Orateur
Description
Measuring the distribution of gas pressure in galaxy clusters is a key ingredient of cluster science, both from a cosmological and an astrophysical standpoint. Millimeter-wave observations offer highly valuable datasets for these measurements thanks to the thermal Sunyaev-Zeldovich (tSZ) effect, a spectral distorsion of the CMB with an amplitude directly proportional to the line of sight-integrated pressure of the intracluster medium (ICM). To perform these measurements, we have developed panco2, a Python library using MCMC forward modeling to extract ICM pressure profile estimates from millimeter-wave datasets. The software uses very flexible inputs, allowing its user to take into account various systematics affecting millimeter-wave observations, such as point source contamination, spatial filtering, and colored noise.
In this talk, I will present panco2, its usage and validation. I will describe the algorithm used to perform the pressure profile estimation, the different observational features that can be taken into account, and the data required to perform the analysis. I will describe the validation framework that has been created for panco2, using mock clusters of different masses and redshifts, with simulated observations by different millimeter-wave instruments. Finally, I will discuss the code availability, from the public Github including the code and the validation products, to the online documentation.
