论文标题
引力波检测和通过神经网络提取信息
Gravitational Wave Detection and Information Extraction via Neural Networks
论文作者
论文摘要
激光干涉仪重力波观测站(LIGO)是第一个测量引力波的实验室。需要一种非凡的实验设计来测量距离的变化远小于质子的半径。同样,数据分析以确认和提取信息是一项非常艰巨的任务。在这里,它显示了一个人工神经网络上的计算程序基础,以检测引力波事件并从Ligo数据中提取其降落时间的知识。通过此建议,可以制作一个概率温度计进行引力波检测,并获取有关创建现象的天文体系统的物理信息。在这里,划线时间是通过直接数据度量来确定的,而无需使用数值相对论技术和高计算能力。
Laser Interferometer Gravitational-Wave Observatory (LIGO) was the first laboratory to measure the gravitational waves. It was needed an exceptional experimental design to measure distance changes much less than a radius of a proton. In the same way, the data analyses to confirm and extract information is a tremendously hard task. Here, it is shown a computational procedure base on artificial neural networks to detect a gravitation wave event and extract the knowledge of its ring-down time from the LIGO data. With this proposal, it is possible to make a probabilistic thermometer for gravitational wave detection and obtain physical information about the astronomical body system that created the phenomenon. Here, the ring-down time is determined with a direct data measure, without the need to use numerical relativity techniques and high computational power.