Cosmology Lunchtime Seminar

Efficient identification and follow-up of astronomical transients is hindered by the need to manually select promising candidates from data streams that contain many false positives. With data from Pan-STARRS1 we present the citizen science project, Supernova Hunters created with the Zooniverse project builder. The project allows us to crowdsource classifications of supernova candidates, and test methods to combine human and machine classifications. We show this combination produces a purer and more complete sample of supernovae than either individually.