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We present the Spectroscopic Classification of Astronomical Transients (SCAT) survey, which is dedicated to spectrophotometric observations of transient objects such as supernovae and tidal disruption events. SCAT uses the SuperNova Integral-Field Spectrograph (SNIFS) on the University of Hawai'i 2.2-meter (UH2.2m) telescope. SNIFS was designed specifically for accurate transient spectrophotometry, including absolute flux calibration and host-galaxy removal. We describe the data reduction and calibration pipeline including spectral extraction, telluric correction, atmospheric characterization, nightly photometricity, and spectrophotometric precision. We achieve $\lesssim 5\%$ spectrophotometry across the full optical wavelength range ($3500-9000~\r{A}$) under photometric conditions. The inclusion of photometry from the SNIFS multi-filter mosaic imager allows for decent spectrophotometric calibration ($10-20\%$) even under unfavorable weather/atmospheric conditions. SCAT obtained $\approx 640$ spectra of transients over the first 3 years of operations, including supernovae of all types, active galactic nuclei, cataclysmic variables, and rare transients such as superluminous supernovae and tidal disruption events. These observations will provide the community with benchmark spectrophotometry to constrain the next generation of hydrodynamic and radiative transfer models., Comment: 12 pages, 9 figures, 2 tables. Accepted for publication in to PASP

The Asteroid Terrestrial impact Last Alert System (ATLAS) system consists of two 0.5m Schmidt telescopes with cameras covering 29 square degrees at plate scale of 1.86 arcsec per pixel. Working in tandem, the telescopes routinely survey the whole sky visible from Hawaii (above $\delta > -50^{\circ}$) every two nights, exposing four times per night, typically reaching $o < 19$ magnitude per exposure when the moon is illuminated and $c < 19.5$ per exposure in dark skies. Construction is underway of two further units to be sited in Chile and South Africa which will result in an all-sky daily cadence from 2021. Initially designed for detecting potentially hazardous near earth objects, the ATLAS data enable a range of astrophysical time domain science. To extract transients from the data stream requires a computing system to process the data, assimilate detections in time and space and associate them with known astrophysical sources. Here we describe the hardware and software infrastructure to produce a stream of clean, real, astrophysical transients in real time. This involves machine learning and boosted decision tree algorithms to identify extragalactic and Galactic transients. Typically we detect 10-15 supernova candidates per night which we immediately announce publicly. The ATLAS discoveries not only enable rapid follow-up of interesting sources but will provide complete statistical samples within the local volume of 100 Mpc. A simple comparison of the detected supernova rate within 100 Mpc, with no corrections for completeness, is already significantly higher (factor 1.5 to 2) than the current accepted rates., Comment: 27 pages, 12 figures. Accepted for publication in PASP on 2020 May 15

The Asteroid Terrestrial-impact Last Alert System (ATLAS) observes most of the sky every night in search of dangerous asteroids. Its data are also used to search for photometric variability, where sensitivity to variability is limited by photometric accuracy. Since each exposure spans 7.6 deg corner to corner, variations in atmospheric transparency in excess of 0.01 mag are common, and 0.01 mag photometry cannot be achieved by using a constant flat field calibration image. We therefore have assembled an all-sky reference catalog of approximately one billion stars to m~19 from a variety of sources to calibrate each exposure's astrometry and photometry. Gaia DR2 is the source of astrometry for this ATLAS Refcat2. The sources of g, r, i, z photometry include Pan-STARRS DR1, the ATLAS Pathfinder photometry project, ATLAS re-flattened APASS data, SkyMapper DR1, APASS DR9, the Tycho-2 catalog, and the Yale Bright Star Catalog. We have attempted to make this catalog at least 99% complete to m<19, including the brightest stars in the sky. We believe that the systematic errors are no larger than 5 millimag RMS, although errors are as large as 20 millimag in small patches near the galactic plane., Comment: 22 pages, 6 figures, ApJ in press

