There have been many simulations that show that observing an offset between x-ray centers and the Brightest Cluster Galaxy (BCG) of a galaxy cluster can give competitive constraints on the self-interaction of dark matter.

In order to determine the x-ray center of a galaxy, we must determine how much of an effect noise has on the centroid measurement. This repository holds the code that creates noise simulations on x-ray data, remeasures the centroid, and determines the best estimate of the x-ray center.

cd scripts/

python cluster_info_generator.py DES_data_mergers_removed.fits ../data/xray_data/

First argument (in this case DES_data_mergers_removed.fits) is the data from DES. The columns we use from this table are:

1. Name (in 'catalogue_x' format)
2. redMaPPer_ra and redMaPPer_dec
3. reMaPPer wrong (which tells us if we need to correct the ra and dec)
4. r500_radius
5. Redshift
6. x_ray_peak_ra and x_ray_peak_dec

Second argument (in this case ../data/x-ray_data/) is the directory that contains all of the x-ray data from Chandra.

This will output a file called prepared_data.fits. Do not move or alter this table.

python get_centroids.py 100 first_simulation 

First argument (100) is the number of simulations you want to run per cluster.

Second argument (first_simulation) is the name of your simulation. This will create a directory in ~/simulations/ that stores the results of this step.

OPTIONAL third argument is how close you want the x-ray peak to be to the center of the R500 cutout. The default is 2 pixels.

This step will take a while, but there should be annotations on what simulation and cluster is being worked on.

python final_results.py first_simulation

This will create an image in the ~/results/results_images/ directory called result_first_simulation.png.

python histogram_fit.py first_simulation

This will create another image in the ~/results/results_images/ directory called histogram_fit_first_simulation.png.

python sim_illustrations.py 199 first_simulation