Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program 后印本

摘要: 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 optimally target low-redshift dwarf galaxies (z < 0.03) between 19 < r < 21. We employ a convolutional neural network (CNN) to select high priority targets. Our data validation shows that the CNN can achieve 90% completeness at z < 0.03 with 20% efficiency at selecting low-redshift galaxies, compared to compared to efficiencies of ~1% using traditional photometric methods. The LOW-Z survey has already obtained over 22,000 redshifts of dwarf galaxies ($M_*$ < $10^9$ $M_\odot$), comparable to the number of dwarf galaxies discovered in SDSS and GAMA. As a spare fiber survey, LOW-Z currently receives fiber allocation for just ~30% of its targets. However, we estimate that our photometric cuts are > 95% complete in target selection at z < 0.03 between 19

• 分类： 天文学 >> 天文学
• 引用： ChinaXiv:202303.05433 (或此版本 ChinaXiv:202303.05433V1)
  DOI:10.12074/202303.05433V1
  CSTR:32003.36.ChinaXiv.202303.05433.V1
• 科创链TXID： 2196917f-5f73-4c4d-af14-659e367d571d
• 推荐引用方式： Elise Darragh-Ford,John F. Wu,Yao-Yuan Mao,Risa H. Wechsler,Marla Geha,Jaime E. Forero-Romero,ChangHoon Hahn,Nitya Kallivayalil,John Moustakas,Ethan O. Nadler,Marta Nowotka,J. E. G. Peek,Erik J. Tollerud,Benjamin Weiner,J. Aguilar,S. Ahlen,D. Brooks,A. P. Cooper,A. de la Macorra,A. Dey,K. Fanning,A. Font-Ribera,S. Gontcho A Gontcho,K. Honscheid,T. Kisner,Anthony Kremin,M. Landriau,Michael E. Levi,P. Martini,Aaron M. Meisner,R. Miquel,Adam D. Myers,Jundan Nie,N. Palanque-Delabrouille,W. J. Percival,F. Prada,D. Schlegel,M. Schubnell,Gregory Tarlé,M. Vargas-Magaña,Zhimin Zhou,H. Zou.Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program.中国科学院科技论文预发布平台.[ChinaXiv:202303.05433V1] (点此复制)