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

Content

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.

Installation

You can use pip to install the package:

pip install pitszi

Reference

PITSZI: Probing ICM Turbulence from Sunyaev-Zel'dovich Imaging -- Application to the triple merging cluster MACS J0717.5+3745, Adam et al. (2025)

History

• Version 0.1.0 --> Initial upload