Taiji data challenge for exploring gravitational wave universe

doi:10.1007/s11467-023-1318-y

Frontiers of Physics

2023, Vol. 18

Issue (6): 64302 https://doi.org/10.1007/s11467-023-1318-y

本期目录

Taiji data challenge for exploring gravitational wave universe

Zhixiang Ren^1,², Tianyu Zhao^1,^3,², Zhoujian Cao^1,^3,⁴(

), Zong-Kuan Guo^1,^5,^6,⁴, Wen-Biao Han^1,^4,^7,^8,^9,¹⁰, Hong-Bo Jin^1,^11,⁸, Yue-Liang Wu^1,^5,^4,⁹(

)

¹. Taiji Laboratory for Gravitational Wave Universe, University of Chinese Academy of Sciences (UCAS), Beijing 100049, China
². Peng Cheng Laboratory, Shenzhen 518055, China
³. Department of Astronomy, Beijing Normal University, Beijing 100875, China
⁴. School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
⁵. CAS Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China
⁶. School of Physical Sciences, UCAS, Beijing 100049, China
⁷. Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
⁸. School of Astronomy and Space Science, UCAS, Beijing 100049, China
⁹. International Centre for Theoretical Physics Asia-Pacific (ICTP-AP, UNESCO), UCAS, Beijing 100190, China
¹⁰. Shanghai Frontiers Science Center for Gravitational Wave Detection, Shanghai 200240, China
¹¹. Key Laboratory of Computational Astrophysics, National Astronomical Observatories, Beijing 100101, China

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Abstract：

The direct observation of gravitational waves (GWs) opens a new window for exploring new physics from quanta to cosmos and provides a new tool for probing the evolution of universe. GWs detection in space covers a broad spectrum ranging over more than four orders of magnitude and enables us to study rich physical and astronomical phenomena. Taiji is a proposed space-based gravitational wave (GW) detection mission that will be launched in the 2030s. Taiji will be exposed to numerous overlapping and persistent GW signals buried in the foreground and background, posing various data analysis challenges. In order to empower potential scientific discoveries, the Mock Laser Interferometer Space Antenna (LISA) data challenge and the LISA data challenge (LDC) were developed. While LDC provides a baseline framework, the first LDC needs to be updated with more realistic simulations and adjusted detector responses for Taiji’s constellation. In this paper, we review the scientific objectives and the roadmap for Taiji, as well as the technical difficulties in data analysis and the data generation strategy, and present the associated data challenges. In contrast to LDC, we utilize second-order Keplerian orbit and second-generation time delay interferometry techniques. Additionally, we employ a new model for the extreme-mass-ratio inspiral waveform and stochastic GW background spectrum, which enables us to test general relativity and measure the non-Gaussianity of curvature perturbations. Furthermore, we present a comprehensive showcase of parameter estimation using a toy dataset. This showcase not only demonstrates the scientific potential of the Taiji data challenge (TDC) but also serves to validate the effectiveness of the pipeline. As the first data challenge for Taiji, we aim to build an open ground for data analysis related to Taiji sources and sciences. More details can be found on the official website (taiji-tdc.ictp-ap.org).

Key words： gravitational wave universe evolution Taiji data challenge

收稿日期: 2023-04-01 出版日期: 2023-08-10

Corresponding Author(s): Zhoujian Cao,Yue-Liang Wu

引用本文:

. [J]. Frontiers of Physics, 2023, 18(6): 64302.
Zhixiang Ren, Tianyu Zhao, Zhoujian Cao, Zong-Kuan Guo, Wen-Biao Han, Hong-Bo Jin, Yue-Liang Wu. Taiji data challenge for exploring gravitational wave universe. Front. Phys. , 2023, 18(6): 64302.

链接本文:

https://academic.hep.com.cn/fop/CN/10.1007/s11467-023-1318-y
https://academic.hep.com.cn/fop/CN/Y2023/V18/I6/64302

Tab.1

Tab.2

Fig.1

Fig.2

No.	$M T (M ⊙)$	$q$	$s 1$	$s 2$	$D L$ (Gpc)	$ι$	$ψ$	$λ$	$β$	$t c (y r)$	$? c$

1	$1.2 × 106$	0.3	0.1	0.2	53.39	$2 π / 3$	$π / 3$	$π / 10$	$π / 8$	$0.2$	1
2	$1.8 × 106$	0.8	0.14	0.12	16.02	$π$	$π / 3$	$π / 15$	$5 π / 4$	$0.4$	0.05
3	$2.4 × 106$	0.4	0.18	0.08	21.36	$5 π / 6$	$π / 3$	$π / 20$	$7 π / 4$	$0.6$	0.1
4	$1.5 × 106$	0.7	0.14	0.8	53.39	$π / 3$	$π / 3$	$π / 25$	$3 π / 4$	$0.8$	0.15
5	$6 × 105$	0.5	0.2	0.4	53.39	$π / 3$	$π / 3$	$π / 5$	$π / 4$	$1$	0.5
6	$1.2 × 106$	0.6	0.1	0.6	106.78	$π / 6$	$2 π / 3$	$π / 30$	$5 π / 4$	$1.2$	0.35
7	$2.4 × 106$	0.1	0.22	0.48	16.02	$4 π / 15$	$5 π / 3$	$π / 35$	$π / 8$	$1.4$	0.45
8	$1.2 × 106$	0.05	0.16	0.28	26.69	$13 π / 30$	$π / 3$	$2 π / 5$	$π / 12$	$1.6$	1
9	$1.8 × 106$	0.5	0.02	0.08	32.03	$14 π / 30$	$π / 3$	$3 π / 5$	$11 π / 40$	$1.601$	0.4
10	$1.2 × 107$	1	0.06	0.08	10.68	$π / 3$	$π / 3$	$6 π / 5$	$π / 4$	$1.8$	0.5

Tab.3

Name	Scientific objective	Technical challenge	Signals	Waveform model

TDC-1	1, 5, 6	7	1 MBHB signal	SEOBNRv4_opt
TDC-2-1	2, 5, 6	7	1 EMRI signal	PN5AAK
TDC-2-2	2, 5, 6	7	1 EMRI signal	XSPEG
TDC-3	3, 5, 6	7	43 VGB signals	Sinusoidal
TDC-4	3, 5, 6	1, 7	$3 × 107$ GB signals	Sinusoidal
TDC-5	4, 5, 6	2, 7	$2 × 105$ SOBBH signals	IMRPhenomD
TDC-6-1	5, 6, 7	7	SGWB	Power-law
TDC-6-2	5, 6, 7	7	SGWB	Non-Gaussian curvature perturbations
TDC-7	1, 3, 5, 6	1, 3, 7	10 MBHBs, 43 VGBs, $3 × 107 GBs$	SEOBNRv4_opt, Sinusoidal

Tab.4

Fig.3

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