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NOBEL PRIZE 2026

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NSFDirectorate for Mathematical and Physical Sciences

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

Active
Institution
University of Maryland Baltimore County, MD
Principal investigator
Adi Foord
Funding
$160K
Duration
2024–2027
Open portfolio

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Still being scored

Abstract

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.

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Directorate for Mathematical and Physical SciencesArtificial Intelligence (AI)OBSERVATIONAL ASTRONOMYTHEORETICAL & COMPUTATIONAL ASTROPHYSICSWindows on the Universe (WoU)EXTRAGALACTIC ASTRON & COSMOLOWoU-Windows on the Universe: Tblackblack holesaccretionsupermassive blacksupermassiveblack holeholeholes

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