Tails: Chasing Comets with the Zwicky Transient Facility and Deep Learning

02/26/2021
by   Dmitry A. Duev, et al.
9

We present Tails, an open-source deep-learning framework for the identification and localization of comets in the image data of the Zwicky Transient Facility (ZTF), a robotic optical time-domain survey currently in operation at the Palomar Observatory in California, USA. Tails employs a custom EfficientDet-based architecture and is capable of finding comets in single images in near real time, rather than requiring multiple epochs as with traditional methods. The system achieves state-of-the-art performance with 99 recall, 0.01 predicted position. We report the initial results of the Tails efficiency evaluation in a production setting on the data of the ZTF Twilight survey, including the first AI-assisted discovery of a comet (C/2020 T2) and the recovery of a comet (P/2016 J3 = P/2021 A3).

READ FULL TEXT

page 3

page 6

page 7

page 8

page 9

research
07/15/2014

Machine Learning Classification of SDSS Transient Survey Images

We show that multiple machine learning algorithms can match human perfor...
research
11/20/2020

Smart obervation method with wide field small aperture telescopes for real time transient detection

Wide field small aperture telescopes (WFSATs) are commonly used for fast...
research
09/28/2020

Detecting optical transients using artificial neural networks and reference images from different surveys

To search for optical counterparts to gravitational waves, it is crucial...
research
10/04/2017

Effective Image Differencing with ConvNets for Real-time Transient Hunting

Large sky surveys are increasingly relying on image subtraction pipeline...
research
03/15/2023

The Tiny Time-series Transformer: Low-latency High-throughput Classification of Astronomical Transients using Deep Model Compression

A new golden age in astronomy is upon us, dominated by data. Large astro...
research
06/23/2020

MANTRA: A Machine Learning reference lightcurve dataset for astronomical transient event recognition

We introduce MANTRA, an annotated dataset of 4869 transient and 71207 no...
research
10/12/2021

Development of Deep Transformer-Based Models for Long-Term Prediction of Transient Production of Oil Wells

We propose a novel approach to data-driven modeling of a transient produ...

Please sign up or login with your details

Forgot password? Click here to reset