SALSA: Synthetic Absorption Line Surveyor Application is a Python tool that constructs synthetic absorber catalogs from hydrodynamic galaxy simulations. Salsa heavily utilizes yt to access simulation data and Trident to create light rays/sight lines and generate synthetic spectra.

Observational studies generate large absorber catalogs by studying the absorption line spectra of distant quasars, as their light passes through intervening galaxies. Salsa can generate similar catalogs from cosmological and galactic simulations, allowing research to study these simulations from an observers perspective. This can give new insights into the data as well as help facilitate comparisons and collaboration between simulations and observations.

Salsa allows us to dip into galactic simulations and start to chip away at the many unknowns of the universe

A JOSS paper was published for SALSA and we recommend reading it for an overview of the package and its possible uses. If you do use SALSA in a project we ask that you cite this paper.

For detailed information on how to install and run salsa, Read the Docs here

If you have all the dependencies installed, you can use pip and run these commands to install the most stable version:

  $ pip install astro-salsa
  $ python
  >>> import salsa

If you want to install the latest development version and have all the dependencies installed, you can clone the repository and run these commands:

  $ git clone https://github.com/biboyd/SALSA.git
  $ cd SALSA
  $ pip install -e .
  $ python
  >>> import salsa

Now you should be all set to code!

To help with installing dependencies, enivronment.yml is included in the repository. First, install conda Then you should be able to create a conda environment via:

  $ conda env create --file environment.yml
  $ conda activate salsa-env

Note that you need gcc compiler installed (which it often already is on most machines). For a more detailed description see the installation guide which also includes tips if you want to install dependencies on your own.

For an annotated example go here. Or launch an interactive jupyter hosted on Binder here (note that the notebook may take some time to load as it generally has to build the repository).

If you want to explore on your own, the easiest way to get started is use salsa.generate_catalog(). This takes:

• The simulation dataset
• Number of light rays/sightlines to make
• Directory to save those light rays
• A list of ions
• Some other optional parameters.
  This creates a number light rays and then extracts absorbers for each ion. A pandas.DataFrame is returned with information about all the absorbers which can then be further analyzed.

All contributions are welcome! This is an open-source project, built on many other open-source projects. Contributing can take many forms including: contributing code, testing and experimenting, or offering ideas for different features.

If you are interested in contributing you can contact us directly at [email protected] or add an issue on this Github page.