Collaborative Research: Cosmic Shear on Extremely Large Scales with the Dark Energy Camera

合作研究：利用暗能量相机进行极大尺度的宇宙剪切

• 批准号: 2108168
• 负责人: Chihway Chang
• 金额: $ 36.67万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2108168&HistoricalAwards=false
• 关键词: Collaborative; Research; Cosmic; Shear; Extremely

Dark matter and dark energy make up 95% of the Universe, yet the physics governing these components is not well understood. Weak lensing, the bending of light as it passes by mass in the Universe, is one of the most powerful tools for studying dark matter and dark energy. Weak lensing measurements from the recent Universe have been found to be discrepant with cosmic microwave background measurements from the early Universe, which may indicate that our understanding of cosmology is incomplete. The investigators will assemble an independent weak lensing data set using public observations covering a new area of sky comparable to the largest state-of-the-art weak lensing surveys. These data will be used to perform an independent analysis and directly address the tension between measurements of the Universe at early and recent times. This program will be part of the education for a diverse group of students. It will also include outreach efforts that share cosmology with the public by combining art and science in collaboration with Adler Planetarium and the Space Explorers program. The investigators will use public data from the Dark Energy Camera (DECam) at the NSF’s Cerro Tololo Inter-American Observatory to generate a new weak lensing shear catalog containing approximately 80 million galaxies. This new catalog will be used to perform an independent cosmic shear analysis, which connects weak lensing measurements to cosmological model parameters. The dataset will cover 5,000 sq. deg. of sky outside of the footprint of the Dark Energy Survey (DES). This investigation will provide a statistically independent cross-check of recent cosmic shear analyses from DES and other surveys. Furthermore, when combined with DES, this program will provide a shear catalog that covers 10,000 sq. deg. of sky, giving access to cosmological scales that have not been explored by current weak lensing surveys. The public release of processed DECam data will increase scientific accessibility for amateur and professional astronomers. In particular, it will help the community prepare for early data from the NSF-funded Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

暗物质和暗能量构成了宇宙的95%，但支配这些成分的物理学还没有得到很好的理解。弱透镜效应，即光在宇宙中通过质量时的弯曲，是研究暗物质和暗能量的最有力的工具之一。最近宇宙的弱透镜测量与早期宇宙的宇宙微波背景测量不一致，这可能表明我们对宇宙学的理解是不完整的。研究人员将使用公共观测数据收集一个独立的弱透镜数据集，覆盖一个新的天空区域，可与最大的最先进的弱透镜调查相媲美。这些数据将用于进行独立分析，并直接解决早期和近代宇宙测量之间的紧张关系。该计划将成为不同学生群体教育的一部分。它还将包括通过与阿德勒天文馆和太空探索者计划合作，将艺术和科学相结合，与公众分享宇宙学的外展工作。研究人员将使用NSF Cerro Tololo美洲天文台暗能量相机（DECam）的公共数据来生成一个新的弱透镜剪切目录，其中包含大约8000万个星系。这个新的星表将被用来进行独立的宇宙剪切分析，它将弱透镜测量与宇宙模型参数联系起来。数据集将覆盖5,000平方米。°的暗能量调查（DES）足迹之外的天空。这项调查将提供一个统计独立的交叉检查最近的宇宙剪切分析DES和其他调查。此外，当与DES相结合时，该程序将提供一个涵盖10，000平方米的剪切目录。°的的天空，使访问宇宙尺度，还没有探索目前的弱透镜调查。公开发布经处理的DECam数据将增加业余和专业天文学家的科学可及性。特别是，它将帮助社区为NSF资助的Vera C的早期数据做好准备。Rubin Observatory Legacy Survey of Space and Time（LSST）.该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

The DECam Local Volume Exploration Survey Data Release 2

• DOI: 10.3847/1538-4365/ac78eb
• 发表时间: 2022-03
• 期刊: The Astrophysical Journal Supplement Series
• 作者: A. Drlica-Wagner;P. Ferguson;M. Adam'ow;M. Aguena;F. Andrade-Oliveira;D. Bacon;K. Bechtol;E. Bell;E. Bertin;P. Bilaji;S. Bocquet;C. Bom;D. Brooks;D. Burke;J. Carballo-Bello;J. Carlin;A. Rosell;M. Kind;J. Carretero;F. Castander;W. Cerny;C. Chang;Y. Choi;C. Conselice;M. Costanzi;D. Crnojevi'c;L. Costa;J. Vicente;S. Desai;J. Esteves;S. Everett;I. Ferrero;M. Fitzpatrick;B. Flaugher;D. Friedel;J. Frieman;J. Garc'ia-Bellido;M. Gatti;E. Gaztañaga;D. Gerdes;D. Gruen;R. Gruendl;J. Gschwend;W. Hartley;D. Hernández-Lang;S. Hinton;D. Hollowood;K. Honscheid;A. Hughes;A. Jacques;D. James;M. Johnson;K. Kuehn;N. Kuropatkin;O. Lahav;T. Li;C. Lidman;H. Lin;M. March;J. Marshall;D. Mart'inez-Delgado;C. E. Mart'inez-V'azquez;P. Massana;S. Mau;M. McNanna;Peter Melchior;F. Menanteau;A. Miller;R. Miquel;J. Mohr;R. Morgan;B. Mutlu-Pakdil;R. Munoz;E. Neilsen;D. Nidever;R. Nikutta;J. L. N. Castellón;N. E. D. Noel;R. Ogando;K. Olsen;A. Pace;A. Palmese;F. Paz-Chinch'on;M. Pereira;A. Pieres;A. P. Malag'on;J. Prat;A. Riley;M. Rodríguez-Monroy;A. Romer;A. Roodman;M. Sako;J. Sakowska;E. Sanchez;F. S'anchez;D. Sand;L. Santana-Silva;B. Santiago;M. Schubnell;S. Serrano;I. Sevilla-Noarbe;J. Simon;M. Smith;M. Soares-Santos;G. Stringfellow;E. Suchyta;D. Suson;C. Tan;G. Tarlé;K. Tavangar;D. Thomas;C. To;E. Tollerud;M. Troxel;D. Tucker;T. Varga;A. K. Vivas;A. Walker;J. Weller;R. Wilkinson;J. F. Wu;B. Yanny;E. Zaborowski;A. Zenteno