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The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys
Monthly Notices of the Royal Astronomical Society ( IF 4.8 ) Pub Date : 2020-07-13 , DOI: 10.1093/mnras/staa1957
J Sánchez 1, 2 , C W Walter 3 , H Awan 4 , J Chiang 5 , S F Daniel 6 , E Gawiser 4 , T Glanzman 5 , D Kirkby 1 , R Mandelbaum 7 , A Slosar 8 , W M Wood-Vasey 9 , Y AlSayyad 10 , C J Burke 11, 12 , S W Digel 5 , M Jarvis 13 , T Johnson 5 , H Kelly 5 , S Krughoff 14 , R H Lupton 10 , P J Marshall 5 , J R Peterson 11 , P A Price 10 , G Sembroski 11 , B Van Klaveren 5 , M P Wiesner 15 , B Xin 16 ,
Affiliation  

Author(s): Sanchez, J; Walter, CW; Awan, H; Chiang, J; Daniel, SF; Gawiser, E; Glanzman, T; Kirkby, D; Mandelbaum, R; Slosar, A; Wood-Vasey, WM; AlSayyad, Y; Burke, CJ; Digel, SW; Jarvis, M; Johnson, T; Kelly, H; Krughoff, S; Lupton, RH; Marshall, PJ; Peterson, JR; Price, PA; Sembroski, G; Van Klaveren, B; Wiesner, MP; Xin, B; Collaboration, LSST Dark Energy Sci | Abstract: ABSTRACT Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r-band observations of 40 deg2 to 10 yr LSST depth. We present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star–galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2σ–6σ) in the estimated power spectra at small scales (l g 1200), highlighting the impact of blending in studies at small angular scales in LSST.

中文翻译:

LSST DESC 数据挑战 1:生成和分析用于下一代调查的合成图像

作者(S):桑切斯,J;沃尔特,CW;阿万,H;蒋,J;丹尼尔,SF;加维瑟,E;格兰兹曼,T;柯克比,D;曼德鲍姆,R;斯洛萨,A;伍德瓦西,WM;阿尔赛亚德,Y;伯克,CJ;迪格尔,西南;贾维斯,M;约翰逊,T; 凯利,H;克鲁霍夫,S;拉普顿,RH;马歇尔,PJ;彼得森,JR;价格,PA;森布罗斯基,G;范克拉维伦,B;威斯纳,议员;辛,乙;合作,LSST 暗能量科学 | 摘要:摘要数据挑战 1 (DC1) 是鲁宾天文台时空遗产调查 (LSST) 暗能量科学合作 (DESC) 产生的第一个合成数据集。DC1 旨在开发和验证数据简化和分析,并研究将影响 LSST 数据集的系统效应的影响。DC1 由 40 deg2 到 10 yr LSST 深度的 r 波段观测组成。我们介绍了模拟和分析过程的每个阶段:(a)生成,通过在具有不同观测条件的单个传感器访问图像中合成来自宇宙学 N 体模拟的源;(b) 使用 LSST 科学管道的开发版本进行缩减;(c) 匹配输入的宇宙学目录以进行验证和测试。我们验证可测试的 LSST 要求在 DC1 的保真度内通过。我们建立了一个选择程序,为聚类分析生成足够干净的河外样本,并讨论残留样本污染,包括星-星系分离效率低下和不完全去混合的贡献。我们在模拟场上计算星系功率谱并得出结论:(i) 调查属性对 DC1 中使用的尺度和模型的统计不确定性有 50% 的影响;(ii) 有必要选择消除目录中的人工制品,以避免测量聚类中的偏差;(iii) 明亮物体的存在对小尺度 (lg 1200) 的估计功率谱有显着影响 (2σ–6σ),突出了 LSST 中小角尺度研究中混合的影响。
更新日期:2020-07-13
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