Project Grant 2406110
- This $599,199 National Science Foundation award under the Mathematical and Physical Sciences program will fund development of tools and infrastructure to characterize discoveries from the Vera C. Rubin Observatory's Legacy Survey of Space and Time. Led by Las Cumbres Observatory Global Telescope Network, Inc., the team will build software to model populations of exoplanets, stars, and black holes detected by the LSST survey in real time. This includes algorithms to prioritize microlensing events...
- This $328,623 Project Grant award from the National Science Foundation's (NSF) Division of Astronomical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) will fund a 4-year collaborative research program led by investigators at Louisiana State University, Harvard University, University of Minnesota-Twin Cities, and University of Maryland, College Park. The research aims to improve our understanding of explosive transients, such as gamma-ray bursts and...
- This $325,777 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support a collaborative research effort to study nearby cosmic explosions, known as supernovae, from their earliest moments. The research team will enhance its rapid survey capabilities to promptly identify and study new supernovae in nearby galaxies, taking advantage of a network of small telescopes. This will enable the discovery of...
- This $134,210 National Science Foundation project grant supports the development and enhancement of the Supernovae Early Warning System (SNEWS) network. SNEWS is an international collaboration between neutrino and dark matter detectors designed to provide early alerts of impending supernovae in our galaxy to the astronomy community. Funded activities under this three-year award include optimizing the SNEWS 2.0 system to improve detection capabilities, developing a follow-up strategy involving...
- This $249,278 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program will support the continued development of the Supernovae Early Warning System (SNEWS) network. SNEWS is an international collaboration between neutrino and dark matter detectors designed to provide automated early alerts of impending supernovae in our galaxy to the astronomical community. Under this award, a collaborative group of scientists from multiple institutions will work to...
- This Project Grant from the National Science Foundation's Mathematical and Physical Sciences Directorate (NSF MPS), under the Mathematical and Physical Sciences program (CFDA 47.049), provides $143,185 to support collaborative research advancing the Supernova Early Warning System (SNEWS) through August 2025. SNEWS is a network between neutrino and dark matter detectors designed to provide automated prompt alerts of impending supernovae in our galaxy. The awardee, University of Rochester, will...
- This Project Grant award, provided by the National Science Foundation (NSF) under the Integrative Activities program (CFDA 47.083), aims to establish a collaboration between the University of Hawaii (UH) and Duke University to advance supernova cosmology research. The $277,608 award will support activities to: Leverage UH-led supernova discovery surveys, such as Pan-STARRS and ATLAS, to significantly reduce key systematic uncertainties in cosmological parameters. This will be achieved by...
- This $532,327 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program will fund a research project at the University of Chicago to study the chemical composition of stars in the Milky Way's stellar halo. The goal is to reconstruct the early assembly of the Milky Way and search for signatures of the first supernovae in the universe. The research will leverage data from the Sloan Digital Sky Survey (SDSS) to identify and analyze approximately...
- This $415,181 project grant from the National Science Foundation Division of Astronomical Sciences will fund collaborative research between Michigan State University and the University of Virginia to analyze data and model stripped supernovae. The researchers will analyze data from a large set of stripped supernovae and model the data using radiative transfer software called TARDIS in combination with machine learning emulators. They aim to resolve controversies in the supernova community...
- This $717,600 National Science Foundation project grant, funded under the Mathematical and Physical Sciences program (CFDA 47.049), supports research to better understand the nature of dark energy and the expansion of the universe. The principal investigator will use the Young Supernova Experiment to measure a uniform sample of Type Ia supernovae in the nearby universe and develop novel methods for determining cosmological parameters. They will also identify Type Ia supernovae in distant...
CDS & E: ENABLING POPULATION STUDIES OF SUPERNOVAE IN THE ERA OF VERA RUBIN VIA SIMULATED-BASED INFERENCE -THE VERA C. RUBIN OBSERVATORY'S LEGACY SURVEY OF SPACE AND TIME (LSST) IS EXPECTED TO DISCOVER OVER 10,000 SUPER-LUMINOUS SUPERNOVAE (SLSNE) ANNUALLY, A SIGNIFICANT INCREASE FROM THE AROUND 100 KNOWN TODAY. SLSNE ARE RARE, EXCEPTIONALLY BRIGHT SUPERNOVAE, BELIEVED TO BE POWERED BY NEWLY FORMED, HIGHLY MAGNETIZED NEUTRON STARS CALLED MAGNETARS. THIS PROJECT AIMS TO DEVELOP ADVANCED STATISTICAL TECHNIQUES TO ANALYZE THIS UNPRECEDENTED VOLUME OF DATA, IMPROVING OUR UNDERSTANDING OF THE PROGENITOR SYSTEMS AND THE PROPERTIES OF THESE MAGNETARS. THE METHODOLOGIES DEVELOPED CAN BE APPLIED TO OTHER SN CLASSES. ADDITIONALLY, THE RESEARCH TEAM WILL CREATE AN ONLINE GAME THAT ALLOWS USERS TO CLASSIFY SUPERNOVAE BASED ON LSST LIGHT CURVES. THE GAME WILL BE FEATURED AT THE ANNUAL CAMBRIDGE SCIENCE FESTIVAL AND MADE AVAILABLE ONLINE, ENGAGING AND EDUCATING A BROAD AUDIENCE ABOUT THESE EXTRAORDINARY COSMIC EVENTS. A SET OF LSST SLSNE WILL BE SIMULATED USING ARCHIVAL LIGHT CURVES AND INCORPORATED INTO THE PLASTICC DATASET. A CUSTOM CLASSIFIER WILL BE DEVELOPED TO IDENTIFY SLSNE WITH HIGH ACCURACY, AND BOTH THE DATASETS AND CLASSIFIER WILL BE MADE PUBLICLY ACCESSIBLE. SECOND, A NEW INFERENCE PIPELINE FOR SLSN LIGHT CURVES WILL BE CREATED, UTILIZING SIMULATION-BASED INFERENCE (SBI), AND ITS PERFORMANCE WILL BE THOROUGHLY STUDIED UNDER VARIOUS CONDITIONS. A BAYESIAN HIERARCHICAL MODELING FRAMEWORK WILL BE IMPLEMENTED TO COMBINE INDIVIDUAL EVENT DATA AND CORRECT FOR OBSERVATIONAL BIASES. FINALLY, THE FIRST YEAR OF LSST DATA WILL BE ANALYZED TO PLACE THE STRONGEST CONSTRAINTS ON THE UNDERLYING SLSN PROGENITOR POPULATION. 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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 7/3/25 | ||
| Not listed | $436.3k | 8/29/24 |