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@article{Darragh-Ford:2023:1538-4357/ace902,
author = {Darragh-Ford, E and Wu, JF and Mao, YY and Wechsler, RH and Geha, M and Forero-Romero, JE and Hahn, CH and Kallivayalil, N and Moustakas, J and Nadler, EO and Nowotka, M and Peek, JEG and Tollerud, EJ and Weiner, B and Aguilar, J and Ahlen, S and Brooks, D and Cooper, AP and de, la Macorra A and Dey, A and Fanning, K and Font-Ribera, A and Gontcho, A Gontcho S and Honscheid, K and Kisner, T and Kremin, A and Landriau, M and Levi, ME and Martini, P and Meisner, AM and Miquel, R and Myers, AD and Nie, J and Palanque-Delabrouille, N and Percival, WJ and Prada, F and Schlegel, D and Schubnell, M and Tarlé, G and Vargas-Magaña, M and Zhou, Z and Zou, H},
doi = {1538-4357/ace902},
journal = {Astrophysical Journal},
title = {Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program},
url = {http://dx.doi.org/10.3847/1538-4357/ace902},
volume = {954},
year = {2023}
}

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TY  - JOUR
AB  - We introduce the DESI LOW-Z Secondary Target Survey, which combines the wide-area capabilities of the Dark Energy Spectroscopic Instrument (DESI) with an efficient, low-redshift target selection method. Our selection consists of a set of color and surface brightness cuts, combined with modern machine-learning methods, to target low-redshift dwarf galaxies (z < 0.03) between 19 < r < 21 with high completeness. We employ a convolutional neural network (CNN) to select high-priority targets. The LOW-Z survey has already obtained over 22,000 redshifts of dwarf galaxies (M  < 109 M ), comparable to the number of dwarf galaxies discovered in the Sloan Digital Sky Survey DR8 and GAMA. As a spare fiber survey, LOW-Z currently receives fiber allocation for just ∼50% of its targets. However, we estimate that our selection is highly complete: for galaxies at z < 0.03 within our magnitude limits, we achieve better than 95% completeness with ∼1% efficiency using catalog-level photometric cuts. We also demonstrate that our CNN selections z < 0.03 galaxies from the photometric cuts subsample at least 10 times more efficiently while maintaining high completeness. The full 5 yr DESI program will expand the LOW-Z sample, densely mapping the low-redshift Universe, providing an unprecedented sample of dwarf galaxies, and providing critical information about how to pursue effective and efficient low-redshift surveys.
AU  - Darragh-Ford,E
AU  - Wu,JF
AU  - Mao,YY
AU  - Wechsler,RH
AU  - Geha,M
AU  - Forero-Romero,JE
AU  - Hahn,CH
AU  - Kallivayalil,N
AU  - Moustakas,J
AU  - Nadler,EO
AU  - Nowotka,M
AU  - Peek,JEG
AU  - Tollerud,EJ
AU  - Weiner,B
AU  - Aguilar,J
AU  - Ahlen,S
AU  - Brooks,D
AU  - Cooper,AP
AU  - de,la Macorra A
AU  - Dey,A
AU  - Fanning,K
AU  - Font-Ribera,A
AU  - Gontcho,A Gontcho S
AU  - Honscheid,K
AU  - Kisner,T
AU  - Kremin,A
AU  - Landriau,M
AU  - Levi,ME
AU  - Martini,P
AU  - Meisner,AM
AU  - Miquel,R
AU  - Myers,AD
AU  - Nie,J
AU  - Palanque-Delabrouille,N
AU  - Percival,WJ
AU  - Prada,F
AU  - Schlegel,D
AU  - Schubnell,M
AU  - Tarlé,G
AU  - Vargas-Magaña,M
AU  - Zhou,Z
AU  - Zou,H
DO  - 1538-4357/ace902
PY  - 2023///
SN  - 0004-637X
TI  - Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program
T2  - Astrophysical Journal
UR  - http://dx.doi.org/10.3847/1538-4357/ace902
VL  - 954
ER  -

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