29 citations · 133 across the 15 of their papers we have counts for
15 papers
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…
Cosmological neutrino N-body simulations of dark matter halo
Yu Chen, Chang-Zhi Lu, Juan Li +3
The study of massive neutrinos and their interactions is a critical aspect of contemporary cosmology. Recent advances in parallel computation and high-performance computing provide…
Effect of Neutrinos on Angular Momentum of Dark Matter Halo
Yu Chen, Chang-Zhi Lu, Yu Lu +2
Massive neutrinos are expected to affect the large-scale structure formation, including the major component of solid substances, dark matter halos. How halos are influenced by neut…
A Search for Extraterrestrial Technosignatures in Archival FAST Survey Data Using a New Procedure
Yu-Chen Wang, Zhen-Zhao Tao, Zhi-Song Zhang +4
The "search for extraterrestrial intelligence" (SETI) commensal surveys aim to scan the sky to find possible technosignatures from the extraterrestrial intelligence (ETI). The miti…
Novel Cosmological Joint Constraints in Multidimensional Observables Space with Redshift-free Inferences
Wei Hong, Kang Jiao, Yu-Chen Wang +2
Cosmology constraints serve as a crucial criterion in discriminating cosmological models. The traditional combined method to constrain the cosmological parameters designates the co…
Kernel Selection for Gaussian Process in Cosmology: with Approximate Bayesian Computation Rejection and Nested Sampling
Hao Zhang, Yu-Chen Wang, Tong-Jie Zhang +1
Gaussian Process (GP) has gained much attention in cosmology due to its ability to reconstruct cosmological data in a model-independent manner. In this study, we compare two method…
Test of Artificial Neural Networks in Likelihood-free Cosmological Constraints: A Comparison of IMNN and DAE
Jie-Feng Chen, Yu-Chen Wang, Tingting Zhang +1
In the procedure of constraining the cosmological parameters with the observational Hubble data and the type Ia supernova data, the combination of Masked Autoregressive Flow and De…
A Reliable Calibration of HII Galaxies Hubble Diagram with Cosmic Chronometers and Artificial Neural Network
Jian-Chen Zhang, Kang Jiao, Tingting Zhang +2
The relation of HII galaxies (HIIGx) calibrated by a distance indicator is a reliable standard candle for measuring the Hubble constant . The most straightforward calibr…
Statistical distribution of HI 21cm intervening absorbers as potential cosmic acceleration probes
Chang-Zhi Lu, Tingting Zhang, Tong-Jie Zhang
Damped Lyman- Absorber (DLA), or HI 21cm Absorber (H21A), is an important probe to model-independently measure the acceleration of spectroscopic velocity () via th…
Toward a direct measurement of the cosmic acceleration: the first preparation with FAST
Chang-Zhi Lu, Kang Jiao, Tingting Zhang +2
Damped Lyman- Absorber(DLA) of HI 21cm system is an ideal probe to directly measure cosmic acceleration in real-time cosmology via Sandage-Loeb(SL) test. During short observatio…
Cosmological Constraints on the Coupling Model from Observational Hubble Parameter and Baryon Acoustic Oscillation Measurements
Shulei Cao, Tong-Jie Zhang, Xinya Wang +1
In the paper, we consider two models in which dark energy is coupled with either dust matter or dark matter, and discuss the conditions that allow more time for structure formation…
A new analytical approximation of luminosity distance by optimal HPM-Padé technique
Bo Yu, Jian-Chen Zhang, Tong-Jie Zhang +1
By the use of homotopy perturbation method-Padé (HPM-Padé) technique, a new analytical approximation of luminosity distance in the flat universe is proposed, which has the advantag…
Likelihood-free Cosmological Constraints with Artificial Neural Networks: An Application on Hubble Parameters and SNe Ia
Yu-Chen Wang, Yuan-Bo Xie, Tong-Jie Zhang +3
The errors of cosmological data generated from complex processes, such as the observational Hubble parameter data (OHD) and the Type Ia supernova (SN Ia) data, cannot be accurately…
The constraint ability of Hubble parameter by gravitational wave standard sirens on cosmological parameters
Tong-Jie Zhang, Yang Liu, Zhi-E Liu +3
In this paper, we present the application of a new method measuring Hubble parameter by using the anisotropy of luminosity distance() of the gravitational wave(GW) st…
Model-independent determination of cosmic curvature based on Padé approximation
Shi-Yu Li, Yun-Long Li, Tong-Jie Zhang +1
Given observations of the standard candles and the cosmic chronometers, we apply Padé parameterization to the comoving distance and the Hubble paramter to find how stringent the co…