High-performance information extraction from cosmic web probes

13 Octobre 2023

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Catégorie : Stagiaire

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Physical cosmology has brilliantly interwoven high-energy physics and observational astronomy to sketch the history of the Universe’s evolution from the Big Bang to its present state. Yet, lingering mysteries still beckon, primarily concerning dark energy, the cause of the Universe's accelerated expansion, and the elusive masses of neutrino particles. Recent advances in statistical cosmology show the potential of going beyond traditional methodologies centred around correlation functions to unveil these secrets. The INFOCW project, funded by the Agence Nationale de la Recherche (ANR), seeks to employ models that predict the complete map of the large-scale structure as seen by ESA’s Euclid satellite, a recently launched space observatory. Through the synergy of cosmological simulations, data science, and astrophysical observations, the project promises to bring forth innovations that harness information trapped in the cosmic web—the Universe's grandest observable structure.

Identifying and extracting the maximum amount of cosmological information from cosmic maps is still a largely open problem and will play a pivotal role in INFOCW. The goal of this master internship and PhD project is to tackle this task. In the first phase of the project, we will utilise physically and statistically motivated cosmic web probes. We will then optimise the extraction of cosmological information using automatically defined statistical summaries of galaxy catalogues, i.e. machine-aided definition of probes.

The student will gain insights into cosmological modelling, work with large astronomical data sets, and recent advances in machine learning. They will play a role in scaling up data models, optimising information extraction from the cosmic web, and enriching the scientific yield from Euclid data analysis. They will work within the Aquila Consortium and take part in some projects of the Euclid Consortium.

We are looking for candidates with:

• A strong background in cosmology and/or astrophysics,
• Good computational abilities, preferably some familiarity with at least Python,
• A willingness to learn, and to work collaboratively.