Machine Learning for the Zwicky Transient Facility

Abstract

The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective.

Published in PASP Focus Issue on the Zwicky Transient Facility (doi: 10.1088/1538-3873/aaf3fa). 14 Pages, 8 Figures

References in corpus (18)

• Gaia Data Release 1. Summary of the astrometric, photometric, and survey properties
• The Zwicky Transient Facility: System Overview, Performance, and First Results
• The Zwicky Transient Facility: Data Processing, Products, and Archive
• The Catalina Surveys Periodic Variable Star Catalog
• Weak Gravitational Lensing with COSMOS: Galaxy Selection and Shape Measurements
• The Zwicky Transient Facility Alert Distribution System
• A recurrent neural network for classification of unevenly sampled variable stars
• A Morphological Classification Model to Identify Unresolved PanSTARRS1 Sources: Application in the ZTF Real-Time Pipeline
• Comparative performance of selected variability detection techniques in photometric time series
• Machine learning for transient discovery in Pan-STARRS1 difference imaging
• How to Find More Supernovae with Less Work: Object Classification Techniques for Difference Imaging
• Machine learning search for variable stars
• The Palomar-Quest Digital Synoptic Sky Survey
• Small near-Earth asteroids in the Palomar Transient Factory survey: A real-time streak-detection system
• 313 new asteroid rotation periods from Palomar Transient Factory observations
• Preparing for advanced LIGO: A Star-Galaxy Separation Catalog for the Palomar Transient Factory
• Towards a Real-time Transient Classification Engine
• ANTARES: A Prototype Transient Broker System

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• The Zwicky Transient Facility: Science Objectives
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• Palomar Gattini-IR: Survey overview, data processing system, on-sky performance and first results
• Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks -- sifting the GOTO candidate stream
• 2900 square degree search for the optical counterpart of short gamma-ray burst GRB 180523B with the Zwicky Transient Facility
• Towards Efficient Detection of Small Near-Earth Asteroids Using the Zwicky Transient Facility (ZTF)
• GWOPS: A VO-technology Driven Tool to Search for the Electromagnetic Counterpart of Gravitational Wave Event