3 citations · 8 across the 4 of their papers we have counts for
5 papers
Multi-Method Machine Learning Classification of Astronomical Sources with Rubin Data Previews: a Spectroscopy-Free Approach with DP1 and DP2
Andrés Alejandro Plazas Malagón, Yasna Ordenes-Briceño, Dan S. Taranu +8
We present a multi-method machine-learning study for the binary photometric classification of point-like and extended sources in the Rubin Observatory Data Preview 1 (DP1) and Data…
Mitigation of the Brighter-Fatter Effect in the LSST Camera
Alex Broughton, Yousuke Utsumi, Andrés Plazas Malagón +8
Thick, fully depleted charge-coupled devices (CCDs) are known to exhibit non-linear behavior at high signal levels due to the dynamic behavior of charges collecting in the potentia…
Photometry, Centroid and Point-Spread Function Measurements in the LSST Camera Focal Plane Using Artificial Stars
Johnny H. Esteves, Yousuke Utsumi, Adam Snyder +12
The Vera C. Rubin Observatory's LSST Camera (LSSTCam) pixel response has been characterized using laboratory measurements with a grid of artificial stars. We quantify the contribut…
Deep Learning Models of the Discrete Component of the Galactic Interstellar Gamma-Ray Emission
Alexander Shmakov, Mohammadamin Tavakoli, Pierre Baldi +3
A significant point-like component from the small scale (or discrete) structure in the H2 interstellar gas might be present in the Fermi-LAT data, but modeling this emission relies…
Improved Modeling of the Discrete Component of the Galactic Interstellar Gamma-ray Emission and Implications for the Fermi-LAT Galactic Center Excess
Christopher M. Karwin, Alex Broughton, Simona Murgia +3
The aim of this work is to improve models for the gamma-ray discrete or small-scale structure related to H2 interstellar gas. Reliably identifying this contribution is important to…