Precision Cosmology with Photometrically-Classified Supernovae

光度分类超新星的精密宇宙学

• 批准号: 2108094
• 负责人: Masao Sako
• 金额: $ 34.44万
• 依托单位: University of Pennsylvania
• 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=2108094&HistoricalAwards=false
• 关键词: Precision; Cosmology; Photometrically; Classified; Supernovae

Type 1a supernovae can be used as a tool to measure distances to galaxies at high redshift. Surveys of such supernovae therefore allow astronomers to determine cosmological parameters. This project makes use of imaging surveys to make improvements in photometric classification of supernovae and to construct a framework for accurately characterizing the resulting uncertainties on cosmological model parameters. The Principal Investigator will establish a new mentoring program for physics majors at the University of Pennsylvania. This program will help create a cultural shift within the department and increase awareness of issues related to inclusivity and diversity. Cosmological parameter measurements with present and future supernova surveys will rely on photometric Type Ia supernova (SN Ia) classification with or without spectroscopic redshifts of the host galaxies. The PI will conduct a research program to make improvements in photometric classification and to construct a framework for accurately characterizing the systematic uncertainties on cosmological model parameters. The project focuses on quantifying the systematic uncertainties due to (1) photometric misclassification of SN candidates and (2) mis-association of their host galaxies. Data from the Dark Energy Survey will be used to characterize the non-SN Ia population. This will be used to help improve photometric classifiers as well as place robust uncertainties on misclassification rates versus redshift, which is essential for precision cosmology. The methodology will be applied to help make further improvements with the Vera Rubin Observatory. The PI will establish a mentoring and support program for Physics majors at the University of Pennsylvania. The mentors will consist of graduate students, who will be trained through the PI and other teaching resources at Penn. Undergraduate students will be paired with a mentor, who will guide them through the process of finding a research advisor, making realistic decisions about their career paths, and for those interested, help them with the graduate-school application process.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.

1a型超新星可以用作测量高红移星系距离的工具。因此，对这类超新星的观测使天文学家能够确定宇宙学参数。本项目利用成像巡天来改进超新星的光度分类，并构建一个框架来准确表征由此产生的宇宙学模型参数的不确定性。首席研究员将为宾夕法尼亚大学的物理专业学生建立一个新的指导项目。该项目将有助于在部门内部创造文化转变，并提高对包容性和多样性相关问题的认识。当前和未来超新星调查的宇宙学参数测量将依赖于Ia型超新星（SN Ia）的光度分类，无论是否存在宿主星系的光谱红移。PI将进行一项研究计划，以改进光度分类，并构建一个框架，以准确表征宇宙模型参数的系统不确定性。该项目的重点是量化由于(1)对SN候选者的光度错误分类和(2)其宿主星系的错误关联造成的系统不确定性。暗能量调查的数据将被用来描述非Ia星系群的特征。这将用于帮助改进光度分类器，并对误分类率和红移进行强大的不确定性，这对精确宇宙学至关重要。该方法将用于帮助维拉鲁宾天文台进一步改进。PI将为宾夕法尼亚大学的物理专业学生建立一个指导和支持计划。导师将由研究生组成，他们将通过私人项目和宾夕法尼亚大学的其他教学资源接受培训。本科生将与一名导师配对，导师将指导他们寻找研究顾问，对自己的职业道路做出现实的决定，对于感兴趣的学生，还将帮助他们申请研究生院。该奖项反映了美国国家科学基金会的法定使命，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 Dark Energy Survey supernova program: cosmological biases from supernova photometric classification

暗能量巡天超新星计划：超新星光度分类的宇宙学偏差

• DOI: 10.1093/mnras/stac1404
• 发表时间: 2022
• 期刊: Monthly Notices of the Royal Astronomical Society
• 影响因子: 4.8
• 作者: Vincenzi, M.;Sullivan, M.;Möller, A.;Armstrong, P.;Bassett, B. A.;Brout, D.;Carollo, D.;Carr, A.;Davis, T. M.;Frohmaier, C.
• 通讯作者: Frohmaier, C.

Photo-zSNthesis: Converting Type Ia Supernova Lightcurves to Redshift Estimates via Deep Learning

• DOI: 10.3847/1538-4357/aceafa
• 发表时间: 2023-05
• 期刊: The Astrophysical Journal
• 作者: H. Qu;M. Sako

Photometric Classification of Early-time Supernova Light Curves with SCONE

• DOI: 10.3847/1538-3881/ac39a1
• 发表时间: 2021-11
• 期刊: The Astronomical Journal
• 作者: H. Qu;M. Sako

The Dark Energy Survey Supernova Program: Cosmological Biases from Host Galaxy Mismatch of Type Ia Supernovae

• DOI: 10.3847/1538-4357/ad251d
• 发表时间: 2023-07
• 期刊: The Astrophysical Journal
• 作者: H. Qu;M. Sako;M. Vincenzi;C. Sánchez;D. Brout;R. Kessler;R. Chen;T. Davis;L. Galbany;L. Kelsey;J. Lee;C. Lidman;B. Popovic;B. Rose;D. Scolnic;M. Smith;M. Sullivan;P. Wiseman;T. Abbott;M. Aguena;O. Alves;D. Bacon;E. Bertin;D. Brooks;D. Burke;A. Rosell;J. Carretero;L. Costa;M. Pereira;H. Diehl;P. Doel;S. Everett;I. Ferrero;J. Frieman;J. García-Bellido;G. Giannini;D. Gruen;R. Gruendl;G. Gutiérrez;S. Hinton;D. Hollowood;K. Honscheid;D. James;K. Kuehn;O. Lahav;J. Marshall;J. Mena-Fernández;F. Menanteau;R. Miquel;R. Ogando;A. Palmese;A. Pieres;A. P. Malagón;M. Raveri;E. Sanchez;I. Sevilla-Noarbe;M. Soares-Santos;E. Suchyta;G. Tarlé;N. Weaverdyck;Des collaboration

The dark energy survey 5-yr photometrically identified type Ia supernovae

暗能量调查 5 年光度鉴定 Ia 型超新星

• DOI: 10.1093/mnras/stac1691
• 发表时间: 2022
• 期刊: Monthly Notices of the Royal Astronomical Society
• 影响因子: 4.8
• 作者: Möller, A;Smith, M;Sako, M;Sullivan, M;Vincenzi, M;Wiseman, P;Armstrong, P;Asorey, J;Brout, D;Carollo, D
• 通讯作者: Carollo, D