6 papers
Simulation-Based Inference for Probabilistic Galaxy Detection and Deblending
Ismael Mendoza, Derek Hansen, Runjing Liu +6
Stage-IV dark energy wide-field surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will observe an unprecedented number density of galaxies. As…
Neural Posterior Estimation for Cataloging Astronomical Images from the Legacy Survey of Space and Time
Yicun Duan, Xinyue Li, Camille Avestruz +2
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will commence full-scale operations in 2026, yielding an unprecedented volume of astronomical images. Construct…
Neural Posterior Estimation for Cataloging Astronomical Images with Spatially Varying Backgrounds and Point Spread Functions
Aakash Patel, Tianqing Zhang, Camille Avestruz +2
Neural posterior estimation (NPE), a type of amortized variational inference, is a computationally efficient means of constructing probabilistic catalogs of light sources from astr…
Weak lensing mass-richness relation of redMaPPer clusters in the LSST DESC DC2 simulations
Constantin Payerne, Zhuowen Zhang, Michel Aguena +13
Cluster scaling relations are key ingredients in cluster abundance-based cosmological studies. In optical cluster cosmology, where clusters are detected through their richness, clu…
The Blending ToolKit: A simulation framework for evaluation of galaxy detection and deblending
Ismael Mendoza, Andrii Torchylo, Thomas Sainrat +18
We present an open source Python library for simulating overlapping (i.e., blended) images of galaxies and performing self-consistent comparisons of detection and deblending algori…
Statistical Inference for Coadded Astronomical Images
Mallory Wang, Ismael Mendoza, Cheng Wang +2
Coadded astronomical images are created by stacking multiple single-exposure images. Because coadded images are smaller in terms of data size than the single-exposure images they s…