Gravitational-wave Detection

The Detection, Extraction and Parameter Estimation of Extreme-Mass-Ratio Inspirals with Deep Learning

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals (EMRIs). This endeavor presents a significant challenge due to the complex and lengthy EMRI signals, further compounded by …

Probing the gravitational wave background from cosmic strings with Alternative LISA-TAIJI network

As one of the detection targets of all gravitational wave detectors at present, stochastic gravitational wave background (SGWB) provides us an important way to understand the evolution of our universe. In this paper, we explore the feasibility of …

Detecting Extreme-Mass-Ratio Inspirals for Space-Borne Detectors with Deep Learning

Space-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 method, matched filtering, will …

Rapid search for massive black hole binary coalescences using deep learning

The coalescences of massive black hole binaries (MBHBs) are one of the main targets of space-based gravitational wave observatories. Such gravitational wave sources are expected to be accompanied by electromagnetic emission. Low latency time of …

Intelligent Noise Suppression for Gravitational Wave Observational Data

With the advent of gravitational-wave astronomy and the discovery of more compact binary coalescences, data quality improvement techniques are desired to handle the complex and overwhelming noise in gravitational wave (GW) observational data. Though …

First machine learning gravitational-wave search mock data challenge

We present the results of the first Machine Learning Gravitational-Wave Search Mock Data Challenge (MLGWSC-1). For this challenge, participating groups had to identify gravitational-wave signals from binary black hole mergers of increasing complexity …

Ensemble of deep convolutional neural networks for real-time gravitational wave signal recognition

With the rapid development of deep learning technology, more and more researchers apply it to gravitational wave (GW) data analysis. Previous studies focused on a single deep learning model. In this paper we design an ensemble algorithm combining a …

Sampling with prior knowledge for high-dimensional gravitational wave data analysis

Extracting knowledge from high-dimensional data has been notoriously difficult, primarily due to the so-called "curse of dimensionality" and the complex joint distributions of these dimensions. This is a particularly profound issue for …

Gravitational-wave Signal Recognition of LIGO Data by Deep Learning

Deep learning method develops very fast as a tool for data analysis these years. Such a technique is quite promising to treat gravitational wave detection data. There are many works already in the literature which used deep learning technique to …