Welcome to SingletScalar-DM’s documentation!#

Installation#

The package supports Python 3.7 and beyond. Moreover, it depends on the following packages:

To install the package along its dependencies, download a release (for stable version) or clone this repository (for development version) and run the following command in the package directory:

python -m pip install .

Running the examples#

We provide an examples gallery, where it is possible to see many applications of the routines contained in the package to plot relevant phenomenological quantities. It also enables the possibility of downloading every example either as .py scripts or .ipynb notebooks.

The examples rely on the matplotlib package in order to show the plots. You can install this dependence using the following command in the package root directory:

python -m pip install '.[examples]'

Building the documentation#

If you want to rebuild the documentation for yourself, you need to use sphinx with the configuration provided in the docs/ folder.

You can install the required dependencies using the following command in the package root directory:

python -m pip install '.[docs]'

Build using sphinx. You can run the following commands inside the docs/ directory.

If you want to update the source documentation:

make rst

If you want to build the documentation in a certain format, you can specify a <builder> among the available builders:

make <builder>

Notice that it can take a while to build the whole documentation, given it will run all the examples.

Install in development mode#

If you wish to change something in the data files or in the code, we advise you to install the package in development or editable mode, using the following command in the package root directory:

python -m pip install --editable .

In this way you are free to modify anything inside the src/ folder and the changes will be immediately reflected in the installed package once you re-import it.

Contents#

Topics:

Citation#

If you are using this tool or the results obtained with it in a published work, please cite arXiv:2305.11937.

Indices and tables#

References#

The package relies on pre-computed data obtained according to several codes:

[MadDM1.0]

M. Backovic, K. Kong, and M. McCaskey, Physics of the Dark Universe 5-6, 18 (2014), 1308.4955

[MadDM2.0]

M. Backovic, A. Martini, O. Mattelaer, K. Kong, and G. Mohlabeng, Phys. Dark Univ. 9-10, 37 (2015), 1505.04190

[MadDM3.0]

F. Ambrogi, C. Arina, M. Backovic, J. Heisig, F. Maltoni, L. Mantani, O. Mattelaer, and G. Mohlabeng, Phys. Dark Univ. 24, 100249 (2019), 1804.00044

[MadDM3.2]

C. Arina, J. Heisig, F. Maltoni, D. Massaro, and O. Mattelaer, Eur. Phys. J. C 83, 241 (2023), 2107.04598

[DRAKE1.0]

T. Binder, T. Bringmann, M. Gustafsson, and A. Hryczuk, Eur. Phys. J. C 81, 577 (2021), 2103.01944

[micrOMEGAs2.0]

G. Belanger, F. Boudjema, A. Pukhov, and A. Semenov, Comput. Phys. Commun. 176, 367 (2007), hep-ph/0607059

[micrOMEGAs3.0]

G. Belanger, F. Boudjema, A. Pukhov, and A. Semenov, Comput. Phys. Commun. 185, 960 (2014), 1305.0237

[micrOMEGAs4.0]

D. Barducci, G. Belanger, J. Bernon, F. Boudjema, J. Da Silva, S. Kraml, U. Laa, and A. Pukhov, Comput. Phys. Commun. 222, 327 (2018), 1606.03834

[micrOMEGAs5.0]

G. Belanger, F. Boudjema, A. Goudelis, A. Pukhov, and B. Zaldivar, Comput. Phys. Commun. 231, 173 (2018), 1801.03509

[micrOMEGAs5.2]

G. Belanger, A. Mjallal and A. Pukhov, Eur. Phys. J. C 81, 239 (2021), 2003.08621

[micrOMEGAs5.3]

G. Alguero, G. Belanger, S. Kraml and A. Pukhov, SciPost Phys. 13, 124 (2022), 2207.10536