23 citations · 37 across the 5 of their papers we have counts for
5 papers
GANSky -- fast curved sky weak lensing simulations using Generative Adversarial Networks
Supranta S. Boruah, Pier Fiedorowicz, Rafael Garcia +3
Extracting non-Gaussian information from the next generation weak lensing surveys will require fast and accurate full-sky simulations. This is difficult to achieve in practice with…
Bayesian mass mapping with weak lensing data using KARMMA -- validation with simulations and application to Dark Energy Survey Year 3 data
Supranta S. Boruah, Pier Fiedorowicz, Eduardo Rozo
We update the field-level inference code KARMMA to enable tomographic forward-modelling of shear maps. Our code assumes a lognormal prior on the convergence field, and properly acc…
KaRMMa 2.0 -- Kappa Reconstruction for Mass Mapping
Pier Fiedorowicz, Eduardo Rozo, Supranta S. Boruah
We present KaRMMa 2.0, an updated version of the mass map reconstruction code introduced in Fiedorowicz et al. (2022). KaRMMa is a full-sky Bayesian algorithm for reconstructing we…
Map-based cosmology inference with lognormal cosmic shear maps
Supranta Sarma Boruah, Eduardo Rozo, Pier Fiedorowicz
Most cosmic shear analyses to date have relied on summary statistics (e.g. and ). These types of analyses are necessarily sub-optimal, as the use of summary statistics i…
KaRMMa -- Kappa Reconstruction for Mass Mapping
Pier Fiedorowicz, Eduardo Rozo, Supranta S. Boruah +2
We present KaRMMa, a novel method for performing mass map reconstruction from weak-lensing surveys. We employ a fully Bayesian approach with a physically motivated lognormal prior…