1 citations · 1 across the 4 of their papers we have counts for
9 papers
Smokescreen: A Python package for data vector blinding and encryption in cosmological analyses
Arthur Loureiro, Jessica Muir, Jonathan Blazek +10
Smokescreen is an open-source Python library for data-vector concealment (blinding) in cosmological analyses. Data-vector blinding works by applying cosmology-dependent shifts to t…
pop-cosmos: Forward modeling KiDS-1000 redshift distributions using realistic galaxy populations
Boris Leistedt, Hiranya V. Peiris, Anik Halder +13
The accuracy of the cosmological constraints from Stage~IV galaxy surveys will be limited by how well the galaxy redshift distributions can be inferred. We have addressed this chal…
Reconstructing the largest scales of the Universe with field-level inference applied to the Quaia Quasar Catalogue
Adam Andrews, Arthur Loureiro, Jens Jasche +3
The recently released Quaia quasar catalogue, with its broad redshift range and all-sky coverage, enables unprecedented three-dimensional reconstructions of matter across cosmic ti…
Almanac: HMC sampling with bounded velocity
Javier Silva Lafaurie, Lorne Whiteway, Elena Sellentin +4
In Hamiltonian Monte Carlo sampling, the shape of the potential and the choice of the momentum distribution jointly give rise to the Hamiltonian dynamics of the sampler. An efficie…
KiDS-Legacy: Constraints on Horndeski gravity from weak lensing combined with galaxy clustering and cosmic microwave background anisotropies
Benjamin Stölzner, Robert Reischke, Matteo Grasso +25
We present constraints on modified gravity from a cosmic shear analysis of the final data release of the Kilo-Degree Survey (KiDS-Legacy) in combination with DESI measurements of b…
Flinch: A Differentiable Framework for Field-Level Inference of Cosmological parameters from curved sky data
Andrea Crespi, Marco Bonici, Arthur Loureiro +6
We present Flinch, a fully differentiable and high-performance framework for field-level inference on angular maps, developed to improve the flexibility and scalability of current…