Gravitational wave signal denoising and merger time prediction with a deep neural network
文献类型：期刊论文
| 作者 | Xu YX(许宇翔); Wang, He; Du MH(杜明辉); Liang, Bo; Xu P(徐鹏) |
| 刊名 | PHYSICAL REVIEW D
 |
| 出版日期 | 2025-03-14 |
| 卷号 | 111期号:6页码:13 |
| ISSN号 | 2470-0010 |
| DOI | 10.1103/PhysRevD.111.063037 |
| 通讯作者 | Xu, Yuxiang(xuyuxiang22@mails.ucas.ac.cn) ; Wang, He(hewang@ucas.ac.cn) ; Xu, Peng(xupeng@imech.ac.cn) |
| 英文摘要 | The mergers of massive black hole binaries could generate rich electromagnetic emissions, which allow us to probe the environments surrounding these massive black holes and gain deeper insights into the high energy astrophysics. However, due to the short timescale of binary mergers, it is crucial to predict the time of the merger in advance to devise detailed observational plans. The overwhelming noise and slow accumulation of the signal-to-noise ratio in the inspiral phase make this task particularly challenging. To address this issue, we propose a novel deep neural denoising network in this study, capable of denoising a 30-day inspiral phase signal. Following the denoising process, we perform the detection and merger time prediction based on the denoised signals. Our results demonstrate that, for a 30-day inspiral phase data with a signal-to-noise ratio between 10 and 50 occurring no more than 10 days before the merger, our absolute prediction error for the merger time is generally within 24 h. |
| 分类号 | 二类/Q1 |
| WOS关键词 | BLACK-HOLE BINARIES |
| 资助项目 | National Key Research and Development Program of China[2021YFC2201901] ; National Key Research and Development Program of China[2021YFC2201903] ; National Key Research and Development Program of China[2020YFC2200601] ; National Key Research and Development Program of China[2020YFC2200901] ; National Key Research and Development Program of China[2021YFC2203004] ; National Science Foundation of China (NSFC)[12405076] ; National Science Foundation of China (NSFC)[12347103] ; National Science Foundation of China (NSFC)[12247187] ; International Partnership Program of Chinese Academy of Sciences[025GJHZ2023106GC] |
| WOS研究方向 | Astronomy & Astrophysics ; Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:001459609800016 |
| 资助机构 | National Key Research and Development Program of China ; National Science Foundation of China (NSFC) ; International Partnership Program of Chinese Academy of Sciences |
| 其他责任者 | 许宇翔 ; Wang, He ; 徐鹏 |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/100792]  |
| 专题 | 力学研究所_国家微重力实验室 |
| 推荐引用方式 GB/T 7714 | Xu YX,Wang, He,Du MH,et al. Gravitational wave signal denoising and merger time prediction with a deep neural network[J]. PHYSICAL REVIEW D,2025,111(6):13. |
| APA | 许宇翔,Wang, He,杜明辉,Liang, Bo,&徐鹏.(2025).Gravitational wave signal denoising and merger time prediction with a deep neural network.PHYSICAL REVIEW D,111(6),13. |
| MLA | 许宇翔,et al."Gravitational wave signal denoising and merger time prediction with a deep neural network".PHYSICAL REVIEW D 111.6(2025):13. |
入库方式： OAI收割
来源：力学研究所
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