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Simulating the Universe on a mobile phone
25-05-2020
In this post, we discuss a new algorithm to simulate the Universe on a variety of hardware architectures.
Continue readingOn the accuracy and precision of correlation functions and field-level inference in cosmology
Leclercq, Heavens
Perfectly parallel cosmological simulations using spatial comoving Lagrangian acceleration
Leclercq, Faure, Lavaux, Wandelt, Jaffe, Heavens, Percival, Noûs
Systematic-free inference of the cosmic matter density field from SDSS3-BOSS data
Lavaux, Jasche, Leclercq
Primordial power spectrum and cosmology from black-box galaxy surveys
Leclercq, Enzi, Jasche, Heavens
Bayesian optimisation for likelihood-free cosmological inference
Leclercq
The phase-space structure of nearby dark matter as constrained by the SDSS
Leclercq, Jasche, Lavaux, Wandelt, Percival
Bayesian analysis of the dynamic cosmic web in the SDSS galaxy survey
Leclercq, Jasche, Wandelt
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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
- 23-09-2022
New paper: Simulation-based inference of Bayesian hierarchical models while checking for model misspecification (MaxEnt'22 proceedings). - 20-09-2022
Internship opportunities for Spring 2023: see Supervision and mentoring. - 29-06-2022
An interview on the INS2I website: Florent Leclercq, à l’interface entre l’intelligence artificielle et la cosmologie (in French). - 04-04-2022
Submitted paper: Field-based physical inference from peculiar velocity tracers.
Upcoming Talks
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Hopes and challenges in data science for cosmology
15-12-2022, ASNUM2022 : Journées de l'Action Spécifique Numérique de l'INSU, Lyon, France - 2.
Forward modelling the large-scale structure: field-level and implicit likelihood inference
29-11-2022, Rubin LSST France meeting, Laboratoire de physique nucléaire et de hautes énergies, Paris, France - 1.
SELFI enhanced: robustness to model misspecification and Euclid forecast
28-11-2022, Euclid France Theory and Likelihood workshop, Institut d'Astrophysique de Paris, Paris, France
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.
08-04-2020
Algorithms 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.
25-04-2019
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.
Public data and software
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.
Public data and software
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.
Public data and software