Kavli Affiliate: Xian Chen
| First 5 Authors: Minghui Du, Pengcheng Wang, Ziren Luo, Wen-Biao Han, Xin Zhang
| Summary:
Taiji, a Chinese space-based gravitational wave detection project, aims to
explore the millihertz gravitational wave universe with unprecedented
sensitivity, targeting astrophysical and cosmological sources including
Galactic binaries, massive black hole binaries, extreme mass-ratio inspirals,
and stochastic gravitational wave backgrounds, etc. These observations are
expected to provide transformative insights into astrophysics, cosmology, and
fundamental physics. However, Taiji’s data analysis faces unique challenges
distinct from ground-based detectors like LIGO-Virgo-KAGRA, such as the overlap
of numerous signals, extended data durations, more rigorous accuracy
requirements for the waveform templates, non-negligible subdominant waveform
complexities, incompletely characterized noise spectra, non-stationary noises,
and various data anomalies. This paper presents the second round of Taiji Data
Challenge, a collection of simulation datasets designed as a shared platform
for resolving these critical data analysis problems. The current platform
distinguishes from previous works by the systematic integration of orbital
dynamics based on the full drag-free and attitude control simulation, extended
noise sources, more sophisticated and overlapping gravitational wave signals,
second-generation time-delay interferometry and the coupling effect of
time-varying armlengths, etc. Concurrently released is the open-source toolkit
Triangle (available at https://github.com/TriangleDataCenter), which offers the
capabilities for customized simulation of signals, noises and other
instrumental effects. By taking a step further towards realistic detection,
Taiji Data Challenge II and Triangle altogether serve as a new testbed,
supporting the development of Taiji’s global analysis and end-to-end pipelines,
and ultimately bridging the gaps between observation and scientific objectives.
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