The Zwicky Transient Facility: System Overview, Performance, and First Results

Abstract

The Zwicky Transient Facility (ZTF) is a new optical time-domain survey that uses the Palomar 48 inch Schmidt telescope. A custom-built wide-field camera provides a 47 deg 2 field of view and 8 s readout time, yielding more than an order of magnitude improvement in survey speed relative to its predecessor survey, the Palomar Transient Factory. We describe the design and implementation of the camera and observing system. The ZTF data system at the Infrared Processing and Analysis Center provides near-real-time reduction to identify moving and varying objects. We outline the analysis pipelines, data products, and associated archive. Finally, we present on-sky performance analysis and first scientific results from commissioning and the early survey. ZTF's public alert stream will serve as a useful precursor for that of the Large Synoptic Survey Telescope.

Absorbed relativistic jets in radio-quiet narrow-line Seyfert 1 galaxies

“…Assuming its typical spectral index, α = −2.5, and extrapolating from the flux density measured at 37 GHz, the expected S ν at 9.0 GHz during the flare should be around 13 mJy. This value corresponds to a flux density increase of ∼ 400 times which, under typical conditions, should also be seen by optical transient surveys (e.g., Bellm et al 2019), assuming that the flare occurs throughout the whole electromagnetic spectrum. Therefore, the spectrum between 9 and 37 GHz may have a higher slope than that of synchrotron selfabsorption, and the high-frequency excess is not (entirely) due to a flaring state of the source.…”

Physical Parameters of Late-type Contact Binaries in the Northern Catalina Sky Survey

“…However, most previous studies dealing with large samples of CBs were limited to analyses of their light-curve morphology (e.g., periods and amplitudes), which is rather different from deriving the intrinsic properties of the stellar components. Moreover, future surveys using, e.g., the Zwicky Transient Facility (ZTF; Bellm et al 2019) and the Large Synoptic Survey Telescope (LSST; LSST Science Collaboration et al 2009) will likely result in enormous numbers of newly discovered CBs, thus posing a challenge to our ability to derive stellar parameters based on individual light-curve solutions.…”

Surveying the reach and maturity of machine learning and artificial intelligence in astronomy

“…The Large Synoptic Survey Telescope (Ivezi c et al, 2019;LSST Science Collaboration and LSST Project, 2009); the Euclid satellite (Amendola et al, 2013;Laureijs et al, 2011); MeerKAT (Booth, de Blok, Jonas, & Fanaroff, 2009); the Australian Square Kilometer Array Pathfinder (Johnston et al, 2007(Johnston et al, , 2008; and the Square Kilometer Array (Dewdney, Hall, Schilizzi, & Lazio, 2009), among others, will all generate datasets on scales (volumes and velocities) that vastly exceed the discovery capabilities of humans. In the interim, the SDDS (Abazajian et al, 2009;Stoughton et al, 2002;York et al, 2000), the Panoramaic Survey Telescope and Rapid Response System (Kaiser, 2004), the Catalina Real-Time Transient Survey (CRTS; Drake et al, 2009;Mahabal et al, 2011) and the Zwicky Transient Facility (ZTF; Bellm et al, 2019), the Kilo Degree Survey (KiDS; de Jong, Verdoes Kleijn, Kuijken, & Valentijn, 2013), and the Fornax Deep Survey (Iodice et al, 2016), both using the VLT Survey Telescope, 9 LOFAR (van Haarlem et al, 2013), the Solar Dynamic Observatory (SDO; Lemen et al, 2012;Pesnell, Thompson, & Chamberlin, 2012), the Kepler Planet-Detection Mission (Borucki et al, 2010), and the GAIA space mission (Gaia Collaboration, Gaia Collaboration, Prusti, et al, 2016;Gaia Collaboration et al, 2018), are generating data with which ML and AI has enabled classification, regression, forecasting, and discovery, leading to new knowledge and new insights.…”