SPT Likelihoods

External likelihoods for SPT experiment using cobaya. These are python implementation of original Fortran code for CosmoMC sampler.

The package includes the following likelihoods:

• sptpol_2017 relates to SPTPol EETE likelihood used in Henning et al., 2017. The original Fortran code is available here or in LAMBDA.
• spt_hiell_2020 relates to SPT-SZ TT likelihood used in Reichardt et al., 2020. The original Fortran code is available in LAMBDA.
• spt3g_2020 relates to SPT3G EETE likelihood used in Dutcher et al., 2021. The original Fortran code is available here.

Installing the code

You can install the following code by just typing

$ pip install git+https://github.com/xgarrido/spt_likelihoods.git

If you plan to develop/modify the code, the easiest way is to clone this repository to some location

$ git clone https://github.com/xgarrido/spt_likelihoods.git /where/to/clone

Then you can install the likelihoods and its dependencies via

$ pip install -e /where/to/clone

The -e option allow the developer to make changes within the spt directory without having to reinstall at every changes. If you plan to just use the likelihood and do not develop it, you can remove the -e option.

Installing SPT likelihood data

SPT data are stored in LAMBDA. You can download them by yourself but you can also use the cobaya-install binary and let it do the installation job. For instance, if you do the next command

$ cobaya-install /where/to/clone/examples/spt3g_example.yaml -p /where/to/put/packages

data for SPT3G and code such as CAMB will be downloaded and installed within the /where/to/put/packages directory. For more details, you can have a look to cobaya documentation.

Running/testing the code

You can test the SPT likelihoods by doing

$ test-spt

It will perform basic Χ² checks over the three different likelihoods.

You can also run MCMC chains with

$ cobaya-run /where/to/clone/examples/spt3g_example.yaml -p /where/to/put/packages