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Tools WG session of GDR Cophy

→ Europe/Paris
IAP

IAP

98bis Boulevard Arago
Guilhem Lavaux (IAP), Mickael Rigault (IPNL), Simon Prunet (OCA), Yann Rasera (LUTH/Université Paris Cité/Observatoire de Paris/IUF)
Description

This working group (website here) is dedicated to raise awareness of new tools and methodology developed in the wider French community to do cosmology. The tools must be understood in a wide sense: it may be large software stack, online websites, or Mathematica© notebook.

This Working Group aims at sharing and helping the development of tools for which the needs are common to all the actors of the GDR.

It includes:

  • tools that are oriented toward the predictions of cosmological observables (including non-linearities) and their relative theoretical systematic uncertainties such as Boltzmann solvers, numerical simulations, approximate methods for the non-linear evolution, and forward modeling,
  • development of estimators for data analysis which are for example based on power spectra, and higher order statistics;
  • mathematical methods for inference such as the one based on MCMC, Machine Learning, and minimizer;
  • production of validation data, such as mock galaxy catalog, mock CMB maps;
  • tools for symbolic-based computation in the cosmological context.

This session is dedicated particularly to the use of JAX, PyTorch, and others in cosmology.

The meeting will happen in salle des séminaires / Evry Schatzman (level -1) at the IAP on November 18-20 2024.

Please note that the present timetable is preliminary and slots may be swapped depending on external cosntraints.

 

Participants
  • Ali Rida Khalife
  • Amandine Le Brun
  • Antoine Rocher
  • Arnaud de Mattia
  • Benjamin Beringue
  • Cail Daley
  • Clément Stahl
  • Deaglan Bartlett
  • Dylan Kuhn
  • Ema Tsang King Sang
  • Erwan Allys
  • Felicitas Keil
  • Guilhem Lavaux
  • Hoang Viet Tran
  • Hugo Simon-Onfroy
  • Iñigo Sáez-Casares
  • Jean Prost
  • Jean-Eric Campagne
  • Johann Cohen-Tanugi
  • Jérémy Neveu
  • Louise Mousset
  • Magdy Morshed
  • Mahmoud Osman
  • Maude Le Jeune
  • Michele Citran
  • Natalie Hogg
  • Pauline Zarrouk
  • Pierre Masson
  • Raphael Gavazzi
  • romain brunet
  • Simon Biquard
  • Simon Prunet
  • Simone Vinciguerra
  • Sébastien Gadrat
  • Sébastien Pierre
  • Sébastien Renaux-Petel
  • Valade Aurélien
  • Wassim Kabalan
  • Wuhyun Sohn
  • Yann Rasera
  • +12
  • Monday, November 18
  • Tuesday, November 19
  • Wednesday, November 20
    • New possibilities
      • 9
        JAX-Healpy: a JAX package compatible with the Healpy library

        The Healpy package is widely used in cosmology, both for the handling of the HEALPix pixelization and the associated spherical harmonic transforms. The current Healpy package implementation is not JAX friendly, as the spherical harmonics implementation is based in C++, which prevents us to possibly accelerate the associated routines using JIT or to run them on GPUs. In this talk, we will present JAX-Healpy, a package aimed at proposing Healpy routines implemented using JAX. In particular, we will review the current status of the codes, with the spherical harmonics implementation wrapping the JAX package S2FFT.

        Speaker: Magdy Morshed (INFN Ferrara)
        Slides
    • 10:10 AM
      Coffee break
    • New possibilities
      • 10
        s2scat : a software in JAX for generative models on the sphere using Scattering Transforms

        Scattering Transforms are a new type of summary statistics recently developed for the study of highly non-Gaussian processes. These statistics can be used to build generative data models, and even to develop new component separation techniques. In the context of upcoming cosmological surveys, such as LiteBIRD for the cosmic microwave background polarisation or the Vera C. Rubin Observatory and the Euclid space telescope for study of the large-scale structures of the Universe, extending these tools to spherical data is necessary. In this work, we developed s2scat, a software in JAX, for scattering transforms on the sphere and focused on the construction of maximum-entropy generative models of several astrophysical fields.

        Speaker: Louise Mousset (LPENS)
        GDR_Cophy_Nov2024.pdf
      • 11
        FURAX: a modular JAX toolbox for solving inverse problems in science

        Modern scientific data analyses involve complex models, presenting significant challenges in both data volume and computation. We present FURAX (Framework for Unified and Robust data Analysis with JAX), an open-source Python library that provides building blocks to construct instrument and noise models in a modular fashion, that benefit from the cutting-edge optimisation and GPU utilisation from JAX. FURAX is applied to cosmological data analysis with the CMB data. The examples include maximum-likelihood map-making, gap-filling of a time-ordered series and incorporation of non-ideal instrumental components.

        Speaker: Pierre Chanial (APC)
        Slides
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