Project Grant 2206317
- The University of Central Florida was awarded a $416,532 three-year Project Grant from the National Science Foundation Division of Astronomical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The grant will support the development of machine learning techniques to enable three-dimensional mapping and characterization of brown dwarf and exoplanet atmospheres using significantly less computational resources than current methods. A team led by the...
- The National Science Foundation (NSF) Division of Astronomical Sciences awarded a $399,362 Project Grant to the University of California-Santa Cruz (UCSC) to explore the physics of cloud formation and dynamics in the atmospheres of giant planets and brown dwarfs. The three-year research program will simulate cloudy atmospheric conditions on the four solar system giant planets as well as exoplanets and brown dwarfs, in order to improve understanding of temperature, chemical mixing, and patchiness...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $330,607 to The University of Central Florida Board of Trustees to conduct collaborative research on the L/T transition in brown dwarfs, the evolutionary changes in their atmospheres. The research team will create comprehensive models to understand how cloud formation and chemical processes impact the polarization and flux signals of brown dwarfs, with the...
- This $560,337 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support collaborative research at the University of Arizona focused on improving our understanding of how convective mixing impacts the nature of gas giant exoplanet atmospheres. The project aims to develop computational simulation tools to investigate the physical, evolutionary, and observational consequences of convection for gas giant worlds, which...
- This Project Grant award from the National Science Foundation (NSF) Division of Astronomical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), provides $490,337 to the University of California, Santa Cruz (UCSC) from August 15, 2023 to July 31, 2026. The primary objective of this project is to develop novel data-driven machine learning techniques to enhance the computational performance and accuracy of numerical simulations for modeling relativistic plasma flows in...
- This three-year, $110,972 Project Grant from the National Science Foundation's Division of Astronomical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of new statistical and machine learning methods and software to improve the detection, characterization, and classification of astrophysical objects using multi-epoch imaging survey data. The California Institute of Technology will apply innovative algorithms to optimize the discovery...
- This $457,976 Project Grant awarded by the National Science Foundation's (NSF) Division of Astronomical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports research to develop a novel framework for constraining models of baryonic feedback in the universe. The research team at the University of Chicago will apply artificial intelligence and machine learning techniques to data from cosmic microwave background and galaxy surveys to gain insights into the...
- This $306,464 Project Grant awarded by the National Science Foundation's (NSF) Division of Astronomical Sciences under the Mathematical and Physical Sciences (CFDA 47.049) program will develop "DECIPHER: Deep Computer Vision in the Astrophysics of Planet Formation." The project aims to create a machine learning tool that can detect and measure the mass of exoplanets forming in protoplanetary disks from observational data. This cross-disciplinary effort will leverage advances in...
- This National Science Foundation (NSF) Division of Astronomical Sciences award, under the Mathematical and Physical Sciences program (CFDA 47.049), provides $405,151 to the University of Chicago for a 3-year collaborative research project focused on probing the atmospheres of exoplanets orbiting distant stars. The project team, led by the University of Chicago and Arizona State University, will utilize high-resolution spectroscopy techniques to address key science questions about the chemical...
- This $421,175 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program supports a research project titled "The Emergence of Star Clusters: Insights from Artificial Intelligence." The project aims to better understand the physical mechanisms of star formation by analyzing data from the Atacama Large Millimeter Array and the James Webb Space Telescope to measure the timescales for clearing natal gas from newly formed stellar clusters....
This Project Grant award from the National Science Foundation Division of Astronomical Sciences provides $103,690 to support the development of new machine learning techniques to enable three-dimensional mapping and characterization of brown dwarf and exoplanet atmospheres. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), a team led by the University of Central Florida and the University of California, Santa Cruz will create a surrogate radiative transfer code using neural networks to model atmospheric spectra more efficiently than current methods. They will also develop a 3-D mapping code to fit time-resolved observations in a Bayesian framework using the surrogate code. The University of California, Santa Cruz will serve as a sub-awardee, providing location of performance in Santa Cruz, California. The aims of this research are to advance understanding of atmospheric properties and cloud dynamics through 3-D climate modeling at significantly reduced computational cost.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $103.7k | 8/23/22 |