19 citations · 53 across the 35 of their papers we have counts for
36 papers
Correlated Galactic Confusion Foreground for the LISA-Taiji-TianQin Network and Its Impacts on Resolvable-Source Analysis
Minghui Du, Peng Xu, Ziren Luo
The millihertz gravitational-wave sky is expected to be observed by a network of space-based detectors (LISA, Taiji, and TianQin) in the 2030s. A dominant noise in this band is the…
Full-Covariance Bayesian Inference of Stochastic Gravitational Wave Backgrounds with Time-Domain Simulations for Taiji-like Missions
Qingyuan Liang, Ju Chen, Minghui Du +1
For Taiji-like missions, we implement a Bayesian spectral inference framework that combines second-generation time-domain (TD) simulations of time-delay interferometry (TDI) with a…
FUSE: FK-Steered Multi-Modal Flow Matching for Efficient Simulation-Based Posterior Estimation
Weichen Qin, Yufan Xie, Peihao Wang +8
Simulation-Based Inference (SBI) is critical for scientific discovery, with generative models offering a promising path toward efficient inference. However, existing methods strugg…
Measuring the Hubble constant with strongly lensed gravitational waves from space-based detector networks
Yong Yuan, Minghui Du, Wen-Fan Feng +4
The measurement of the Hubble constant plays a central role in modern cosmology. In this work, we investigate the potential of strongly lensed gravitational-wave (SLGW) signa…
Ringdown Signatures of Dehnen Dark Matter Halos: Fluid Modes and Detectability with Space-Based Detectors
Manjia Liang, Minghui Du, Qing Diao +5
In this work, we investigate the feasibility of using ringdown waveforms from supermassive black holes immersed in dark-matter halos to extract both the intrinsic black-hole parame…
Physics informed operator learning of parameter dependent spectra
Haohao Gu, Sensen He, Hanlin Song +6
Spectral problems governed by differential operators underpin a wide range of physical systems, yet remain computationally challenging because their spectra depend sensitively on c…
High-Precision Ground Characterization of Test-Mass Magnetic Properties for the Taiji Gravitational Wave Mission via a Physics-Informed Neural Framework
Chang Liu, Qiong Deng, Huadong Li +12
Taiji is a gravitational wave detection mission in space initiated by the Chinese Academy of Sciences, which will open the millihertz window through a heliocentric triangular const…
Bayesian Analysis of Gravitational Wave Microlensing Effects from Galactic Double White Dwarfs
Yan Sun, Yong Yuan, Minghui Du +3
Gravitational waves (GWs) from the galactic double white dwarf (DWD) systems are one of the primary targets for upcoming space-based detectors. Due to their vast abundance and wide…
Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows
Tian-Yang Sun, Bo Liang, Ji-Yu Song +6
Transient noise artifacts, commonly referred to as glitches, pose a major challenge to parameter inference for space-based gravitational-wave (GW) observations. We develop a glitch…
A Dynamical Equilibrium Linking Nanohertz Stochastic Gravitational Wave Background to Cosmic Structure Formation
Manjia Liang, Peng Xu, Ruijun Shi +6
The stochastic gravitational wave background (SGWB) is conventionally treated as a passive relic of its astrophysical and cosmological sources, with negligible back-reaction on the…
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…
An Opacity-Free Test of the Cosmic Distance Duality Relation Using Strongly Lensed Gravitational Wave Signals with Space-Based Detector Networks
Yong Yuan, Minghui Du, Benyang Zhu +4
The cosmic distance duality relation (CDDR), expressed as , is a fundamental relation in modern cosmology. In this work, we apply a method to test the CDDR…
Detection of Lensed Gravitational Waves in the Millihertz Band Using Frequency-Domain Lensing Feature Extraction Network
Tianlong Wang, Tianyu Zhao, Minghui Du +3
The space-based gravitational wave (GW) detectors are expected to observe lensed GW events, offering new opportunities for cosmology and fundamental physics.Across the millihertz b…
Detectability of axion-like dark matter for different time-delay interferometry combinations in space-based gravitational wave detectors
Yong-Yong Liu, Jing-Rui Zhang, Ming-Hui Du +3
In the space-based gravitational wave detections, the axion-like dark matter would alter the polarization state of the laser link between spacecrafts due to the birefringence effec…
Gravitomagnetic-Hydrodynamics and Turbulence in Early Universe
Jiaxiang Liang, Peng Xu, Minghui Du +4
The nonlinear coupling between spacetime geometry and matter in the early Universe remains a frontier in theoretical cosmology. By introducing a novel gravitomagnetic-hydrodynamic…
Estimating Orbital Parameters of Direct Imaging Exoplanet Using Neural Network
Bo Liang, Hanlin Song, Chang Liu +9
In this work, we propose a flow-matching Markov chain Monte Carlo (FM-MCMC) algorithm for estimating the orbital parameters of exoplanetary systems, especially for those only one e…
Inter-Spacecraft Tilt-to-Length Noise Reduction Algorithm for Taiji Mission
Qiong Deng, Leiqiao Ye, Ke An +6
The Taiji mission for space-based gravitational wave (GW) detection employs laser interferometry to measure picometer-scale distance variations induced by GWs. The tilt-to-length (…
Bayesian Analysis of Wave-Optics Gravitationally Lensed Massive Black Hole Binaries with Space-Based Gravitational Wave Detector
Yong Yuan, Minghui Du, Xin-yi Lin +2
Within a Bayesian statistical framework, we jointly estimate the source and lens parameters and evaluate the relative evidence between the lensed and unlensed models. This work foc…
Toward Efficient and Accurate EMRI Parameter Estimation: A Machine Learning-Enhanced MCMC Framework
Bo Liang, Chang Liu, Hanlin Song +12
The detection of gravitational waves from extreme-mass-ratio inspirals (EMRIs) in space-based antennas like Taiji and Laser Interferometer Space Antenna promises deep insights into…
Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises
Minghui Du, Ziren Luo, Peng Xu
The data analysis of space-based gravitational wave detectors like Taiji faces significant challenges from non-stationary noise, which compromises the efficacy of traditional frequ…
Extending the micro-Hertz detection horizons via orbital resonance effect for geocentric gravitational wave antennas
Qiong Deng, Minghui Du, Peng Xu +2
The Hz gravitational wave band holds crucial insights into coalescing supermassive black hole binaries and stochastic backgrounds but remains inaccessible due to technical chall…
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…
Primordial Black Holes Formed during Magneto-Hydrodynamic Turbulence in The Early Universe as Dominant Part of Dark Matter
Jia-xiang Liang, Peng Xu, Ming-hui Du +1
Primordial black holes (PBHs) offer a compelling candidate for dark matter. The production of PBHs through well-tested and accepted physical processes is highly worthy of investiga…