PITSZI: Probing ICM Turbulence from Sunyaev-Zel'dovich Imaging

Software dedicated to model intracluster medium pressure fluctuations, generate Monte Carlo Sunyaev-Zel'dovich data, and fit the model to input data.

Overview of the physical processes and structure of the code

The pitszi directory contains the main code, including:

model_main.py : main code entry to use the class Model
model_library.py : subclass that defines model libraries and tools
model_sampling.py : subclass that deals with the sampling of the model
model_mock.py : subclass used to generate mock images
data_main.py : class Data used to define input data and usefull associated functions
inference_radial_main.py : class InferenceRadial used to constrain the pressure radial model (from Model class) given input data (from Data class)
inference_radial_fitting.py : subclass of inference_radial_main, used for fitting
inference_fluctuation_main.py : class InferenceFluctuation used to constrain the pressure fluctuation model (from Model class) given input data (from Data class)
inference_fluctuation_fitting.py : subclass of inference_fluctuation_main, used for fitting
physics_main.py : libraries to be used for infering nonthermal ICM information from pressure fluctuations
utils.py, utils_pk.py, utils_fitting.py, utils_plot.py : library of useful functions
title.py : title for the package
notebook : Repository where to find Jupyter notebook used for validation/example/developments.

You can use pip to install the package:

pip install pitszi

PITSZI: Probing ICM Turbulence from Sunyaev-Zel'dovich Imaging -- Application to the triple merging cluster MACS J0717.5+3745, Adam et al. (in prep)