AI

AI × 宇宙学:从算法工具到科学发现的新范式

AI and Cosmology | 2026/01/10 10:00-11:00 | 第五届后羿系列研讨会

大模型驱动的科学计算新范式:自动化算法发现及其在引力波探测中的应用

"LLM and Science" Program, ITP-CAS, December 2025

AI探索引力波奥秘

超算前沿直播间

Advances and Analysis in Global Fitting Techniques

空间引力波探测数据分析研讨会会议

Deep Learning for Gravitational Wave Detection and Analysis

2024 东北大学·青年学者学术论坛

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 …

基于深度学习的引力波探测与参数反演方法探索

学术讲座 | 湖北 · 武汉大学

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 …