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| Denoising and detection for binary black hole gravitational waves in the context of the Einstein Telescope | |
Ma, Cunliang1,2; Liu, Zehua2; Gao, Zhifu3 ; Cao, Zhoujian4,5; Jia, Mingzhen1,2; Wei, Kai1,2; Dai, Tanming1,2; Wu, Junqin1,2
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| 2025-07-01 | |
| Source Publication | SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY
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| ISSN | 1674-7348 |
| Volume | 68Issue:7Pages:279512 |
| Contribution Rank | 3 |
| Abstract | With the advent of third-generation (3G) ground-based gravitational wave (GW) detectors, such as the Einstein Telescope (ET), we anticipate a substantial enhancement in sensitivity across a wide frequency range. The machine learning approach for GW search necessitates an update to address the challenges posed by data features that deviate from those of 2G detectors. In this paper, we introduce a novel GW search pipeline specifically designed for 3G ground-based detectors like ET. Our pipeline leverages three types of deep learning models: an envelope extraction model, a denoising model, and an astrophysical origin discrimination model. Additionally, we propose a signal consistency test across multiple detectors. Given that denoising results vary among different detectors, we present a new method for selecting the optimal waveform. This selected waveform serves as a template for estimating the signal-to-noise ratio (SNR) of strain data from all detectors. Furthermore, if 3G detectors operate alongside 2G detectors, the templates derived from 3G detector data can be utilized to predict the SNR for 2G detectors, significantly reducing the computational burden of GW searches for the latter. We also assess the robustness of our method when applied to data containing binary neutron star (BNS) foreground noise. We believe that the proposed method holds promise for detecting BBH events in future 3G detectors. |
| Keyword | gravitational wave search machine learning Einstein Telescope gravitational wave denoising |
| DOI | 10.1007/s11433-025-2673-5 |
| Indexed By | SCI |
| Language | 英语 |
| WOS Keyword | NEUTRON-STAR MERGERS ; 3RD OBSERVING RUN ; PARAMETER-ESTIMATION ; ADVANCED LIGO ; COSMIC EXPLORER ; COMPACT-OBJECT ; SEARCH ; PIPELINE ; SIGNALS ; LOCALIZATION |
| Funding Project | Gravitational-Wave Open Science Center, a service of LIGO Laboratory ; LIGO Scientific Collaboration ; Virgo Collaboration ; National Key Research and Development Program of China[2021YFC2203001] ; National Key Research and Development Program of China[2022YFC2205202] ; National Natural Science Foundation of China[12463012] ; National Natural Science Foundation of China[12288102] ; National Natural Science Foundation of China[11920101003] ; National Natural Science Foundation of China[12021003] ; National Natural Science Foundation of China[11864014] ; Natural Science Foundation of Jiangxi[20224BAB211012] ; Jiangxi Province Key Laboratory of Multidimensional Intelligent Perception and Control of China[2024SSY03161] |
| WOS Research Area | Physics |
| WOS Subject | Physics, Multidisciplinary |
| WOS ID | WOS:001499617400003 |
| Publisher | SCIENCE PRESS |
| Funding Organization | Gravitational-Wave Open Science Center, a service of LIGO Laboratory ; LIGO Scientific Collaboration ; Virgo Collaboration ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; Natural Science Foundation of Jiangxi ; Jiangxi Province Key Laboratory of Multidimensional Intelligent Perception and Control of China |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.xao.ac.cn/handle/45760611-7/7805 |
| Collection | 射电天文研究室_脉冲星研究团组 |
| Corresponding Author | Cao, Zhoujian |
| Affiliation | 1.Jiangxi Prov Key Lab Multidimens Intelligent Perce, Ganzhou 341000, Peoples R China 2.Jiangxi Univ Sci & Technol, Sch Informat Engn, Ganzhou 341000, Peoples R China 3.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China 4.Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing 100190, Peoples R China 5.UCAS, Hangzhou Inst Adv Study, Sch Fundamental Phys & Math Sci, Hangzhou 310024, Peoples R China |
| Recommended Citation GB/T 7714 | Ma, Cunliang,Liu, Zehua,Gao, Zhifu,et al. Denoising and detection for binary black hole gravitational waves in the context of the Einstein Telescope[J]. SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY,2025,68(7):279512. |
| APA | Ma, Cunliang.,Liu, Zehua.,Gao, Zhifu.,Cao, Zhoujian.,Jia, Mingzhen.,...&Wu, Junqin.(2025).Denoising and detection for binary black hole gravitational waves in the context of the Einstein Telescope.SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY,68(7),279512. |
| MLA | Ma, Cunliang,et al."Denoising and detection for binary black hole gravitational waves in the context of the Einstein Telescope".SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY 68.7(2025):279512. |
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| Ma-2025-Denoising an（2322KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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