Crowdsourcing the Sky with the NOIRLab Source Catalog

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The all-sky NOIRLab Source Catalog (NSC) is a catalog of nearly all the data, taken by astronomers over many years that is resident in NOIRLab’s image archive. This data includes information on three quarters of the sky and is available for exploration with innovative big data techniques that will also be useful for other large surveys such as that to be obtained with the Rubin Observatory. This project will use the database to address two important science questions regarding asteroids and pulsating stars. There are many asteroids in our solar system, some of which are nearby and could potentially impact the earth. Astronomers have been trying to catalog most of them over the last couple of decades. The NSC can help with this effort as it is able to detect fainter asteroids than most current searches and covers parts of the sky not previously explored. Large scale structures in our Milky Way galaxy can be mapped and explored by finding certain types of pulsating stars for which distances can be accurately determined from previous studies. The project includes a plan to involve tens of thousands of citizen scientists to assist in various aspects of the project notably to find stars that have change position on the sky.New techniques are needed to extract important scientific information and insights from both existing data sets and future large data such as the Legacy Survey of Space and Time (LSST) at the Rubin Observatory. The all-sky NOIRLab Source Catalog (NSC) is a catalog of nearly all public data in NOIRLab’s image archive. The NSC covers three quarters of the sky going substantially deeper than previous projects and includes data in areas never before cataloged. The project looks to explore the NSC to develop big data techniques focused on two science cases. The first of these is to search for high proper motion objects, especially Near-Earth Objects that could potentially impact the earth. Modern clustering algorithms such as Spectral Clustering and DBSCAN will be utilized to process the 68 billion measurements and provide a census of nearby objects. The second science investigation will be on searching for stellar variability. The time-series nature of the NSC will permit a search for objects that vary in brightness over time. This includes variable stars that are good tracers of the structure of the Milky Way. Non-parametric period estimation techniques and new variable star templates will be utilized to enable automatic and robust identification and classification of all variables in the NSC. An extensive citizen scientist program is planned for assistance in the detection of proper motions of stars.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.