The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
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DOI:
10.3847/1538-4365/acbd41
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发表时间:
2023-02
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影响因子:
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通讯作者:
H. Corbett;Jonathan Carney;R. Gonzalez;O. Fors;N. Galliher;A. Glazier;W. Howard;N. Law;R. Q
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作者:
H. Corbett;Jonathan Carney;R. Gonzalez;O. Fors;N. Galliher;A. Glazier;W. Howard;N. Law;R. Q
Astrophysical transients with rapid developments on subhour timescales are intrinsically rare. Due to their short durations, events like stellar superflares, optical flashes from gamma-ray bursts, and shock breakouts from young supernovae are difficult to identify on timescales that enable spectroscopic follow-up. This paper presents the Evryscope Fast Transient Engine (EFTE), a new data reduction pipeline that is designed to provide low-latency transient alerts from the Evryscopes—a north–south pair of ultra-wide-field telescopes with an instantaneous footprint covering 38% of the entire sky—and tools for building long-term light curves from Evryscope data. EFTE leverages the optical stability of the Evryscopes by using a simple direct image subtraction routine that is suited to continuously monitoring the transient sky at a cadence of a minute. Candidates are produced within the base Evryscope 2 minute cadence for 98.5% of images, and internally filtered using vetnet, a convolutional neural network real–bogus classifier. EFTE provides an extensible and robust architecture for transient surveys probing similar timescales, and serves as the software test bed for the real-time analysis pipelines and public data distribution systems for the Argus Array, a next-generation all-sky observatory with a data rate 62 times higher than that of Evryscope.