Poster Abstract

P10.9 Fabio Castagna (INAF - Osservatorio Astronomico di Brera)

Theme: Data processing pipelines

PREPROFIT - PREssure PROfile FIT for galaxy clusters in Python

Observations of the thermal Sunyaev-Zel’dovich (SZ) effect and of the X-ray
emission of galaxy clusters are becoming more and more widespread, offering
us an unique asset to the study of the properties of the intracluster medium.
We present PreProFit, a bayesian forward-modelling Python code designed to
fit the pressure profile of galaxy clusters from SZ data and further developed
to perform a joint SZ-plus-X analysis. When X-ray data are also available,
PreProFit is able to derive the thermodynamic profiles of galaxy clusters for
the first time making full and consistent use of all the information contained
in the observations. This is implemented by merging our code with a forward
modelling X-ray data cube fitter.