techniques, which involve combining raw data with time delays. This paper will be based on the basic principles of TDI to present methods for obtaining multi-type TDI combinations, including algebraic methods for solving indeterminate equations and geometric methods for symbolic search. Furthermore, the applicability of TDI under actual operating conditions will be considered, such as the arm locking in conjunction with the TDI algorithm. Finally, the sensitivity functions for different types of TDI combinations will be provided, which can be used to evaluate the signal-to-noise ratio (SNRs) of different TDI combinations.

UniverseVol. 10(10)
Huazhong University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 28%
Pulsars and Gravitational Waves Research
0.66
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.