Cosmology has transitioned from data-starved to data-driven science in the last two decades due to advancements in theory, observation, and computational domains. Developments in large-scale observational surveys, along with the use of parallel programming and sophisticated simulations allow for quantitative study of the universe's formation and evolution on vast scales and long time spans.
These sophisticated observational and computational missions have led to generation of large amount of data over the decades. However, we rely on data where a host of useful information is enclosed but is encoded in a non-trivial way. The challenges in extracting this information must be overcome to make the most of the large experimental effort. Hence, it becomes pivotal that we become familiar with the developments on all these fronts in order to extract more information and science from the datasets that we (will) obtain from these large surveys and cosmological simulations. This marks the significance of summer school.
The school will cover the following topics:
Statistical analysis in cosmology
As gathering data is such an expensive and difficult process, cosmologists want to find out a priori, before actually doing costly experiments as to how much one would be able to learn from it. Hence, more and more sophisticated statistical techniques are being employed in cosmology and it has become crucial to know some statistical background to understand recent literature in the field. This school aims to teach our participants some statistical tools that any cosmologist should know about in order to be able to comprehend recently published results from the analysis of cosmological data sets.
Analysis of observational datasets
In the era of the large-scale present (like DES, eBOSS) and future (like LSST, EUCLID) surveys, the observational data will increase by orders of magnitude. Therefore it is important to learn techniques that would be crucial to analyse this data. This is one of the main aims of our summer school: to enlighten the participants on the significance of tools being used and developed to handle large-survey datasets.
Hands-on cosmological N-body simulations
Since our universe evolves on vastly unimaginable scales and absurdly long time spans, we are limited as these scales are beyond our comprehension. As a result, we need to rely on cosmological simulations to study the formation and evolution of large-scale structures. We will organise lectures that would cover setting up and running N-body simulations, and post-processing the simulation data for specific scientific purposes.
