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CAREER: Exploring the dark sector with state-of-the-art galaxy surveys

NSF

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About This Grant

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will map cosmic structure across the sky to incredible depth. Such maps have immense statistical power to shed light on dark energy and dark matter, perhaps the most compelling mysteries in modern physics. To reach the full potential of LSST and other upcoming projects, a better understanding of astrophysical processes and observational uncertainties is required. This program focuses on two of the most important astrophysical effects, determining where galaxies form and what shapes they have. Prof. Blazek’s team will pursue several linked themes leading to robust, sophisticated cosmological analyses of LSST data. His tightly coupled education plan includes a mentoring and research program for a dynamic and comprehensive student cohort. Prof. Blazek will also develop a numerical methods course for graduate and advanced undergraduate students. This course will provide workforce training in cutting-edge techniques used in this research. Weak lensing and galaxy clustering are powerful probes of dark energy and dark matter. Intrinsic alignment (IA) and galaxy bias represent two of the most critical challenges to these measurements. This program combines Blazek’s leading expertise in IA with novel simulation and artificial intelligence / machine learning techniques. Applying a semi-analytic approach to IA and bias on gravity-only simulations will enable production of mock galaxy catalogs in large cosmological volumes with a wide range of IA properties. By developing sophisticated emulation with neural networks, the research will accelerate the process of creating and analyzing simulated galaxy data, providing direct simulation-based modeling. These innovations will enable Rubin-LSST data analyses not possible with existing methods and will broaden the discovery potential of future data through measurements of IA as a cosmic probe. Prof. Blazek’s advancement of research opportunities and targeted mentoring for students in physics and astronomy builds substantially on a successful pilot program he has developed. His simulated galaxy catalogs and modeling tools will be made public, benefiting the LSST Dark Energy Science Collaboration and the broader cosmology community, including through a cross-survey project that Blazek leads. This research award is partially funded by a generous gift from Charles Simonyi to the NSF Astronomy division. The project includes significant contributions to Vera C. Rubin Observatory’s Legacy Survey of Space and Time. 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.

Focus Areas

machine learningphysicseducation

Eligibility

universitynonprofitsmall business

How to Apply

Funding Range

Up to $605K

Deadline

2030-08-31

Complexity
Medium
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