Milky Way Satellite Census. I. The Observational Selection Function for Milky Way Satellites in DES Y3 and Pan-STARRS DR1
Milky Way Satellite Census. I. The Observational Selection Function for Milky Way Satellites in DES Y3 and Pan-STARRS DR1
复制标题
DOI：
10.3847/1538-4357/ab7eb9
复制
发表时间：
2019-12
期刊：
影响因子：
--
通讯作者：
A. Drlica-Wagner;K. Bechtol;S. Mau;M. McNanna;E. Nadler;A. Pace;T. Li;A. Pieres;E. Rozo;J. Simon;A. Walker;Risa Wechsler;T. Abbott;S. Allam;J. Annis;E. Bertin;D. Brooks;D. Burke;A. Rosell;M. Kind;J. Carretero;M. Costanzi;L. Costa;J. Vicente;S. Desai;H. Diehl;P. Doel;T. Eifler;S. Everett;B. Flaugher;J. Frieman;J. García-Bellido;E. Gaztañaga;D. Gruen;R. Gruendl;J. Gschwend;G. Gutiérrez;K. Honscheid;D. James;E. Krause;K. Kuehn;N. Kuropatkin;O. Lahav;M. Maia;J. Marshall;Peter Melchior;F. Menanteau;R. Miquel;A. Palmese;A. Plazas;E. Sánchez;V. Scarpine;M. Schubnell;S. Serrano;I. Sevilla-Noarbe;M. Smith;E. Suchyta;G. Tarlé
中科院分区：
文献类型：
--
作者：
A. Drlica-Wagner;K. Bechtol;S. Mau;M. McNanna;E. Nadler;A. Pace;T. Li;A. Pieres;E. Rozo;J. Simon;A. Walker;Risa Wechsler;T. Abbott;S. Allam;J. Annis;E. Bertin;D. Brooks;D. Burke;A. Rosell;M. Kind;J. Carretero;M. Costanzi;L. Costa;J. Vicente;S. Desai;H. Diehl;P. Doel;T. Eifler;S. Everett;B. Flaugher;J. Frieman;J. García-Bellido;E. Gaztañaga;D. Gruen;R. Gruendl;J. Gschwend;G. Gutiérrez;K. Honscheid;D. James;E. Krause;K. Kuehn;N. Kuropatkin;O. Lahav;M. Maia;J. Marshall;Peter Melchior;F. Menanteau;R. Miquel;A. Palmese;A. Plazas;E. Sánchez;V. Scarpine;M. Schubnell;S. Serrano;I. Sevilla-Noarbe;M. Smith;E. Suchyta;G. Tarlé
我们报告了使用暗能量巡天（DES）和Pan-STARRS 1（PS1）的数据系统搜索超暗银河系卫星星系的结果。DES和PS1共同提供了超过80%天空的光学/近红外波长的多波段测光。我们对卫星星系的搜索目标是高银河纬度天空的1025，000 deg 2，在g和r波段达到10σ点源深度为1022.5等。虽然之前已经在DES和PS1上独立进行了卫星星系搜索，但这是第一次在两个数据集上进行自洽搜索。我们没有发现任何新的高重要性卫星星系候选者，恢复了以前在可比深度的调查中发现的大多数卫星。我们使用大量的模拟卫星注入到调查数据的敏感性，我们的搜索特征。我们使用这些模拟来推导分析和机器学习模型，这些模型可以准确地预测银河系卫星的可探测性，作为它们在天空中的距离，大小，亮度和位置的函数。为了证明这个观测选择函数的效用，我们计算了银河系卫星星系的光度函数，假设已知的卫星星系的人口是代表的基本分布。我们提供访问我们的观测选择功能，以方便与星系形成和演化的宇宙学模型进行比较。
We report the results of a systematic search for ultra-faint Milky Way satellite galaxies using data from the Dark Energy Survey (DES) and Pan-STARRS1 (PS1). Together, DES and PS1 provide multi-band photometry in optical/near-infrared wavelengths over ∼80% of the sky. Our search for satellite galaxies targets ∼25,000 deg2 of the high-Galactic-latitude sky reaching a 10σ point-source depth of ≳22.5 mag in the g and r bands. While satellite galaxy searches have been performed independently on DES and PS1 before, this is the first time that a self-consistent search is performed across both data sets. We do not detect any new high-significance satellite galaxy candidates, recovering the majority of satellites previously detected in surveys of comparable depth. We characterize the sensitivity of our search using a large set of simulated satellites injected into the survey data. We use these simulations to derive both analytic and machine-learning models that accurately predict the detectability of Milky Way satellites as a function of their distance, size, luminosity, and location on the sky. To demonstrate the utility of this observational selection function, we calculate the luminosity function of Milky Way satellite galaxies, assuming that the known population of satellite galaxies is representative of the underlying distribution. We provide access to our observational selection function to facilitate comparisons with cosmological models of galaxy formation and evolution.