Tools

Generating realistic galaxy catalogs using the GalSBI galaxy population model

A deep learning algorithm designed to analyze and reconstruct sequential cosmological data, accounting for covariances between data points, and predicting both mean values and associated uncertainties.

21cmFirstCLASS is an extension of the popular 21cmFAST code that interfaces with CLASS to generate initial conditions at recombination that are consistent with the input cosmological model. These initial conditions can be set during the time of recombination, allowing one to compute the 21cm signal (and its spatial fluctuations) throughout the dark ages, as well as in the proceeding cosmic dawn and reionization epochs.

Optimal and efficient power spectrum and bispectrum estimators for large-scale structure. This applies to both simulations and observational data, implemented using Python & Jax.

Numerical relativity simulations in cosmology and fundamental physics

CoLFI (Likelihood-free inference package for cosmology and the wider sciences) is a framework to estimate model parameters based on neural density estimators. It is an alternative to the traditional Markov chain Monte Carlo (MCMC) method. CoLFI models parameters directly without using Bayes's theorem. Therefore, in a narrow sense, it is independent of Bayesian theory.

ReFANN is a nonlinear interpolating tool based on an artificial neural network, without assuming a model or parameterization. It can reconstruct functions from data with no assumption to the data, and is a completely data-driven approach.

CAMB - Code for Anisotropies in the Microwave Background. A cosmology code for calculating theoretical CMB, lensing, galaxy count, dark-age 21cm power spectra, matter power spectra and transfer functions from parameters. There are also general utility function for cosmological calculations such as the background expansion, distances, etc

PRyMordial is a program dedicated to the computation of observables in the early universe with a focus on the cosmological era of Big Bang Nucleosynthesis (BBN). The code is the first of its kind written in python and offers fast and precise evaluation of both the BBN light-element abundances and the effective number of relativistic degrees of freedom. PRyMordial was created for both state-of-the-art analyses in the Standard Model as well as for general investigation of New Physics present in the early universe.

The code computes the abundances of light elements produced during Big Bang Nucleosynthesis. The main improvements in this new version include a revisited implementation of the nuclear rates for the most important reactions of deuterium destruction, and a re-designed GUI for running over grids of parameters with a better management of parallel runs, and a brand-new set of functions for plotting the results.

MontePython (Bayesian inference package for cosmology, modular and interfaced with CLASS)

CLASS (simulation of cosmological background evolution, thermodynamical evolution and perturbations, from inflation till today, including linear theory and some of its extensions like HMcode or 1-loop EFT, as well as the calculation of many CMB and LSS observables)

Einstein-Boltzmann solver for Horndeski's theory (the most general second-order scalar-tensor theory of gravity). The user can specify a paremeterization within the effective field theory of dark energy or a scalar-tensor Lagrangian. Hi_class computes linear cosmological observables (FRW distances, CMB, matter power and number count spectra) and can be used for parameter estimation (Montepython, Cobaya).

The popcorn void finder is used to identify void structures in cosmological simulations.