Classifying the gravitational waves using the deep learning technique

Al Mahmud Al Mamun, Md. Ashik Iqbal
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引用次数: 1

Abstract

Gravitational waves are related to the concept of vibration of space-time curvature. When the body of heavy masses lies on the four-dimensional space-time and changes their position with turbulence motion then actually they create a disturbance in the space. The disturbance travels outward from the origin having light velocity is known as gravitational waves. Laser Interferometer Gravitational-Wave Observatory (LIGO) scientific teamwork declared the identification of these waves. In this paper, we review Gravitational waves, Detection of gravitational waves, deep learning for the classification of gravitational waves. We design and develop a deep learning system to classification gravitational waves of the dataset ‘Gravity Spy (Gravitational waves)’ that is made up of the LIGO images. The goals of this research are to gain a piece of reasonable and useful knowledge about Gravitational waves and propose an effective deep learning network system to classify the gravitational waves. The accuracy achieved by our model is 99.34%.
使用深度学习技术对引力波进行分类
引力波与时空曲率的振动概念有关。当大质量物体位于四维时空上,并随着湍流运动而改变其位置时,实际上会在空间中产生扰动。以光速从原点向外传播的扰动被称为引力波。激光干涉仪引力波天文台(LIGO)的科学团队宣布确认了这些引力波。本文综述了引力波、引力波探测、引力波分类的深度学习。我们设计并开发了一个深度学习系统,用于对由LIGO图像组成的数据集“Gravity Spy(引力波)”中的引力波进行分类。本研究的目标是获得关于引力波的合理和有用的知识,并提出一种有效的深度学习网络系统来对引力波进行分类。该模型的准确率为99.34%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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