Active Anomaly Detection for time-domain discoveries

TL;DR

This paper demonstrates that active learning techniques significantly improve the discovery of unusual astronomical objects in light curve data by adaptively updating anomaly detection models, outperforming traditional static methods.

Contribution

The paper introduces an active anomaly detection algorithm that adaptively modifies the Isolation Forest to enhance discovery of rare objects in astronomical data, showing improved results over static models.

Findings

AAD identified ~80% more true anomalies than static IF in real data.

Active learning boosts anomaly detection efficiency in large sky surveys.

The method is effective on both simulated and real astronomical light curves.

Abstract

We present the first evidence that adaptive learning techniques can boost the discovery of unusual objects within astronomical light curve data sets. Our method follows an active learning strategy where the learning algorithm chooses objects which can potentially improve the learner if additional information about them is provided. This new information is subsequently used to update the machine learning model, allowing its accuracy to evolve with each new information. For the case of anomaly detection, the algorithm aims to maximize the number of scientifically interesting anomalies presented to the expert by slightly modifying the weights of a traditional Isolation Forest (IF) at each iteration. In order to demonstrate the potential of such techniques, we apply the Active Anomaly Discovery (AAD) algorithm to 2 data sets: simulated light curves from the PLAsTiCC challenge and real light curves from the Open Supernova Catalog. We compare the AAD results to those of a static IF. For both methods, we performed a detailed analysis for all objects with the ~2% highest anomaly scores. We show that, in the real data scenario, AAD was able to identify ~80\% more true anomalies than the IF. This result is the first evidence that AAD algorithms can play a central role in the search for new physics in the era of large scale sky surveys.