# Colossus Documentation¶

Colossus is a python toolkit for calculations pertaining to cosmology, the large-scale structure of the universe, and the properties of dark matter halos. The name is an acronym for **CO**smology, ha**LO** and large-**S**cale **S**tr**U**cture tool**S**. Correspondingly, Colossus consists of three top-level modules:

- Cosmology: Implements LCDM cosmologies with curvature, relativistic species, and different dark energy equations of state. Includes standard calculations such as densities and times, but also more advanced computations such as the power spectrum, variance, and correlation function.
- Large-scale structure: Deals with peaks in Gaussian random fields and the statistical properties of halos such as peak height, peak curvature, halo bias, and the mass function.
- Dark matter halos: Deals with halo masses and radii in arbitrary spherical overdensity definitions, pseudo-evolution, implements general and specific halo density profiles (Einasto, Hernquist, NFW, DK14), computes models for halo concentration and the splashback radius.

Colossus is developed with the following chief design goals in mind:

*Intuitive use:*The fundamental philosophy of Colossus is to make it easy to evaluate complex astrophysical quantities in a single or in a few lines of code. For this purpose, numerous fitting functions have been pre-programmed.*Stand-alone, pure python:*No dependencies beyond numpy and scipy, no C modules to be compiled. You can install Colossus either as a python package using pip or clone the repository.*Performance:*Computationally intensive routines have been optimized for speed, often using interpolation tables. Virtually all functions accept either numbers or numpy arrays as input.

The easiest way to learn how to use Colossus is to follow the examples in the Tutorials. The Search Page is useful when looking for specific functions. While Colossus has been tested extensively, there is no guarantee that it is free of bugs. Use it at your own risk, and please report any errors, inconveniences and unclear documentation to the author.

## Citing Colossus¶

If you use Colossus for a publication, please cite the code paper (Diemer 2017). Many Colossus routines implement the results of other papers. If you use such routines, please take care to cite the relevant papers as well (they will be mentioned in the function and/or module documentation).