Abstract
The SNAD team has developed an adaptive learning algorithm, named Pine Forest (PF), to enhance anomaly detection in astronomical data. Recognizing the essential role of human engagement in the discovery process, PF presents outliers to a human expert for review, and filters out trees which disagree with the feedback provided. During the sixth annual SNAD workshop (https://snad.space/2023/), held in 2023 July, we applied PF to the Zwicky Transient Facility’s DR17 data. Interesting discoveries include long-duration objects such as supernovae, along with fast transients like red dwarf flares and one microlensing event. As a result, new variable stars were identified and labeled in the SNAD knowledge database.
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