Backyard Worlds: Cool Neighbors – Citizen Science and Machine Learning Join Forces

Brown dwarfs represent astrophysical laboratories capable of yielding fundamental insights about planetary atmospheres and the process of star formation at low masses. Although observational and theoretical studies of brown dwarfs have progressed over the past ~25 years, the solar neighborhood census of such objects remains incomplete, especially for faint populations with the very lowest luminosities: Y dwarfs (T_eff < 450 K) and low-metallicity T type subdwarfs. The archival data set furnished by NASA’s Wide-field Infrared Survey Explorer (WISE) has unrivaled potential to pinpoint the lowest luminosity brown dwarfs, but this vast archive has not yet been exhaustively explored. Our existing Backyard Worlds: Planet 9 citizen science project has serendipitously discovered hundreds of brown dwarfs through extensive visual inspection of WISE sky maps. Despite this success, the Backyard Worlds: Planet 9 interface is primarily optimized for discovery of hypothesized outer solar system planets rather than brown dwarfs. We will soon launch a spin-off citizen science project called Backyard Worlds: Cool Neighbors, which is optimized for discovery of extremely low luminosity brown dwarfs. Whereas Backyard Worlds: Planet 9 shows participants randomly selected sky patches, Backyard Worlds: Cool Neighbors is a targeted survey. Our candidate brown dwarf targets are selected from WISE/NEOWISE data using an innovative machine learning technique, then visually inspected by citizen scientists to reliably confirm or reject each candidate’s motion (a telltale proxy for solar neighborhood membership). The coldest and lowest-metallicity brown dwarfs discovered via Backyard Worlds: Cool Neighbors will yield unique insights into planetary atmospheres by expanding the parameter space spanned by the sample of known nearby brown dwarfs.