Latest posts on Astrodon
Mon séminaire au @collegedefrance est en ligne ! "L’énergie noire avec Euclid", https://www.youtube.com/watch?v=bLy8_iKY0rE
Merci à Françoise Combes pour son invitation.
#astrophysics #darkenergy #euclid #cosmology
COmoving Computer Acceleration (COCA): N-body simulations in an emulated frame of reference
Bartlett, Chiarenza, Doeser, Leclercq
Field-Based Physical Inference From Peculiar Velocity Tracers
Prideaux-Ghee, Leclercq, Lavaux, Heavens, Jasche
On 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
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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
- 05-12-2024
Submitted paper: Diagnosing Systematic Effects Using the Inferred Initial Power Spectrum. - 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.
Upcoming Talks
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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
07-01-2025, 14:54
Le 13 janvier prochain, je serai au Collège de France @collegedefrance pour parler de l'une des grandes questions actuelles de l'astrophysique : l'énergie noire. 🌌
Mon séminaire aura lieu lors de la dernière séance du cycle "Le secteur sombre de l’Univers : matière et énergie noires" de Françoise Combes, titulaire de la chaire Galaxies et Cosmologie. J'explorerai les différentes théories possibles et leurs implications pour l’avenir de l’Univers, en mettant l'accent sur les résultats que nous allons pouvoir obtenir grâce à Euclid @ec_euclid, la mission spatiale de l'ESA. 🛰️
📅 Quand ? Le 13 janvier 2025 à 17h45 📍 Où ? Amphithéâtre Marguerite de Navarre, Site Marcelin Berthelot, Collège de France, Paris (ou en ligne plus tard !)
20-12-2024, 14:32
3/3 How it works:
1️⃣ Infer the initial power spectrum using SELFI,
2️⃣ Use it to expose and diagnose misspecifications (galaxy bias, masks, redshift errors, etc.) before parameter inference,
3️⃣ Recycle simulations for efficient cosmological parameter estimation.
Tristan Hoellinger & Florent Leclercq, Diagnosing systematic effects using the inferred initial power spectrum, arxiv.org/abs/2412.04443.
Developed in @AquilaScience at @astroIAP.
20-12-2024, 14:31
2/3 The next generation of galaxy surveys (DESI, Euclid @ec_euclid, LSST @VRubinObs) will revolutionise #cosmology—but only if we tackle *systematic uncertainties*. Our new method builds on SELFI (arxiv.org/abs/1902.10149) & Implicit Likelihood Inference of Bayesian hierarchical models (arxiv.org/abs/2209.11057) to detect and avoid hidden model biases.
Blog
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.
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.
25-04-2019Public 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.
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
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.