A Python module to compute the power spectrum and 2-point correlation function in real space using second-order CTM.
Please see the Documentation for more details and cite Lane et al. 2021.
Any queries please email: [email protected]
mcfit which can be installed using
pip install mcfit
classylss which can be installed using
conda install -c bccp classylss
or
pip install classylss
The CTM module can be installed using
pip install ctmmodule
if this method is used then mcfit and classylss will be automatically installed if they have not previously been installed. If classylss fails to install automatically please follow the conda installation instructions above and then attempt to pip install the ctmmodule again.
To check the code has been installed properly run in the terminal
python
from ctm import CTM
The following parameters can be specified by the user using
CTM(omega0_cdm=0.25, omega0_b=0.05, h=0.7, n_s=0.96, sigma_8=0.8)
| Parameter | Automatic Value |
|---|---|
| 0.11933 | |
| 0.02233 | |
| 0.6737 | |
| 0.9665 | |
| 0.8102 |
The following CTM parameters can be specified by the user using
CTM().ctm_power(epsilon=0.01, z_init=150.0, k_c=5.0)
| Parameter | Automatic Value | Description |
|---|---|---|
| 3000 | Number of k values used in calculation of the power spectrum | |
| 1.0 | The value of the expansion parameter | |
| 100.0 | The value of the initial redshift from which the time dependence is integrated from | |
| 0.0 | The value of the cutoff k value for using an initial Gaussian damped power spectrum | |
| 32 | The number of spherical Bessel functions used in the calculation |
The range of values for the CTM parameters are:
An example notebook can be found in the folder Examples
Real-space examples: CTM_real_space_examples.ipynb