activity
20232026
most citedCombineHarvesterFlow: Joint Probe Analysis Made Easy with Normalizing Flows

7 citations · 9 across the 7 of their papers we have counts for

collaborators

7 papers

astro-ph.CO2026

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…

astro-ph.CO2026

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…

astro-ph.CO2025★ 1 cited

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 e…

astro-ph.CO2025

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 (), whi…

astro-ph.CO2024★ 7 cited

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…

astro-ph.IM2024

Unsupervised Searches for Cosmological Parity Violation: Improving Detection Power with the Neural Field Scattering Transform

Matthew Craigie, Peter L. Taylor, Yuan-Sen Ting +3

Recent studies using four-point correlations suggest a parity violation in the galaxy distribution, though the significance of these detections is sensitive to the choice of simula…

astro-ph.CO2023★ 1 cited

Unsupervised Searches for Cosmological Parity-Violation: An Investigation with Convolutional Neural Networks

Peter L. Taylor, Matthew Craigie, Yuan-Sen Ting

Recent measurements of the -point correlation functions (4PCF) from spectroscopic surveys provide evidence for parity-violations in the large-scale structure of the Universe. If…