COmoving Computer Acceleration (COCA): N-body simulations in an emulated frame of reference

Bartlett, Chiarenza, Doeser, Leclercq

COmoving Computer Acceleration (COCA): N-body simulations in an emulated frame of reference

Field-Based Physical Inference From Peculiar Velocity Tracers

Prideaux-Ghee, Leclercq, Lavaux, Heavens, Jasche

Field-Based Physical Inference From Peculiar Velocity Tracers

On the accuracy and precision of correlation functions and field-level inference in cosmology

Leclercq, Heavens

On the accuracy and precision of correlation functions and field-level inference in cosmology

Perfectly parallel cosmological simulations using spatial comoving Lagrangian acceleration

Leclercq, Faure, Lavaux, Wandelt, Jaffe, Heavens, Percival, Noûs

Perfectly parallel cosmological simulations using spatial comoving Lagrangian acceleration

Systematic-free inference of the cosmic matter density field from SDSS3-BOSS data

Lavaux, Jasche, Leclercq

Systematic-free inference of the cosmic matter density field from SDSS3-BOSS data

Primordial power spectrum and cosmology from black-box galaxy surveys

Leclercq, Enzi, Jasche, Heavens

Primordial power spectrum and cosmology from black-box galaxy surveys

Bayesian optimisation for likelihood-free cosmological inference

Leclercq

Bayesian optimisation for likelihood-free cosmological inference
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Welcome!

Florent Leclercq 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.

Research interestsPublicationsMedia and outreach


Blog

Simulating the Universe on a mobile phone

25-05-2020 Comparison of traditional and sCOLA simulations

In this post, we discuss a new algorithm to simulate the Universe on a variety of hardware architectures.

More posts

Public data and software

pySELFI

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.

Simbelmynë

Simbelmynë

Simbelmynë is a publicly-available simulator to generate synthetic galaxy survey data. A more detailed description of the code can be found on its homepage, hosted on this website.

The BORG SDSS data release

The BORG SDSS data release

This website hosts the BORG SDSS data release, a set of data products that follow a chrono-cosmographic analysis of the three-dimensional large-scale structure of the nearby Universe.