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arXiv 2209.02673gr-qcastro-ph.IM
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用于双黑洞并合引力波信号检测的联合啁啾率-时间-频率变换

A Joint-Chirp-Rate-Time-Frequency Transform for BBH Merger Gravitational Wave Signal Detection

Xiyuan Li, Martin Houde, Jignesh Mohanty, S. R. Valluri

AI总结:

针对强非平稳噪声下并合引力波快速调频难以识别的问题,提出JCTFT及啁啾率增强频谱图生成方法,并在信噪比6–10的模拟信号中经InceptionV3验证平均检测能力提升14%。

摘要:

双黑洞(BBH)和双中子星(BNS)并合引力波(GW)信号的低延迟检测,对于实现此类系统的多信使观测至关重要。并合引力波信号具有不断变化的频率,并受到非平稳噪声的污染。早期关于非模板化并合信号检测技术的研究使用基于传统傅里叶变换的时频分解方法生成频谱图,这些方法在强背景噪声下难以识别并合信号中的快速频率变化。为解决这一问题,我们提出了联合啁啾率-时间-频率变换(JCTFT),其中使用复值窗函数来调制输入信号的幅度、频率和相位。此外,我们概述了利用JCTFT结果生成啁啾率增强时频谱图的技术。我们使用InceptionV3图像分类神经网络证明,在信噪比介于6和10之间的模拟探测器信号中,与使用Q变换频谱图训练的同一网络相比,平均可实现14%的并合可检测性提升。JCTFT是一种通用变换技术,可应用于现有及第三代引力波探测器信号。进一步研究将致力于提高JCTFT的效率和性能。

英文摘要:

Low-latency detection of Binary Black Hole (BBH) and Binary Neutron Star (BNS) merger Gravitational Wave (GW) signals is essential for enabling multi-messenger observations of such systems. The merger GW signals have varying frequencies and are contaminated by non-stationary noises. Earlier studies of non-templated merger signal detection techniques used traditional Fourier transform-based time-frequency decomposition methods for spectrogram generation, which have had difficulties identifying rapid frequency changes in merger signals with heavy background noise. To address this problem, we introduce the Joint-Chirp-rate-Time-Frequency Transform (JCTFT), in which complex-valued window functions are used to modulate the amplitude, frequency, and phase of the input signal. In addition, we outline the techniques for generating chirp-rate-enhanced time-frequency spectrograms from the results of a JCTFT. We demonstrate an average of 14 improved merger detectability among simulated detector signals with Signal-to-Noise Ratios between 6 and 10 using the InceptionV3 image classification neural network compared to the same network trained with Q-transform spectrograms. The JCTFT is a general transformation technique that can be applied to existing and third-generation GW detector signals. Further studies will aim to improve the efficiency and performance of the JCTFT.

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