We report on the results from the first six months of the Catalina Real-Time Transient Survey (CRTS). In order to search for optical transients (OTs) with timescales of minutes to years, the CRTS analyses data from the Catalina Sky Survey which repeatedly covers 26,000 of square degrees on the sky. The CRTS provides a public stream of transients that are bright enough to be followed up using small telescopes. Since the beginning of the survey, all CRTS transients have been made available to astronomers around the world in real time using HTML tables,RSS feeds, and VOEvents. As part of our public outreach program, the detections are now also available in Keyhole Markup Language through Google Sky. The initial discoveries include over 350 unique OTs rising more than 2 mag from past measurements. Sixty two of these are classified as supernovae (SNe), based on light curves, prior deep imaging and spectroscopic data. Seventy seven are due to cataclysmic variables (CVs; only 13 previously known), while an additional 100 transients were too infrequently sampled to distinguish between faint CVs and SNe. The remaining OTs include active galactic nucleus, blazars, high-proper-motions stars, highly variable stars (such as UV Ceti stars), and transients of an unknown nature. Our results suggest that there is a large population of SNe missed by many current SN surveys because of selection biases. These objects appear to be associated with faint host galaxies. We also discuss the unexpected discovery of white dwarf binary systems through dramatic eclipses.

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.

The Zwicky Transient Facility (ZTF) is a new robotic time-domain survey currently in progress using the Palomar 48-inch Schmidt Telescope. ZTF uses a 47 square degree field with a 600 megapixel camera to scan the entire northern visible sky at rates of ∼3760 square degrees/hour to median depths of g∼20.8 and r∼20.6 mag (AB, 5σ in 30 sec). We describe the Science Data System that is housed at IPAC, Caltech. This comprises the data-processing pipelines, alert production system, data archive, and user interfaces for accessing and analyzing the products. The real-time pipeline employs a novel image-differencing algorithm, optimized for the detection of point-source transient events. These events are vetted for reliability using a machine-learned classifier and combined with contextual information to generate data-rich alert packets. The packets become available for distribution typically within 13 minutes (95th percentile) of observation. Detected events are also linked to generate candidate moving-object tracks using a novel algorithm. Objects that move fast enough to streak in the individual exposures are also extracted and vetted. We present some preliminary results of the calibration performance delivered by the real-time pipeline. The reconstructed astrometric accuracy per science image with respect to Gaia DR1 is typically 45 to 85 milliarcsec. This is the RMS per-axis on the sky for sources extracted with photometric S/N10 and hence corresponds to the typical astrometric uncertainty down to this limit. The derived photometric precision (repeatability) at bright unsaturated fluxes varies between 8 and 25 millimag. The high end of these ranges corresponds to an airmass approaching ∼2-the limit of the public survey. Photometric calibration accuracy with respect to Pan-STARRS1 is generally better than 2%. The products support a broad range of scientific applications: fast and young supernovae; rare flux transients; variable stars; eclipsing binaries; variability from active galactic nuclei;

With the discovery of the first transiting extrasolar planetary system back in 1999, a great number of projects started to hunt for other similar systems. Because the incidence rate of such systems was unknown and the length of the shallow transit events is only a few percent of the orbital period, the goal was to monitor continuously as many stars as possible for at least a period of a few months. Small aperture, large field of view automated telescope systems have been installed with a parallel development of new data reduction and analysis methods, leading to better than 1% per data point precision for thousands of stars. With the successful launch of the photometric satellites CoRoT and Kepler, the precision increased further by one-two orders of magnitude. Millions of stars have been analyzed and searched for transits. In the history of variable star astronomy this is the biggest undertaking so far, resulting in photometric time series inventories immensely valuable for the whole field. In this review we briefly discuss the methods of data analysis that were inspired by the main science driver of these surveys and highlight some of the most interesting variable star results that impact the field of variable star astronomy.

We present a novel algorithm for scheduling the observations of time-domain imaging surveys. Our Integer Linear Programming approach optimizes an observing plan for an entire night by assigning targets to temporal blocks, enabling strict control of the number of exposures obtained per field and minimizing filter changes. A subsequent optimization step minimizes slew times between each observation. Our optimization metric selfconsistently weights contributions from time-varying airmass, seeing, and sky brightness to maximize the transient discovery rate. We describe the implementation of this algorithm on the surveys of the Zwicky Transient Facility and present its on-sky performance.