LISA

Evolutionary and Reinforcement Learning Approaches for GW Data Analysis

2026/01/27 | Flash Talk @GWFREERIDE

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 …

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. …

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

Comprehensive review of data analysis challenges in space-based gravitational wave detection (LISA, Taiji, TianQin) and transformative applications of artificial intelligence in addressing these challenges.

Gravitational wave signal extraction against non-stationary instrumental noises with deep neural network

Sapce-borne gravitational wave antennas, such as LISA and LISA-like mission (Taiji and Tianqin), will offer novel perspectives for exploring our Universe while introduce new challenges, especially in data analysis. Aside from the known challenges …

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

Analysis of LISA-TAIJI network configurations for detecting stochastic gravitational wave background from cosmic strings, finding LISA-TAIJIc offers optimal sensitivity for constraining string tension at G𝜇~10^-17.

Gravitational Wave Detection and AI Technology: New Methods for Unveiling the Mysteries of the Universe

International Workshop on Intelligent Computing in Astronomy 'Computing Senses Cosmos' (2023) @Zhejiang Lab, Hangzhou, China https://en.zhejianglab.com/newsevents/AI4Astro/

空间引力波科学数据处理的挑战与人工智能技术应用

2023年“第三届空间科学大会”空间引力波探测和精密测量与引力宇宙 | 浙江·德清 https://cssr.kejie.org.cn/meeting/cssa2023/

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))