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arXiv 2603.06010gr-qcastro-ph.IM
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引力波天文学中的加速时域分析

Accelerated Time-domain Analysis for Gravitational Wave Astronomy

International Centre for Theoretical Sciences - Tata Institute of Fundamental Research(国际理论科学中心 - 塔塔基础研究所);Inter-University Centre for Astronomy and Astrophysics(大学间天文学与天体物理学中心);Institute for Gravitation & the Cosmos, Department of Physics, Penn State University(宾夕法尼亚州立大学物理学院引力与宇宙研究中心)

Vaishak Prasad

AI总结:

本文提出了一种完整的时域引力波推断方法,利用结构化线性代数和硬件加速实现大规模似然评估,验证了该方法在引力波天文中的应用。

摘要:

目前大多数紧凑双星搜索和参数估计管道通过频率域内积近似评估高斯噪声似然,这在分析引力波信号上取得了巨大成功。然而,频率域分析本身也有局限性。本文开发了一种自包含、端到端的完全时域引力波推断方法,并展示了利用结构化线性代数、软件和硬件加速实现大规模似然评估的实现。通过注入验证,我们展示了似然评估和现代GPU上的加速效果。我们介绍了tdanalysis,一种能够处理间隙、尖锐边界和多个不连续段的加速实现,并支持GPU。我们展示了其在引力波天文中的某些应用。

英文摘要:

Most current compact-binary searches and parameter-estimation pipelines evaluate the Gaussian-noise likelihood approximately using frequency-domain inner products with great success in analyzing gravitational-wave signals. This is historically motivated by (i) the approximate stationarity of detector noise on sufficiently long timescales, allowing a circulant approximation in the domain that diagonalizes the noise covariance in the Fourier basis, and (ii) the efficiency of matched filtering via fast Fourier transforms. However, the advantage of frequency-domain analysis comes with its own limitations. In this article, we develop a self-contained, end-to-end, \emph{fully time-domain} formulation of gravitational-wave inference and present an implementation that makes the likelihood evaluation practical at scale by exploiting structured linear algebra, software, and hardware acceleration. We validate the method using injections and demonstrate speedups for likelihood evaluation and on modern GPUs. We present \emph{tdanalysis}, an accelerated implementation that handles gaps, sharp boundaries, and multiple disjoint segments, and supports GPUs. We demonstrate some of its applications in gravitational wave astronomy.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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