Technology has advanced to the point that it is possible to image the entire sky every night and process the data in real time. The sky is hardly static: many interesting phenomena occur, including variable stationary objects such as stars or QSOs, transient stationary objects such as supernovae or M dwarf flares, and moving objects such as asteroids and the stars themselves. Funded by NASA, we have designed and built a sky survey system for the purpose of finding dangerous near-Earth asteroids (NEAs). This system, the "Asteroid Terrestrial-impact Last Alert System" (ATLAS), has been optimized to produce the best survey capability per unit cost, and therefore is an efficient and competitive system for finding potentially hazardous asteroids (PHAs) but also for tracking variables and finding transients. While carrying out its NASA mission, ATLAS now discovers more bright ($m < 19$) supernovae candidates than any ground based survey, frequently detecting very young explosions due to its 2 day cadence. ATLAS discovered the afterglow of a gamma-ray burst independent of the high energy trigger and has released a variable star catalogue of 5$\times10^{6}$ sources. This, the first of a series of articles describing ATLAS, is devoted to the design and performance of the ATLAS system. Subsequent articles will describe in more detail the software, the survey strategy, ATLAS-derived NEA population statistics, transient detections, and the first data release of variable stars and transient lightcurves., Comment: 26 pages, 12 figures, submitted to PASP

Thick back-illuminated deep-depletion CCDs have superior quantum efficiency over previous generations of thinned and traditional thick CCDs. As a result, they are being used for wide-field imaging cameras in several major projects. We use observations from the Pan-STARRS $3\pi$ survey to characterize the behavior of the deep-depletion devices used in the Pan-STARRS1 Gigapixel Camera. We have identified systematic spatial variations in the photometric measurements and stellar profiles which are similar in pattern to the so-called "tree rings" identified in devices used by other wide-field cameras (e.g., DECam and Hypersuprime Camera). The tree-ring features identified in these other cameras result from lateral electric fields which displace the electrons as they are transported in the silicon to the pixel location. In contrast, we show that the photometric and morphological modifications observed in the GPC1 detectors are caused by variations in the vertical charge transportation rate and resulting charge diffusion variations., Comment: submitted to PASP

Pan-STARRS1 has carried out a set of distinct synoptic imaging sky surveys including the $3\pi$ Steradian Survey and the Medium Deep Survey in 5 bands ($grizy_{P1}$). The mean 5$\sigma$ point source limiting sensitivities in the stacked 3$\pi$ Steradian Survey in $grizy_{P1}$ are (23.3, 23.2, 23.1, 22.3, 21.4) respectively. The upper bound on the systematic uncertainty in the photometric calibration across the sky is 7-12 millimag depending on the bandpass. The systematic uncertainty of the astrometric calibration using the Gaia frame comes from a comparison of the results with Gaia: the standard deviation of the mean and median residuals ($ \Delta ra, \Delta dec $) are (2.3, 1.7) milliarcsec, and (3.1, 4.8) milliarcsec respectively. The Pan-STARRS system and the design of the PS1 surveys are described and an overview of the resulting image and catalog data products and their basic characteristics are described together with a summary of important results. The images, reduced data products, and derived data products from the Pan-STARRS1 surveys are available to the community from the Mikulski Archive for Space Telescopes (MAST) at STScI., Comment: 38 pages, 29 figures, 12 tables

This paper describes the organization of the database and the catalog data products from the Pan-STARRS1 $3\pi$ Steradian Survey. The catalog data products are available in the form of an SQL-based relational database from MAST, the Mikulski Archive for Space Telescopes at STScI. The database is described in detail, including the construction of the database, the provenance of the data, the schema, and how the database tables are related. Examples of queries for a range of science goals are included. The catalog data products are available in the form of an SQL-based relational database from MAST, the Mikulski Archive for Space Telescopes at STScI., Comment: 63 pages, 59 tables, 16 figures

We present the details of the photometric and astrometric calibration of the Pan-STARRS1 $3\pi$ Survey. The photometric goals were to reduce the systematic effects introduced by the camera and detectors, and to place all of the observations onto a photometric system with consistent zero points over the entire area surveyed, the ~30,000 square degrees north of $\delta$ = -30 degrees. The astrometric calibration compensates for similar systematic effects so that positions, proper motions, and parallaxes are reliable as well. The Pan-STARRS Data Release 2 (DR2) astrometry is tied to the Gaia DR1 release., Comment: Pan-STARRS Public Data Release 2 : Paper V

The Pan-STARRS1 Science Consortium have carried out a set of imaging surveys using the 1.4 giga-pixel GPC1 camera on the PS1 telescope. As this camera is composed of many individual electronic readouts, and covers a very large field of view, great care was taken to ensure that the many instrumental effects were corrected to produce the most uniform detector response possible. We present the image detrending steps used as part of the processing of the data contained within the public release of the Pan-STARRS1 Data Release 1 (DR1). In addition to the single image processing, the methods used to transform the 375,573 individual exposures into a common sky-oriented grid are discussed, as well as those used to produce both the image stack and difference combination products., Comment: 21 pages, 21 figures, Paper III of Pan-STARRS DR1 public data release documentation

