CAREER: Echo Mapping the Census of Supermassive Black Hole Mass, Accretion, and Spin

职业：回声测绘超大质量黑洞质量、吸积和自旋普查

• 批准号: 1945546
• 负责人: Jonathan Trump
• 金额: $ 73.81万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1945546&HistoricalAwards=false
• 关键词: CAREER; Echo; Mapping; Census; Supermassive

This program will compile a census of supermassive black holes in the universe. Essentially every galaxy hosts a supermassive black hole in its center. The program will use a new generation of time-domain observations from the Sloan Digital Sky Survey (SDSS) and Large Synoptic Survey Telescope (LSST) to map the fundamental black hole properties of mass, spin, and accretion. This will give insights into how supermassive black holes and galaxies evolve across cosmic time. The PI will develop a “bridge program” for underrepresented minority undergraduate physics majors at the University of Connecticut to increase their number in STEM fields by completing their education. A census of supermassive black hole will be made using spectroscopic and photometric Reverberation Mapping (RM) in a series of time domain campaigns with massively multiplexed spectroscopy to measure their mass and accretion disks by first using the SDSS-RM survey. Techniques will be developed to construct contemporaneous UV-optical spectral energy distributions that avoid the effects of quasar variability which together with the full SDSS-RM sample with black hole masses will be the first to determine a large number of black hole spin masses. Future matched UV photometry together with time domain optical LSST data for spin measurements with the SDSS-V survey will result in a census of the black hole population and characteristics.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.

该计划将汇编宇宙中超大质量黑洞的普查。基本上每个星系的中心都有一个超大质量的黑洞。该计划将使用来自斯隆数字巡天(SDSS)和大型天文观测望远镜(LSST)的新一代时域观测来绘制质量、自转和吸积的基本黑洞属性图。这将让我们深入了解超大质量黑洞和星系是如何在宇宙时间内演化的。PI将为康涅狄格大学未被充分代表的少数族裔本科物理专业的学生开发一个“桥梁计划”，通过完成他们的教育来增加他们在STEM领域的人数。为了测量超大质量黑洞的质量和吸积盘，将首先使用SDSS-RM测量，在一系列的时间域运动中使用光谱和光度学混响映射(RM)和大规模多路复用光谱测量它们。将开发技术来构建同时的紫外光光谱能量分布，以避免类星体可变性的影响，这将与具有黑洞质量的完整SDSS-RM样本一起第一次确定大量的黑洞自旋质量。未来匹配的UV光度测量和用于自旋测量的时间域光学LSST数据与SDSS-V调查将导致对黑洞数量和特征的普查。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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 Sloan Digital Sky Survey Reverberation Mapping Project: Estimating Masses of Black Holes in Quasars with Single-epoch Spectroscopy

• DOI: 10.3847/1538-4357/abbc1c
• 发表时间: 2020-11-01
• 期刊: ASTROPHYSICAL JOURNAL
• 影响因子: 4.9
• 作者: Bonta, Elena Dalla;Peterson, Bradley M.;Vestergaard, Marianne
• 通讯作者: Vestergaard, Marianne

CLEAR: The Gas-phase Metallicity Gradients of Star-forming Galaxies at 0.6 < z < 2.6

• DOI: 10.3847/1538-4357/ac28f4
• 发表时间: 2020-11
• 期刊: The Astrophysical Journal
• 作者: R. Simons;C. Papovich;I. Momcheva;J. Trump;G. Brammer;V. Estrada-Carpenter;B. Backhaus;N. Cleri-N.-C

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data

斯隆数字巡天第十七次数据发布：MaNGA、MaStar和APOGEE-2数据完整发布

• DOI: 10.3847/1538-4365/ac4414
• 发表时间: 2022
• 期刊: The Astrophysical Journal Supplement Series
• 作者: Abdurro’uf;Accetta, Katherine;Aerts, Conny;Silva Aguirre, Víctor;Ahumada, Romina;Ajgaonkar, Nikhil;Filiz Ak, N.;Alam, Shadab;Allende Prieto, Carlos;Almeida, Andrés
• 通讯作者: Almeida, Andrés

Multimessenger time-domain signatures of supermassive black hole binaries

超大质量黑洞双星的多信使时域特征

• DOI: 10.1093/mnras/stab3713
• 发表时间: 2021
• 期刊: Monthly Notices of the Royal Astronomical Society
• 影响因子: 4.8
• 作者: Charisi, Maria;Taylor, Stephen R.;Runnoe, Jessie;Bogdanovic, Tamara;Trump, Jonathan R.
• 通讯作者: Trump, Jonathan R.

CLEAR: Paschen-β Star Formation Rates and Dust Attenuation of Low-redshift Galaxies

清晰：低红移星系的帕邢-β恒星形成率和尘埃衰减

• DOI: 10.3847/1538-4357/ac5a4c
• 发表时间: 2022
• 期刊: The Astrophysical Journal
• 作者: Cleri, Nikko J.;Trump, Jonathan R.;Backhaus, Bren E.;Momcheva, Ivelina;Papovich, Casey;Simons, Raymond;Weiner, Benjamin;Estrada-Carpenter, Vicente;Finkelstein, Steven L.;Giavalisco, Mauro
• 通讯作者: Giavalisco, Mauro