papers

Publications (5)

astro-ph.IM2026

Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification

Raphaël Bonnet-Guerrini, Bruno Sanchez, Dominique Fouchez +5

Time-domain surveys generate many transient candidates, making Real-Bogus classification a critical step in automated discovery pipelines. Reliable labels are costly, while communi…

astro-ph.CO2022

Designing an Optimal LSST Deep Drilling Program for Cosmology with Type Ia Supernovae

Philippe Gris, Nicolas Regnault, Humna Awan +8

The Vera C. Rubin Observatory's Legacy Survey of Space and Time is forecast to collect a large sample of Type Ia supernovae (SNe Ia) that could be instrumental in unveiling the nat…

astro-ph.CO2026

SLSim: a strong lensing population simulation package

Narayan Khadka, Simon Birrer, Henry Best +45

Gravitational lensing offers unique insights into cosmology by bending light around massive objects. Strong gravitational lensing, in particular, produces magnified and often multi…

astro-ph.EP2021

Easy asteroid phase curve fitting for the Python ecosystem: Pyedra

Milagros Colazo, Juan Cabral, Martin Chalela +1

A trending astronomical phenomenon to study is the variation in brightness of asteroids, caused by its rotation on its own axis, non-spherical shapes, changes of albedo along its s…

astro-ph.IM2020

Astroalign: A Python module for astronomical image registration

Martin Beroiz, Juan B. Cabral, Bruno Sanchez

We present an algorithm implemented in the astroalign Python module for image registration in astronomy. Our module does not rely on WCS information and instead matches 3-point ast…