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Deep Spectroscopy with DESI for Photometric Redshift Training and Calibration
Biprateep Dey, Jeffrey A. Newman, Tianqing Zhang +62
Deep spectroscopic samples can be used to improve photometric redshift (photo-) estimates and reduce uncertainties on redshift distributions. Such improvements can increase the…
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,…
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…