9 citations · 20 across the 6 of their papers we have counts for
6 papers
Redshift-binned constraints on the Hubble constant under CDM, CPL, and Padé cosmography
Zhi-Yuan Mo, Kang Jiao, Tong-Jie Zhang
Motivated by recent claims of a possible redshift dependence in late-Universe determinations of the Hubble constant (H_0), we test the robustness of this behavior using multiple co…
Comparative Analysis of EMCEE, Gaussian Process, and Masked Autoregressive Flow in Constraining the Hubble Constant Using Cosmic Chronometers Dataset
Jing Niu, Jie-Feng Chen, Peng He +2
The Hubble constant () is essential for understanding the universe's evolution. Different methods, such as Affine Invariant Markov chain Monte Carlo Ensemble sampler (EMCEE),…
Constraining the Hubble Constant with a Simulated Full Covariance Matrix Using Neural Networks
Jing Niu, Peng He, Tong-Jie Zhang
The Hubble parameter, , plays a crucial role in understanding the expansion history of the universe and constraining the Hubble constant, . The Cosmic Chronomet…
Estimating Cosmological Parameters and Reconstructing Hubble Constant with Artificial Neural Networks: A Test with covariance matrix and mock H(z)
Jie-feng Chen, Tong-Jie Zhang, Peng He +2
In this work, we reconstruct the H(z) based on observational Hubble data with Artificial Neural Network, then estimate the cosmological parameters and the Hubble constant. The trai…
A Non-parametric Reconstruction of the Hubble Parameter Based on Radial Basis Function Neural Networks
Jian-Chen Zhang, Yu Hu, Kang Jiao +5
Accurately measuring the Hubble parameter is vital for understanding the expansion history and properties of the universe. In this paper, we propose a new method that supplements t…
Reconstruction of the dark energy scalar field potential by Gaussian process
Jing Niu, Kang Jiao, Peng He +1
Dark energy is believed to be responsible for the acceleration of the universe. In this paper, we reconstruct the dark energy scalar field potential using the Hubble paramet…