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From Data to Software to Science with the Rubin Observatory LSST
Katelyn Breivik, Andrew J. Connolly, K. E. Saavik Ford +97
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the…
The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) Survey Design, Reductions, and Detections
Karl Gebhardt, Erin Mentuch Cooper, Robin Ciardullo +60
We describe the survey design, calibration, commissioning, and emission-line detection algorithms for the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX…
Debunking Generalization Error or: How I Learned to Stop Worrying and Love My Training Set
Viviana Acquaviva, Chistopher Lovell, Emille Ishida
We aim to determine some physical properties of distant galaxies (for example, stellar mass, star formation history, or chemical enrichment history) from their observed spectra, us…
Pushing the Technical Frontier: From Overwhelmingly Large Data Sets to Machine Learning
Viviana Acquaviva
This paper summarizes my thoughts, given in an invited review at the IAU symposium 341 "Challenges in Panchromatic Galaxy Modelling with Next Generation Facilities", about how mach…
How to measure metallicity from five-band photometry with supervised machine learning algorithms
Viviana Acquaviva
We demonstrate that it is possible to measure metallicity from the SDSS five-band photometry to better than 0.1 dex using supervised machine learning algorithms. Using spectroscopi…
Bayesian Redshift Classification of Emission-line Galaxies with Photometric Equivalent Widths
Andrew S. Leung, Viviana Acquaviva, Eric Gawiser +13
We present a Bayesian approach to the redshift classification of emission-line galaxies when only a single emission line is detected spectroscopically. We consider the case of surv…