5 papers
cloelike: A Python Library for Cosmological Likelihood Inference in the Euclid Era
Marco Bonici, Guadalupe Cañas-Herrera, Pedro Carrilho +16
cloelike is a Python package providing modular, composable Gaussian likelihood classes for the main cosmological large-scale structure observables targeted by the ESA Euclid space…
cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era
Marco Bonici, Guadalupe Cañas-Herrera, Pedro Carrilho +54
cloelib is a Python library developed to compute cosmological observables within the Cosmology Likelihood for Observables in Euclid (CLOE) ecosystem (cloe-org). As cosmology enters…
Unified reconstruction of the Lyman-alpha power spectrum with Hamiltonian Monte Carlo
N. G. Karaçaylı, P. L. Taylor
The complex geometry of the Ly forest data has motivated the use of various two-point statistics as alternatives to the three-dimensional power spectrum (), wh…
Computing Nonlinear Power Spectra Across Dynamical Dark Energy Model Space with Neural ODEs
Peter L. Taylor
I show how to compute the nonlinear power spectrum across the entire dynamical dark energy model space. Using synthetic CDM data, I train a neural ordinary differential…
CombineHarvesterFlow: Joint Probe Analysis Made Easy with Normalizing Flows
Peter L. Taylor, Andrei Cuceu, Chun-Hao To +1
We show how to efficiently sample the joint posterior of two non-covariant experiments with a large set of nuisance parameters. Specifically, we train an ensemble of normalizing fl…