119 citations · 611 across the 20 of their papers we have counts for
20 papers
Sound-Horizon-Independent Test of Cosmic Distance Duality Relation Using Artificial Neural Networks and Gaussian Processes
Bo-Hao Jiang, Guo-Jian Wang, Tao Yang
The cosmic distance duality relation (CDDR), , is a fundamental relation in modern cosmology linking luminosity distance and angular diamete…
In search of an interaction in the dark sector through Gaussian Process and ANN approaches
Mazaharul Abedin, Guo-Jian Wang, Yin-Zhe Ma +1
Whether the current observational data indicate any evidence of interaction between the dark sector is a matter of supreme interest at the present moment. This article searched for…
When LAMOST meets Gaia DR3 Exploring the metallicity of open clusters
R. Zhang, Guo-Jian Wang, Yuxi +9
Context. Open clusters (OCs) are valuable probes of stellar population characteristics. Their age and metallicity provide insights into the chemical enrichment history of the Milky…
CMBFSCNN: Cosmic Microwave Background Polarization Foreground Subtraction with Convolutional Neural Network
Ye-Peng Yan, Si-Yu Li, Guo-Jian Wang +2
In our previous study, we introduced a machine-learning technique, namely CMBFSCNN, for the removal of foreground contamination in cosmic microwave background (CMB) polarization da…
Lensing reconstruction from the cosmic microwave background polarization with machine learning
Ye-Peng Yan, Guo-Jian Wang, Si-Yu Li +2
The lensing effect of the cosmic microwave background (CMB) is a powerful tool for our study of the distribution of matter in the universe. Currently, the quadratic estimator (EQ)…
CoLFI: Cosmological Likelihood-free Inference with Neural Density Estimators
Guo-Jian Wang, Cheng Cheng, Yin-Zhe Ma +3
In previous works, we proposed to estimate cosmological parameters with the artificial neural network (ANN) and the mixture density network (MDN). In this work, we propose an impro…
Delensing of Cosmic Microwave Background Polarization with machine learning
Ye-Peng Yan, Guo-Jian Wang, Si-Yu Li +1
Primordial B-mode detection is one of the main goals of next-generation cosmic microwave background (CMB) experiments. Primordial B-modes are a unique signature of primordial gravi…
Recovering Cosmic Microwave Background Polarization Signals with Machine Learning
Ye-Peng Yan, Guo-Jian Wang, Si-Yu Li +1
Primordial B-mode detection is one of the main goals of current and future cosmic microwave background (CMB) experiments. However, the weak B-mode signal is overshadowed by several…
Likelihood-free Inference with Mixture Density Network
Guo-Jian Wang, Cheng Cheng, Yin-Zhe Ma +1
In this work, we propose using the mixture density network (MDN) to estimate cosmological parameters. We test the MDN method by constraining parameters of the CDM and CDM mod…
Recovering the CMB Signal with Machine Learning
Guo-Jian Wang, Hong-Liang Shi, Ye-Peng Yan +4
The cosmic microwave background (CMB), carrying the inhomogeneous information of the very early universe, is of great significance for understanding the origin and evolution of our…
ECoPANN: A Framework for Estimating Cosmological Parameters using Artificial Neural Networks
Guo-Jian Wang, Si-Yao Li, Jun-Qing Xia
In this work, we present a new method to estimate cosmological parameters accurately based on the artificial neural network (ANN), and a code called ECoPANN (Estimating Cosmologica…
Machine Learning the Cosmic Curvature in a Model-independent Way
Guo-Jian Wang, Xiao-Jiao Ma, Jun-Qing Xia
In this work, we achieve the determination of the cosmic curvature in a cosmological model-independent way, by using the Hubble parameter measurements and type Ia supe…
Reconstructing Functions and Estimating Parameters with Artificial Neural Networks: A Test with the Hubble Parameter and SNe Ia
Guo-Jian Wang, Xiao-Jiao Ma, Si-Yao Li +1
In this work, we propose a new nonparametric approach for reconstructing a function from observational data using an Artificial Neural Network (ANN), which has no assumptions about…
Curvature from strong gravitational lensing: a spatially closed Universe or systematics?
Zhengxiang Li, Xuheng Ding, Guo-Jian Wang +2
Model-independent constraints on the spatial curvature are not only closely related to important problems such as the evolution of the Universe and properties of dark energy, but a…
Model-independent Constraints on Cosmic Curvature and Opacity
Guo-Jian Wang, Jun-Jie Wei, Zheng-Xiang Li +2
In this paper, we propose to estimate the spatial curvature of the universe and the cosmic opacity in a model-independent way with expansion rate measurements, , and type Ia…
Strongly lensed repeating Fast Radio Bursts as precision probes of the universe
Zhengxiang Li, He Gao, Xu-Heng Ding +2
Fast Radio bursts (FRBs), bright transients with millisecond durations at GHz and typical redshifts probably , are likely to be gravitationally lensed by intervening g…
Test of the FLRW metric and curvature with strong lens time delays
Kai Liao, Zhengxiang Li, Guo-Jian Wang +1
We present a new model-independent strategy for testing the Friedmann-Lema\^ıtre-Robertson-Walker metric and constraining cosmic curvature, based on future time delay measurements…
Evolutions and Calibrations of Long Gamma-Ray Bursts Luminosity Correlations Revisited
Guo-Jian Wang, Hai Yu, Zheng-Xiang Li +2
Luminosity correlations of long Gamma-ray bursts (GRB) are extensively proposed as an effective complementarity to trace the Hubble diagram of Universe at high redshifts, which is…
Revisiting Studies of the Statistical Property of a Strong Gravitational Lens System and Model-independent Constraint on the Curvature of the Universe
Jun-Qing Xia, Hai Yu, Guo-Jian Wang +4
In this paper we use a recently compiled data set, which comprises 118 galactic-scale strong gravitational lensing (SGL) systems to constrain the statistic property of SGL system,…
Model-independent estimations for the curvature from standard candles and clocks
Zhengxiang Li, Guo-Jian Wang, Kai Liao +1
Model-independent estimations for the spatial curvature not only provide a test for the fundamental Copernican principle assumption, but also can effectively break the degeneracy b…