Pourvu:
According to the standard cosmological model, about 95% of the Universe's energy content is in two unknown forms: dark energy, responsible for accelerating cosmic expansion, and dark matter, the predominant form of matter. Understanding these components is one of the key challenges in modern physics and cosmology. This has driven the development of large optical/infrared astronomical surveys, such as the ESA's Euclid satellite (launched in 2023) and the ground-based Vera Rubin Observatory, which will start the 10-year LSST survey in 2025. These surveys aim to probe the growth of large-scale structures (LSS) using different observational probes and tracers of the matter density field.
This thesis project will focus on the use of galaxy clusters, the largest bound structures in the Universe, as cosmological probes to constrain LSS growth. Their abundance as a function of mass, and its evolution with time, informs us about the history of structure formation in the Universe. Galaxy clusters are primarily composed of dark matter (~80%), gas (~15%) and galaxies (~%5). While the gas and galaxy distribution allow us to detect clusters and measure their properties, the distribution of dark matter can be assessed via gravitational lensing, i.e. the deformation of the images of background galaxies by the mass on the line of sight. This signal can be measured statistically from the shape of background galaxies. The measurements are however complex as many source of noise and bias are present.
The project focuses on accurately determining cluster masses up to a redshift of z~2, primarily through weak gravitational lensing from LSST and Euclid, in addition to information from multi-wavelength observations (optical, X- ray, millimeter). The project will contribute to deliver the largest, deepest, and most precise optical cluster sample to date, refining constraints on cosmological parameters and astrophysical processes.
During the course of the thesis, the PhD student will have access to LSST Early Science data as well as Euclid data, to simulated images and catalogs and computing facilities. X-ray and millimeter data will be available for some fields. In consultation with their advisors, the PhD student will also be encouraged to develop their own research projects and ideas, including proposals for telescope time.
As a member of the Euclid consortium and a Builder of the LSST-DESC collaboration (also Galaxy Cluster working group convener), I will make sure that the PhD student work will get a high visibility in one or both of these environments. The project will take place within the Cosmology team at APC, composed of experts of Optical and CMB Survey. The analyses will be conducted in close collaboration with the Astrodeep team, that is dedicated to machine learning applications for large scale structures cosmology. The student and postdoc will benefit from strong collaborations with the LAPP, LPSC and CPPM laboratories as part of LSST France, and with personal collaborators in the USA, UK, or Germany.
Interested applicants must first contact me for an M2 internship, to get to know each other. If the internship goes well for the student, the advisor and in relation with the rest of the team, there is an opportunity to compete for funding from the Doctoral School.
Some references
https://www.esa.int/Science_Exploration/Space_Science/Euclid