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Quality Assessment of Spectroscopic Data Reduction Pipelines Using Artificial Intelligence: Scrutinizing Data Release 2 from the DESI Survey
V. Torres-Gomez, J. Suarez-Perez, J. E. Forero-Romero +45
Large spectroscopic surveys now collect data at a scale that makes traditional visual inspection impractical. We present an unsupervised pipeline for spectroscopic quality assessme…
Identifying Anomalous DESI Galaxy Spectra with a Variational Autoencoder
C. Nicolaou, R. P. Nathan, O. Lahav +43
The tens of millions of spectra being captured by the Dark Energy Spectroscopic Instrument (DESI) provide tremendous discovery potential. In this work we show how Machine Learning,…
Bayesian Component Separation for DESI LAE Automated Spectroscopic Redshifts and Photometric Targeting
Ana Sofía M. Uzsoy, Andrew K. Saydjari, Arjun Dey +37
Lyman Alpha Emitters (LAEs) are valuable high-redshift cosmological probes traditionally identified using specialized narrow-band photometric surveys. In ground-based spectroscopy,…
Deep-TAO: The Deep Learning Transient Astronomical Object data set for Astronomical Transient Event Classification
John F. Suárez-Pérez, Catalina Gómez, Mauricio Neira +3
We present the Deep-learning Transient Astronomical Object (Deep-TAO), a dataset of 1,249,079 annotated images from the Catalina Real-time Transient Survey, including 3,807 transie…
Validation of the DESI DR2 Ly BAO analysis using synthetic datasets
L. Casas, H. K. Herrera-Alcantar, J. Chaves-Montero +95
The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman- (Ly…
The Future of Astronomical Data Infrastructure: Meeting Report
Michael R. Blanton, Janet D. Evans, Dara Norman +69
The astronomical community is grappling with the increasing volume and complexity of data produced by modern telescopes, due to difficulties in reducing, accessing, analyzing, and…