Publications

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

Parameter Inference for Coalescing Massive Black Hole Binaries Using Deep Learning

(This article belongs to the [Special Issue Newest Results in Gravitational Waves and Machine Learning](https://www.mdpi.com/journal/universe/special_issues/48U1E55JLC))

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 …

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 …

Warm inflation with a generalized Langevin equation scenario

In this paper, we discuss the warm inflation model with both a Langevin equation and a generalized Langevin equation scenario. As a brief picture to illustrate the basic properties of stochastic differential equation in warm inflation, this paper is …

Gravitational wave from warm inflation

A fundamental prediction of inflation is a nearly scale-invariant spectrum of gravitational wave. The features of such a signal provide extremely important information about the physics of the early universe. In this paper, we focus on several topics …