Gravitational Wave Detection and Information Extraction via Neural Networks
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Experimental DesignGravitational Wave DetectionSimilar Papers 제목 키워드 기반
Detection of gravitational waves using topological data analysis and convolutional neural network: An improved approach
The gravitational wave detection problem is challenging because the noise is typically overwhelming. Convolutional neural networks (CNNs) have been successfully applied, but require a large training set and the accuracy …
Gravitational Wave DetectionTopological Data AnalysisSpecGrav -- Detection of Gravitational Waves using Deep Learning
Gravitational waves are ripples in the fabric of space-time that travel at the speed of light. The detection of gravitational waves by LIGO is a major breakthrough in the field of astronomy. Deep Learning has revolutioni…
AstronomyDeep LearningGPUSpace-based gravitational wave signal detection and extraction with deep neural network
Space-based gravitational wave (GW) detectors will be able to observe signals from sources that are otherwise nearly impossible from current ground-based detection. Consequently, the well established signal detection met…
Application of Common Spatial Patterns in Gravitational Waves Detection
Common Spatial Patterns (CSP) is a feature extraction algorithm widely used in Brain-Computer Interface (BCI) Systems for detecting Event-Related Potentials (ERPs) in multi-channel magneto/electroencephalography (MEG/EEG…
Brain Computer InterfaceEEGElectroencephalogram (EEG)regression+2Machine-learning non-stationary noise out of gravitational wave detectors
Signal extraction out of background noise is a common challenge in high precision physics experiments, where the measurement output is often a continuous data stream. To improve the signal to noise ratio of the detection…
BIG-bench Machine Learningparameter estimation