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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,…
Using Active Learning to Improve Quasar Identification for the DESI Spectra Processing Pipeline
Dylan Green, David Kirkby, J. Aguilar +51
The Dark Energy Spectroscopic Instrument (DESI) survey uses an automatic spectral classification pipeline to classify spectra. QuasarNET is a convolutional neural network used as p…