6 papers
FluxMC: Rapid and High-Fidelity Inference for Space-Based Gravitational-Wave Observations
Bo Liang, Chang Liu, Hanlin Song +11
Bayesian inference in the physical sciences faces a fundamental challenge: the imperative for high-fidelity physical modeling often clashes with the intrinsic limitations of stocha…
Towards Realistic Detection Pipelines of Taiji: New Challenges in Data Analysis and High-Fidelity Simulations of Space-Based Gravitational Wave Antenna
Minghui Du, Pengcheng Wang, Ziren Luo +23
Taiji, a Chinese space-based gravitational wave (GW) detection project, aims to explore the millihertz GW universe with unprecedented sensitivity. By observing astrophysical and co…
Source Confusion of Massive Black Hole Binaries for the Taiji Mission
Qing Diao, Hongxin Wang, Manjia Liang +4
We systematically investigate the source confusion of massive black hole binaries (MBHBs) for the Taiji space-based gravitational wave mission. Source confusion, arising from the o…
Recent Advances in Simulation-based Inference for Gravitational Wave Data Analysis
Bo Liang, He Wang
The detection of gravitational waves by the LIGO-Virgo-KAGRA collaboration has ushered in a new era of observational astronomy, emphasizing the need for rapid and detailed paramete…
Gravitational Wave Signal Denoising and Merger Time Prediction By Deep Neural Network
Yuxiang Xu, He Wang, Minghui Du +2
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 de…
Rapid Parameter Estimation for Merging Massive Black Hole Binaries Using Continuous Normalizing Flows
Bo Liang, Minghui Du, He Wang +6
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. T…