40 citations · 42 across the 2 of their papers we have counts for
5 papers
Bayesian forward modelling of cosmic shear data
Natalia Porqueres, Alan Heavens, Daniel Mortlock +1
We present a Bayesian hierarchical modelling approach to infer the cosmic matter density field, and the lensing and the matter power spectra, from cosmic shear data. This method us…
A hierarchical field-level inference approach to reconstruction from sparse Lyman- forest data
Natalia Porqueres, Oliver Hahn, Jens Jasche +1
We address the problem of inferring the three-dimensional matter distribution from a sparse set of one-dimensional quasar absorption spectra of the Lyman- forest. Using a Bayesi…
Inferring high redshift large-scale structure dynamics from the Lyman-alpha forest
Natalia Porqueres, Jens Jasche, Guilhem Lavaux +1
One of the major science goals over the coming decade is to test fundamental physics with probes of the cosmic large-scale structure out to high redshift. Here we present a fully B…
Explicit Bayesian treatment of unknown foreground contaminations in galaxy surveys
Natalia Porqueres, Doogesh Kodi Ramanah, Jens Jasche +1
The treatment of unknown foreground contaminations will be one of the major challenges for galaxy clustering analyses of coming decadal surveys. These data contaminations introduce…
NIFTy 3 - Numerical Information Field Theory - A Python framework for multicomponent signal inference on HPC clusters
Theo Steininger, Jait Dixit, Philipp Frank +10
NIFTy, "Numerical Information Field Theory", is a software framework designed to ease the development and implementation of field inference algorithms. Field equations are formulat…