pitszi 0.2.0

Python code to model ICM pressure fluctuations, generate Monte Carlo Sunyaev-Zeldovich data, and fit the model to input data

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

Figure 1. Overview of the code structure.

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. (in prep)

History

• Version 0.1.0 --> Initial upload