Real-time detection of anomalies in large-scale transient surveys

@article{Muthukrishna2021RealtimeDO,
  title={Real-time detection of anomalies in large-scale transient surveys},
  author={Daniel Muthukrishna and Kaisey S. Mandel and Michelle Lochner and Sara Webb and Gautham Narayan},
  journal={ArXiv},
  year={2021},
  volume={abs/2111.00036}
}
New large-scale transient surveys will observe millions of transient alerts each night, making standard approaches of visually identifying new and interesting transients unfeasible. We present a novel method of automatically detecting anomalies in real-time transient light curves. Using state-of-the-art deep recurrent neural networks with Long Short Term Memory (LSTM) units, we present one of the first methods designed to provide anomaly scores of photometric data as a function of time. We build… 

SNAD transient miner: Finding missed transient events in ZTF DR4 using k-D trees

Autonomous Real-Time Science-Driven Follow-up of Survey Transients

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