We describe development and application of a Global Astrometric Solution (GAS) to the problem of Pan-STARRS1 (PS1) astrometry. Current PS1 astrometry is based on differential astrometric measurements using 2MASS reference stars, thus PS1 astrometry inherits the errors of the 2MASS catalog. The GAS, based on a single, least squares adjustment to approximately 750k grid stars using over 3000 extragalactic objects as reference objects, avoids this catalog-to-catalog propagation of errors to a great extent. The GAS uses a relatively small number of Quasi-Stellar Objects (QSOs, or distant AGN) with very accurate (<1 mas) radio positions, referenced to the ICRF2. These QSOs provide a hard constraint in the global least squares adjustment. Solving such a system provides absolute astrometry for all the stars simultaneously. The concept is much cleaner than conventional astrometry but is not easy to perform for large catalogs. In this paper we describe our method and its application to Pan-STARRS1 data. We show that large-scale systematic errors are easily corrected but our solution residuals for position (~60 mas) are still larger than expected based on simulations (~10 mas). We provide a likely explanation for the reason the small-scale residual errors are not corrected in our solution as would be expected., Comment: 39 pages, 19 figures, accepted by AJ

Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of ~32000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20x20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25% of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1%, the classifier initially suggests a missed detection rate of around 10%. However we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6%., Comment: 17 pages, 16 figures, accepted for publication in MNRAS

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SV) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g,r,i, and z. We use three deterministic light-curve models to fit burst-like transients and one stochastic light curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGN). We assess the quality of fit of the models band-wise source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications. We use our clustering method to characterize 4361 extragalactic image difference detected sources in the first 2.5 years of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGN, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 active galactic nuclei and 812 supernovae. We use these samples to identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys., Comment: Accepted for publication in ApJ

We measure quasar variability using the Panoramic Survey Telescope and Rapid Response System 1 Survey (Pan-STARRS1 or PS1) and the Sloan Digital Sky Survey (SDSS) and establish a method of selecting quasars via their variability in 10,000 square degree surveys. We use 100,000 spectroscopically confirmed quasars that have been well measured in both PS1 and SDSS and take advantage of the decadal time scales that separate SDSS measurements and PS1 measurements. A power law model fits the data well over the entire time range tested, 0.01 to 10 years. Variability in the current PS1-SDSS dataset can efficiently distinguish between quasars and non-varying objects. It improves the purity of a griz quasar color cut from 4.1% to 48% while maintaining 67% completeness. Variability will be very effective at finding quasars in datasets with no u band and in redshift ranges where exclusively photometric selection is not efficient. We show that quasars' rest-frame ensemble variability, measured as a root mean squared in delta magnitudes, is consistent with V(z, L, t) = A0 (1+z)^0.37 (L/L0)^-0.16 (t/1yr)^0.246 , where L0 = 10^46 ergs^-1 and A0 = 0.190, 0.162, 0.147 or 0.141 in the gP1 , rP1 , iP1 or zP1 filter, respectively. We also fit across all four filters and obtain median variability as a function of z, L and lambda as V(z, L, lambda, t) = 0.079(1 + z)^0.15 (L/L0 )^-0.2 (lambda/1000 nm)^-0.44 (t/1yr)^0.246 .

As of 2012 Jan 21, the Pan-STARRS 1 3\pi Survey has observed the 3/4 of the sky visible from Hawaii with a minimum of 2 and mean of 7.6 observations in 5 filters, g_p1, r_p1, i_p1, z_p1, y_p1. Now at the end of the second year of the mission, we are in a position to make an initial public release of a portion of this unprecedented dataset. This article describes the PS1 Photometric Ladder, Release 12.01 This is the first of a series of data releases to be generated as the survey coverage increases and the data analysis improves. The Photometric Ladder has rungs every hour in RA and at 4 intervals in declination. We will release updates with increased area coverage (more rungs) from the latest dataset until the PS1 survey and the final re-reduction are completed. The currently released catalog presents photometry of \approx 1000 objects per square degree in the rungs of the ladder. Saturation occurs at g_p1, r_p1, i_p1 \approx 13.5; z_p1 \approx 13.0; and y_p1 \approx 12.0. Photometry is provided for stars down to g_p1, r_p1, i_p1 \approx 19.1 in the AB system. This data release depends on the rigid `Ubercal' photometric calibration using only the photometric nights, with systematic uncertainties of (8.0, 7.0, 9.0, 10.7, 12.4) millimags in (g_p1, r_p1, i_p1, z_p1, y_p1). Areas covered only with lower quality nights are also included, and have been tied to the Ubercal solution via relative photometry; photometric accuracy of the non-photometric regions is lower and should be used with caution., Comment: 14 pages, 8 figures, download data from http://ipp.ifa.hawaii.edu, accepted for publication in ApJ Supplements 2013.03.08

