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Abstract Using the second data release from the Zwicky Transient Facility (ZTF), Chen et al. created a ZTF Catalog of Periodic Variable Stars (ZTF CPVS) of 781,602 periodic variables stars (PVSs) with 11 class labels. Here, we provide a new classification model of PVSs in the ZTF CPVS using a convolutional variational autoencoder and hierarchical random forest. We cross-match the sky-coordinate of PVSs in the ZTF CPVS with those presented in the SIMBAD catalog. We identify non-stellar objects that are not previously classified, including extragalactic objects such as Quasi-Stellar Objects, Active Galactic Nuclei, supernovae and planetary nebulae. We then create a new labeled training set with 13 classes in two levels. We obtain a reasonable level of completeness (≳90%) for certain classes of PVSs, although we have poorer completeness in other classes (∼40% in some cases). Our new labels for the ZTF CPVS are available via Zenodo.
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A Fast Periodicity Detection Algorithm Sensitive to Arbitrary Waveforms
Abstract A reexamination of period-finding algorithms is prompted by new large-area astronomical sky surveys that can identify billions of individual sources having a thousand or more observations per source. This large increase in data necessitates fast and efficient period detection algorithms. In this paper, we provide an initial description of an algorithm that is being used for the detection of periodic behavior in a sample of 1.5 billion objects using light curves generated from Zwicky Transient Facility (ZTF) data. We call this algorithm “Fast Periodicity Weighting” (FPW), derived using a Gaussian Process formalism. Periodic sources in ZTF show a wide variety of waveforms, some quite complex, including eclipsing objects, sinusoidally varying objects also exhibiting eclipses, objects with cyclotron emission at various phases, and accreting objects with complex waveforms. A major advantage of the FPW algorithm is that it is sensitive to a broad range of waveforms. We describe the FPW algorithm and its application to ZTF, and provide efficient code for both CPU and GPU.
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- Award ID(s):
- 2019786
- PAR ID:
- 10593605
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Publications of the Astronomical Society of the Pacific
- Volume:
- 137
- Issue:
- 5
- ISSN:
- 0004-6280
- Format(s):
- Medium: X Size: Article No. 054504
- Size(s):
- Article No. 054504
- Sponsoring Org:
- National Science Foundation
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