activity
20082026
most citedLSST: from Science Drivers to Reference Design and Anticipated Data Products

3.5k citations · 3.9k across the 15 of their papers we have counts for

collaborators

16 papers

astro-ph.IM2026

The LSST Science Pipelines Software: Optical Survey Pipeline Reduction and Analysis Environment

Rubin Observatory Science Pipelines Developers, Yusra AlSayyad, Robert Armstrong +83

The NSF-DOE Vera C. Rubin Observatory is executing the Legacy Survey of Space and Time (LSST) as its prime mission, producing a series of data releases over the ten-year survey. Th…

astro-ph.IM2026★ 14 cited

The Vera C. Rubin Observatory Data Preview 1

Vera C Rubin Observatory Team, Tatiana Acero Cuellar, Emily Acosta +325

We present Rubin Data Preview 1 DP1, the first data from the NSF DOE Vera C Rubin Observatory, comprising raw and calibrated single epoch images, coadds, difference images, detecti…

astro-ph.SR2025

47 Tuc in Rubin Data Preview 1: Exploring Early LSST Data and Science Potential

Yumi Choi, Knut A. G. Olsen, Jeffrey L. Carlin +12

We present analyses of the early data from Rubin Observatory's Data Preview 1 (DP1) for the globular cluster 47 Tuc field. The DP1 dataset for 47 Tuc includes four nights of observ…

astro-ph.IM2021★ 5 cited

Joint survey processing: combined resampling and convolution for galaxy modelling and deblending

Rémy Joseph, Peter Melchior, Fred Moolekamp

We present an extension of the multi-band galaxy fitting method scarlet which allows the joint modeling of astronomical images from different instruments, by performing simultaneou…

astro-ph.IM2019★ 7 cited

Hybrid Physical-Deep Learning Model for Astronomical Inverse Problems

Francois Lanusse, Peter Melchior, Fred Moolekamp

We present a Bayesian machine learning architecture that combines a physically motivated parametrization and an analytic error model for the likelihood with a deep generative model…

math.OC2019★ 7 cited

Proximal Adam: Robust Adaptive Update Scheme for Constrained Optimization

Peter Melchior, Rémy Joseph, Fred Moolekamp

We implement the adaptive step size scheme from the optimization methods AdaGrad and Adam in a novel variant of the Proximal Gradient Method (PGM). Our algorithm, dubbed AdaProx, a…