The Pan-STARRS1 survey is collecting multi-epoch, multi-color observations of the sky north of declination -30 deg to unprecedented depths. These data are being photometrically and astrometrically calibrated and will serve as a reference for many other purposes. In this paper we present our determination of the Pan-STARRS photometric system: gp1, rp1, ip1, zp1, yp1, and wp1. The Pan-STARRS photometric system is fundamentally based on the HST Calspec spectrophotometric observations, which in turn are fundamentally based on models of white dwarf atmospheres. We define the Pan-STARRS magnitude system, and describe in detail our measurement of the system passbands, including both the instrumental sensitivity and atmospheric transmission functions. Byproducts, including transformations to other photometric systems, galactic extinction, and stellar locus are also provided. We close with a discussion of remaining systematic errors., Comment: 39 pages, 9 figures, machine readable table of bandpasses, accepted for publication in ApJ

We present a precise photometric calibration of the first 1.5 years of science imaging from the Pan-STARRS1 survey (PS1), an ongoing optical survey of the entire sky north of declination -30 degrees in five bands. Building on the techniques employed by Padmanabhan et al. (2008) in the Sloan Digital Sky Survey (SDSS), we use repeat PS1 observations of stars to perform the relative calibration of PS1 in each of its five bands, solving simultaneously for the system throughput, the atmospheric transparency, and the large-scale detector flat field. Both internal consistency tests and comparison against the SDSS indicate that we achieve relative precision of <10 mmag in g, r, and i_P1, and ~10 mmag in z and y_P1. The spatial structure of the differences with the SDSS indicates that errors in both the PS1 and SDSS photometric calibration contribute similarly to the differences. The analysis suggests that both the PS1 system and the Haleakala site will enable <1% photometry over much of the sky., Comment: 16 pages, 9 figures (arxiv version updated to published version)

Large photometric surveys of transient phenomena, such as Pan-STARRS and LSST, will locate thousands to millions of type Ia supernova candidates per year, a rate prohibitive for acquiring spectroscopy to determine each candidate's type and redshift. In response, we have developed an economical approach to identifying SNe Ia and their redshifts using an uncommon type of optical filter which has multiple, discontinuous passbands on a single substrate. Observation of a supernova through a specially designed pair of these `cross-correlation filters' measures the approximate amplitude and phase of the cross-correlation between the spectrum and a SN Ia template, a quantity typically used to determine the redshift and type of a high-redshift SN Ia. Simulating the use of these filters, we obtain a sample of SNe Ia which is ~98% pure with individual redshifts measured to 0.01 precision. The advantages of this approach over standard broadband photometric methods are that it is insensitive to reddening, independent of the color data used for subsequent distance determinations which reduces selection or interpretation bias, and because it makes use of the spectral features its reliability is greater. A great advantage over long-slit spectroscopy comes from increased throughput, enhanced multiplexing and reduced set-up time resulting in a net gain in speed of up to ~30 times. This approach is also insensitive to host galaxy contamination. Prototype filters were built and successfully used on Magellan with LDSS-3 to characterize three SNLS candidates. We discuss how these filters can provide critical information for the upcoming photometric supernova surveys., Comment: Accepted for The Astrophysical Journal. 30 pages, 19 figures

Wide-angle surveys have been an engine for new discoveries throughout the modern history of astronomy, and have been among the most highly cited and scientifically productive observing facilities in recent years. This trend is likely to continue over the next decade, as many of the most important questions in astrophysics are best tackled with massive surveys, often in synergy with each other and in tandem with the more traditional observatories. We argue that these surveys are most productive and have the greatest impact when the data from the surveys are made public in a timely manner. The rise of the "survey astronomer" is a substantial change in the demographics of our field; one of the most important challenges of the next decade is to find ways to recognize the intellectual contributions of those who work on the infrastructure of surveys (hardware, software, survey planning and operations, and databases/data distribution), and to make career paths to allow them to thrive., Comment: ASTRO2010 decadal survey state of the profession position paper