Open Supernova Catalog anomaly detection

The analysis consists of the following steps: (1) data selection from the OSC and approximation of the pre-processed data with Gaussian processes, (2) dimensionality reduction, (3) searching for outliers with the use of the isolation forest algorithm, and (4) expert analysis of the identified outliers. The pipeline returned 81 candidate anomalies, 27 (33 per cent) of which were confirmed to be from astrophysically peculiar objects.

Found anomalies correspond to a selected sample of 1.4 per cent of the initial automatically identified data sample of approximately 2000 objects. Among the identified outliers we recognized superluminous supernovae, non-classical Type Ia supernovae, unusual Type II supernovae, one active galactic nucleus and one binary microlensing event. We also found that 16 anomalies classified as supernovae in the literature are likely to be quasars or stars.

Our proposed pipeline represents an effective strategy to guarantee we shall not overlook exciting new science hidden in the data we fought so hard to acquire. All code and products of this investigation are made publicly available. (snad.space/osc/)