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Active STANDARD GRANT National Science Foundation (US)

Collaborative Research: WoU-MMA: Surveying black hole growth history through accretion and mergers

$1.6M USD

Funder National Science Foundation (US)
Recipient Organization University of Maryland Baltimore County
Country United States
Start Date Sep 01, 2024
End Date Aug 31, 2027
Duration 1,094 days
Number of Grantees 1
Roles Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2407750
Grant Description

This project aims to uncover the secrets behind the growth of supermassive black holes (SMBH) located at the centers of galaxies. These enormous black holes are crucial for understanding the evolution of the Universe, as they significantly influence their host galaxies by affecting star formation and the development of galactic structures. The primary focus is to explore how SMBHs grow, either through the accumulation of matter or by merging with other black holes.

The research will also provide educational opportunities and foster diversity within the scientific community. By engaging with the Native Hawaiian community and other underrepresented groups, the project aims to inspire and nurture the next generation of scientists.

The project's main goal is to understand the growth mechanisms of supermassive black holes. It has three specific objectives: 1) to determine the merger rates of SMBHs and relate these to gravitational wave observations; 2) to investigate the growth of SMBHs during the peak period of black hole activity (known as cosmic noon) and its connection to accretion rates; and 3) to map the complete history of SMBH accretion.

The research employs a multiwavelength survey approach, leveraging optical, infrared, and X-ray observations to minimize bias against obscured black holes. Advanced AI techniques will be used to analyze large imaging surveys, identifying dual active galactic nuclei (AGN) and galaxy mergers. This will help predict gravitational wave events and measure black hole masses and luminosities.

Data will be collected using various observatories, including privileged access to Euclid data and several ground-based telescopes. Results will be shared through AGN-DB, an AI-managed database, and supported by tools like THALES and AGNFinder for comprehensive data integration. The project also includes significant educational outreach and diversity initiatives, providing research experiences and professional development for underrepresented students in astronomy.

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.

All Grantees

University of Maryland Baltimore County

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