Jul 3 – 7, 2023
Institute of Physics
Europe/Warsaw timezone

Session Details

Statistical analysis in cosmology

These lecture series will involve familiarizing the participants with statistical tools that are often employed in cosmological analysis for: 

  • Modelling of data and statistical inference
  • Goodness of fit and confidence intervals
  • Marginalisation and combining different experiments
  • Determining and quantifying possible agreements or disagreements
  • Introduction to machine learning


Analysis of observational datasets

The summer school will aim to train the participants in analysing big data sets from present and future large-scale surveys. This training will include:

  • How to download and preprocess galaxy imaging data from the HST archive.
  • How to define a likelihood function to this data, for a specific science case.
  • How to fit a model to the data, via this likelihood function, using Bayesian inference.
  • Performing Bayesian hierarchical analysis of a large imaging dataset.


Hands-on cosmological N-body simulations

N-body simulations enable us to compare cosmological models and theories with ever-more powerful data sets obtained from large telescopes and cosmic probes. In this domain, we will organize lectures that would cover:

  • The theory and principles underlying N-body simulations.
  • Setting up N-body simulations: This would include hands-on some publicly available simulation codes (like Gadget, COLA, SWIFT).
  • Running simulations and post-processing the simulation data for specific scientific purposes.
  • Reading and analysing the simulation data.