{"paper":{"title":"Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.GA","authors_text":"Aaron M. Meisner, Adam D. Myers, A. de la Macorra, A. Dey, A. Font-Ribera, Anthony Kremin, A. P. Cooper, Benjamin Weiner, ChangHoon Hahn, D. Brooks, D. Schlegel, Elise Darragh-Ford, Erik J. Tollerud, Ethan O. Nadler, F. Prada, Gregory Tarl\\'e, H. Zou, J. Aguilar, Jaime E. Forero-Romero, J. E. G. Peek, John F. Wu, John Moustakas, Jundan Nie, K. Fanning, K. Honscheid, Marla Geha, Marta Nowotka, Michael E. Levi, M. Landriau, M. Schubnell, M. Vargas-Maga\\~na, Nitya Kallivayalil, N. Palanque-Delabrouille, P. Martini, Risa H. Wechsler, R. Miquel, S. Ahlen, S. Gontcho A Gontcho, T. Kisner, W. J. Percival, Yao-Yuan Mao, Zhimin Zhou","submitted_at":"2022-12-14T19:00:00Z","abstract_excerpt":"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$_* < 10^9$ M$_\\odot$),"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.07433","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2212.07433/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}