Jupyter notebooks, accompanying files etc.., to reproduce results in Mingarelli et al. (2017)
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codes
detectedSkies
detection_curves
galaxy_data
gw_skies
healpix_maps
scatter_maps
README.md

README.md

nanohertz_GWs: How to create your own nanohertz gravitational-wave universe.

This repo contains Jupyter notebooks, accompanying files etc.., to reproduce results in Mingarelli et al. (2017). Please cite Mingarelli et al. (2017) when using this code, as well as 10.5281/zenodo.838712, DOI .

There are 7 directories in this repository: codes, detectedSkies, detection_curves, galaxy_data, gw_skies, healpix_maps and scatter_maps.

Brief description of directories

codes:

Here you will find ipython notebooks which walk you through creating gravitational wave skies, with each step clearly indicated in the file name. Example output is given in the example_sky directory.

detectedSkies:

when a GW sky contains a detectable GW source, it is saved to a text file in this directory. An example of what this file looks like is given here, in detected_skies.txt

detection_curves:

These are the predicted IPTA curves for 15, 20 and 25 year datasets. Each file has a descriptive name. For example, cw_simulation_Ared_0_dp_0.5_fap_0.001_T_15.txt is the continuous GW wave simulation with zero red noise (Ared_0), a 50% detection probability (dp_0.5), false alarm probability of 0.001 (fap_0.001) for a 15 year dataset (T_15). The code used to make these curves was developed by Justin Ellis, and is available here, https://github.com/jellis18/time_to_detection.

galaxy_data

This contains the galaxy catalog made from 2MASS, together with a list of galaxies which had measured SMBHs. These masses are used instead of M-Mbulge.

gw_skies:

Here we provide a few hundred GW skies as an example of what the code output looks like.

healpix_maps:

Fits files for 87 GW frequencies

scatter_maps:

The same information that was in the fits files, but here in a .dat file as an alternative option.