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Welcome!
My name is Florent Leclercq. I am a research scientist (Chargé de recherche CNRS) at the Institut d'Astrophysique de Paris (IAP). I hold an interdisciplinary position at the interface between astrophysics (Institut national des sciences de l'Univers, INSU) and information science (Institut des sciences de l'information et de leurs interactions, INS2I). I work in the fields of numerical cosmology and artificial intelligence, focusing in particular on the analysis of galaxy survey data. I have been a member of the Aquila Consortium since it was created, in 2016. I am also a member of the Euclid Consortium, where I currently co-lead the "Additional Probes" work package of the Galaxy Clustering Science Working Group.
My current research interests are related to the study of the cosmological large-scale structure using statistical inference, machine learning, and high-performance computing tools. I am particularly interested constraining cosmology from the large-scale structure, in the initial conditions from which it originates, its formation history and the description of the cosmic web.
Please check the full version of my CV, my list of publications and my list of communications.
News
- 13-09-2024
Updated page: Media and Outreach (recent conferences in French). - 03-09-2024
Submitted paper: COmoving Computer Acceleration (COCA): N-body simulations in an emulated frame of reference. - 11-10-2023
New master internship and PhD studentship opportunity: High-performance information extraction from cosmic web probes in the INFOCW project. See Supervision and mentoring. - 03-02-2023
Pages updated: pySELFI (v2.0) and Lotka-Volterra simulator.
Upcoming Talks
- 3.
L’énergie noire avec Euclid
13-01-2025, Seminar at the Collège de France, Paris, France - 2.
Énergie noire et intelligence artificielle
09-12-2024, Conference at the Club Astronomie de l'Université du Mans, Le Mans, France - 1.
L’intelligence artificielle en astronomie
07-11-2024, Conference at the Institut Français d'Algérie, Constantine, Algeria
Evolution of cosmological simulations over the last 50 years
I recently scanned the literature for the purpose of following and plotting the number of particles used in \(N\)-body simulations over the last five decades.
08-04-2020Algorithms for likelihood-free cosmological data analysis
Likelihood-free inference provides a framework for performing Bayesian inference in cosmology, by replacing likelihood calculations with data model evaluations.
25-04-2019Public data and software
pySELFI
pySELFI is a publicly-available implementation of the Simulator Expansion for Likelihood-Free Inference algorithm, allowing primordial power spectrum inference from black-box galaxy surveys.