A python package for CSST cosmological emulator.
This package is only dependent on numpy
, scipy
packages.
All the gaussian process trainings have been done in advance.
The whole package predicts the cosmological statistics [e.g., nonlinear matter power spectrum] with ~ 1 millisecond per cosmology.
The parameter space are shown as followed:
Parameter | Lower Limit | Upper Limit |
---|---|---|
0.04 | 0.06 | |
0.24 | 0.40 | |
60 | 80 | |
0.92 | 1.00 | |
1.7 | 2.5 | |
-1.3 | -0.7 | |
-0.5 | 0.5 | |
0 | 0.3 |
Up to now, the supportted statistics include:
-
PkLin
: Linear matter power spectrum ($0\leq z \leq3$ and$10^{-5}\leq k \leq 100 {\rm\ hMpc^{-1}}$ ); -
Pkmm
: Matter power spectrum ($0\leq z \leq3$ and$0.00628\leq k \leq 10 {\rm\ hMpc^{-1}}$ ); -
Xihm
: Halo-matter cross-correlation function ($0\leq z \leq0.8$ and$10^{-2}\leq r \leq 500 {\rm\ h^{-1}Mpc}$ ). Now this only supports 7 fixed mass bin:[13.0, 13.2, 13.4, 13.6, 13.8, 14.0, 14.4, 15.0]
; -
Ximm
: Matter-matter correlation function ($0\leq z \leq3$ and$r \geq 10^{-2} {\ h^{-1}\mathrm{Mpc}}$ ); -
Cell
: Lensing convergence power spectrum ($0.5\leq z_s \leq3.0$ ); - comming soon ~~ :).
The accuracy for the matter power spectrum on the whole parameter space is shown as followed:
numpy
scipy
CAMB
[optional]CLASS
[optional]CCL
[optional]
You can install this package via pip:
pip install git+https://github.com/czymh/csstemu
You can see the documentation on readthedocs for more details.
Some examples
are shown in the test
directory.
Feel free to contact chyiru@sjtu.edu.cn if you have any questions.