Gravitational Waves

Rapid Parameter Estimation for Merging Massive Black Hole Binaries Using Continuous Normalizing Flows

Detecting the coalescences of massive black hole binaries (MBHBs) is one of the primary targets for space-based gravitational wave observatories such as LISA, Taiji, and Tianqin. The fast and accurate parameter estimation of merging MBHBs is of great …

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 …

Search for exotic gravitational wave signals beyond general relativity using deep learning

The direct detection of gravitational waves by LIGO has confirmed general relativity (GR) and sparked rapid growth in gravitational wave (GW) astronomy. However, subtle post-Newtonian (PN) deviations observed during the analysis of high …

Gravitational Wave Signal Denoising and Merger Time Prediction By Deep Neural Network

The mergers of massive black hole binaries could generate rich electromagnetic emissions, which allow us to probe the environments surrounding these massive black holes and gain deeper insights into the high energy astrophysics. However, due to the …

Rapid Parameter Estimation for Extreme Mass Ratio Inspirals Using Machine Learning

Extreme-mass-ratio inspiral (EMRI) signals pose significant challenges in gravitational wave (GW) astronomy owing to their low-frequency nature and highly complex waveforms, which occupy a high-dimensional parameter space with numerous variables. …

Enhancing Gravitational Wave Astronomy with Artificial Intelligence

2024年粒子天体物理重点实验室系列学术报告 | 高能所

Enhancing Gravitational Wave Astronomy with Artificial Intelligence

NZ Gravity seminar | University of Auckland

Frontiers of AI in Gravitational Wave Astronomy

学术讲座 | 甘肃 · 兰州大学

WaveFormer: Transformer-based Denoising Method for Gravitational-wave Data

GWAC 2024 | 湖北 · 荆州

Challenges in space-based gravitational wave data analysis and applications of artificial intelligence

As space-based gravitational wave detection projects such as LISA, Taiji, and Tianqin continue to advance, we are on the cusp of gaining a new viewpoint on observing the universe.However, the scientific data processing for these projects faces …