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.
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
- 1
- 2
- 3
- 4
- 5
- 6
- 7
Welcome!
My name is Florent Leclercq. I am a Ernest Rutherford Fellow (ERF, funded by UKRI STFC) at the Imperial Centre for Inference and Cosmology, Imperial College London. I work in the fields of theoretical and observational cosmology, 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 data analysis 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
- 09-03-2021
Submitted paper: On the accuracy and precision of correlation functions and field-level inference in cosmology (with Alan Heavens). Companion GitHub repository here. - 25-05-2020
New blog post: Simulating the Universe on a mobile phone. - 08-04-2020
New blog post: Evolution of cosmological simulations over the last 50 years. - 23-07-2019
New page: pySELFI. - 25-04-2019
I have written a post on the Aquila Consortium's website regarding my last two papers on BOLFI and SELFI. It is available here: Algorithms for likelihood-free cosmological data analysis.
Upcoming Talks
- 1.
Forward modelling the large-scale structure: perfectly parallel simulations and simulation-based inference
20-01-2022, London Cosmology Discussion Meeting (remote presentation), Royal Astronomical Society, London, UK
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