The objectives of this hands-on workshop is to familiarise students with some basic and more advanced statistical tools available to the astrophysical community to perform multi-scale and related analysis on ISM gas distributions (PDFs, power spectra, dendrograms, segmentation of cloud density images, etc.)
The first part of the workshop, designed on python Jupyter’s notebook, will explore mainly two packages: TurbuStat and Pywavan TurbuStat includes several techniques described in the literature which aim to describe some property of data cubes and 2D astrophysical maps. It includes an impressive collection of statistical analysis techniques, such as the PDF, the power spectrum, the ∆-variance, the dendrogram, etc. Pywavan has been developed by J.-F. Robitaille and it revolves mainly around one function which is dedicated to the wavelet power spectrum analysis of cloud column density images and its Multi-scale non-Gaussian Segmentation (MnGSeg). It also contains functions to perform the classical Fourier power spectrum analysis, generate fractal simulations and do basic data manipulation, such as cutting fits maps, beam convolution, etc.
The second part of the workshop will explore 3D simulations dataset. It will consist in analysing 3D simulations datasets obtained using the RAMSES code, from which the 2D column density maps were derived. The visualisation code Osyris will be used to load the 3D RAMSES datasets, to plot various quantities (density slices, histograms), to export arrays in order to do PDF of 3D fields for instance or to produce column density maps. If time permits, the RAMSES code will be run at low resolution in order to produce directly the 3D simulation datasets, exploring the initial parameter space.
Supervisors: Frédérique MOTTE, Jean-François ROBITAILLE & Benoît COMMERÇON Objectives: PDF, Power spectrum and segmentation MnGSeg of cloud column density images (observed et simulated), PDF and power spectrum of 3D simulation dataset
Up to 5 students
In the morning (CEST), UTC +2