Using Data from the Literature

Within $ARES/input/litdata there are several empirical formulae and datasets gathered from the literature, which typically include fits to the cosmic star-formation rate density with redshift, the galaxy or quasar luminosity function, and/or model spectral energy distributions.

The current list of papers currently included (at least to some extent) are:

• Leitherer et al. (1999) ('leitherer1999')

• Ueda et al. (2003) ('ueda2003')

• Sazonov et al. (2004) ('sazonov2004')

• Haardt & Madau (2012) ('haardt2012')

• Ueda et al. (2014) ('ueda2014')

• Robertson et al. (2015) ('robertson2015')

• Aird et al. (2015) ('aird2015')

Notice that the shorthand for these papers are just the first author’s last name and the year of publication.

For the rest of the examples on this page, we’ll assume you’ve already imported ARES, i.e. you’ve executed:

import ares

To read the data from e.g., Haardt & Madau (2012), simply do:

hm12 = ares.util.read_lit('haardt2012')

Then, access functions for e.g., the SFRD via

hm12.SFRD(6)  # in Msun / yr / cMpc**3

or the quasar luminosity function:

u03 = ares.util.read_lit('ueda2003')
u03.LuminosityFunction(1e42, z=0)

See $ARES/tests/lit for more examples.

Expanding the Database

If you’d like to add your favorite empirical formulae from the literature to ARES, here are a few conventions to follow:

File contents:

• Dictionaries containing best-fit parameter values and \(1-\sigma\) error bars.

• Functions for computing the SFRD, LuminosityFunction, Emissivity, and/or Spectrum.

Naming conventions:

• Your file should be called <last name of first author><year of publication>.py.

• As long as this file lives in $ARES/input/litdata, ARES will find it.

• Keep best-fit parameter values and errors stored in dictionaries.