1 code implementation • 14 May 2020 • 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 Cosmological Parameters with ANN) is developed to achieve parameter inference.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics Data Analysis, Statistics and Probability
1 code implementation • 8 Oct 2019 • Guo-Jian Wang, Xiao-Jiao Ma, Si-Yao Li, Jun-Qing Xia
We find that both $H(z)$ and $D_L(z)$ can be reconstructed with high accuracy.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics Data Analysis, Statistics and Probability
no code implementations • 6 Nov 2013 • Matteo Costanzi, Francisco Villaescusa-Navarro, Matteo Viel, Jun-Qing Xia, Stefano Borgani, Emanuele Castorina, Emiliano Sefusatti
We find that, in a massive neutrino cosmology, our correction to the halo mass function produces a shift in the $\sigma_8(\Omega_{\rm m}/0. 27)^\gamma$ relation which can be quantified as $\Delta \gamma \sim 0. 05$ and $\Delta \gamma \sim 0. 14$ assuming one ($N_\nu=1$) or three ($N_\nu=3$) degenerate massive neutrino, respectively.
Cosmology and Nongalactic Astrophysics High Energy Physics - Phenomenology
