Advancing the Science from The Hobby-Eberly Telescope Dark Energy Experiment

University Of Texas At Austin, Austin TX

Investigators

Abstract

It is now well established that our universe is undergoing an accelerated expansion. The initial observations in the late 1990s for this expansion come from observations of distant Supernova and have held up to latest analysis today. It is not known what causes this acceleration, named “dark energy”. It is believed to be responsible for about 70% of the matter energy density of the universe. There are many theories for the cause of “dark energy”: perhaps new particles, vacuum energy pushing the universe outward, modifying the theory of relativity concerning the laws of gravity, or some other unknown process which will lead to a more detailed understanding of the evolution of the universe from its origin in a “Big Bang” to the present day. The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) will collect data on at least 700,000 galaxies that are 9 to 11 billion light years away allowing astronomers to measure how fast the universe was expanding at different times in its history. Changes in the expansion rate will reveal the role of “dark energy” at different epochs which will be used to validate/negate the predictions of various theories or give new clues that will lead to a final solution. The observational program for HETDEX is fully funded, and currently about 25% complete. This grant will support the compilation of a detailed catalog containing the calibrated data products that will be available to the scientific community and the public for additional astrophysical science studies. A cell phone app will be developed for a Citizen science program using the data products. This grant will amplify the science from HETDEX by combining a vetted catalog with a public database that will be employed for ancillary science by the scientific community and citizen science applications. The neural networks used for the spectral extractions for classifying the galaxies in the catalog to meet the HETDEX specifications need to be optimized. Partial support will be for an expert at the Texas Advanced Computing Center (TACC) to design the public access to the data base including web development, and data base maintenance and will interface with the postdoctoral fellow for vetting the catalog for the optimization of the visual classification into machine learning. The information from the classification campaign will be folded back into the reduction software for continued reduction optimization. This will allow the data base to be maintained and updated for subsequent data releases as more about the system is learned. This support will build a truly useful data base for the internal use of the HETDEX program, public access for additional science the scientific community as well as Citizen science projects using the cell phone application that will be developed for this program. 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.