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The Asteroid Terrestrial impact Last Alert System (ATLAS) system consists of two 0.5 m 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 δ > − 50 ° ) every two nights, exposing four times per night, typically reaching o < 19 magnitude per exposure when the moon is illuminated and c < 19.5 magnitude 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.

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 catalog of 5 × 106 sources. This is the first of a series of articles describing ATLAS, 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 light curves.

In Smith et al. we published estimates of the volumetric rate of supernovae within 100 Mpc. These were incorrect and we present the correct values in this corrigendum.

In Smith et al. we published estimates of the volumetric rate of supernovae within 100 Mpc. These were incorrect and we present the correct values in this corrigendum.

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 catalog of 5 × 10⁶ sources. This is the first of a series of articles describing ATLAS, 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 light curves.

In the next generation surveys, the discovery of moving objects can be successful only if an observation strategy and the identification/orbit determination procedure are appropriate for the diverse apparent motions of the target sub-populations. The observations must accurately measure the displacement over a short interval of time; observations believed to belong to the same object have to be connected into tracklets. Information contained in tracklets is in most cases not sufficient to compute an orbit: two or more of them must be identified to provide an orbit. We have developed a method for recursive identification of tracklets allowing an unbiased orbit determination for all sub-populations and efficient enough to cope with the data flow expected from the next generation surveys. The success of the new algorithms can be easily measured only in a simulation, by consulting a posteriori some “ground truth”. We present here the results of a simulation of the orbit determination for one month of operations of the future Pan-STARRS survey, based upon a Solar System Model with a downsized population of Main Belt asteroids and a full size populations of Trojans, NEO, Centaurs, Comets and TNO. The results indicate that the method already developed and tested to find identifications of NEO and Main Belt asteroids are directly applicable to Trojans. The more distant objects often require modified algorithms, fitting orbits with only 4 parameters in a coordinate system specially adapted to handle very short arcs of observations. These orbits are mostly used as intermediate results, allowing to find full solutions as more tracklets are identified. When the number density of detections is as large as expected from the next generation surveys, both joining observations into tracklets and identifying tracklets can produce some false results. The only reliable way to remove them is a procedure of tracklet/identification management. It compares the tracklets and the identifications with a complex logic, allowing to discard almost all the false tracklets and all the false identifications. However, the distant objects still present a challenge for orbit determination: they require three tracklets in separate nights. If this requirement is met we have found no problem in achieving an unbiased orbit determination for all populations. Further work will lead to more advanced simulations, in particular by introducing a realistic model for astrometric and photometric errors.

Asteroid phase curves are used to derive fundamental physical properties through the determination of the absolute magnitude H. The upcoming visible Legacy Survey of Space and Time (LSST) and mid-infrared Near-Earth Object Surveillance Mission (NEOSM) surveys rely on these absolute magnitudes to derive the colours and albedos of millions of asteroids. Furthermore, the shape of the phase curves reflects their surface compositions, allowing for conclusions on their taxonomy. We derive asteroid phase curves from dual-band photometry acquired by the Asteroid Terrestrial-impact Last Alert System telescopes. Using Bayesian parameter inference, we retrieve the absolute magnitudes and slope parameters of 127,012 phase curves of 94,777 asteroids in the photometric \\(H, G_1, G_2\\)- and \\(H, G^*_{12}\\)-systems. The taxonomic complexes of asteroids separate in the observed \\(G_1, G_2\\)-distributions, correlating with their mean visual albedo. This allows for differentiating the X-complex into the P-, M-, and E-complexes using the slope parameters as alternative to albedo measurements. Further, taxonomic misclassifications from spectrophotometric datasets as well as interlopers in dynamical families of asteroids reveal themselves in \\(G_1, G_2\\)-space. The \\(H, G^*_{12}\\)-model applied to the serendipitous observations is unable to resolve target taxonomy. The \\(G_1, G_2\\) phase coefficients show wavelength-dependency for the majority of taxonomic complexes. Serendipitous asteroid observations allow for reliable phase curve determination for a large number of asteroids. To ensure that the acquired absolute magnitudes are suited for colour computations, it is imperative that future surveys densely cover the opposition effects of the phase curves, minimizing the uncertainty on H. The phase curve slope parameters offer an accessible dimension for taxonomic classification.

The Asteroid Terrestrial-impact Last Alert System (ATLAS) is an all-sky survey primarily aimed at detecting potentially hazardous near-Earth asteroids. Apart from the astrometry of asteroids, it also produces their photometric measurements that contain information about asteroid rotation and their shape. To increase the current number of asteroids with a known shape and spin state, we reconstructed asteroid models from ATLAS photometry that was available for approximately 180,000 asteroids observed between 2015 and 2018. We made use of the light-curve inversion method implemented in the Asteroid@home project to process ATLAS photometry for roughly 100,000 asteroids with more than a hundred individual brightness measurements. By scanning the period and pole parameter space, we selected those best-fit models that were, according to our setup, a unique solution for the inverse problem. We derived ~2750 unique models, 950 of them were already reconstructed from other data and published. The remaining 1800 models are new. About half of them are only partial models, with an unconstrained pole ecliptic longitude. Together with the shape and spin, we also determined for each modeled asteroid its color index from the cyan and orange filter used by the ATLAS survey. We also show the correlations between the color index, albedo, and slope of the phase-angle function. The current analysis is the first inversion of ATLAS asteroid photometry, and it is the first step in exploiting the huge scientific potential that ATLAS photometry has. ATLAS continues to observe, and in the future, this data, together with other independent photometric measurements, can be inverted to produce more refined asteroid models.

We present here the discovery of a new class of super-slow rotating asteroids (P>1000 hours) in data extracted from the Asteroid Terrestrial-impact Last Alert System (ATLAS) and Zwicky Transient Facility (ZTF) all-sky surveys. Of the 39 rotation periods we report here, 32 have periods longer than any previously reported unambiguous rotation periods currently in the Asteroid Light Curve Database. In our sample, 7 objects have a rotation period > 4000 hours and the longest period we report here is 4812 hours (~200 days). We do not observe any correlation between taxonomy, albedo, or orbital properties with super-slow rotating status. The most plausible mechanism for the creation of these very slow rotators is if their rotations were slowed by YORP spin-down. Super-slow rotating asteroids may be common, with at least 0.4% of the main-belt asteroid population with a size range between 2 and 20 km in diameter rotating with periods longer than 1000 hours.

We present here the c-o colors for identified Flora, Vesta, Nysa-Polana, Themis, and Koronis family members within the historic data set (2015-2018) of the Asteroid Terrestrial-impact Last Alert System (ATLAS). The Themis and Koronis families are known to be relatively pure C- and S-type Bus-DeMeo taxonomic families, respectively, and the extracted color data from the ATLAS broadband c- and o-filters of these two families is used to demonstrate that the ATLAS c-o color is a sufficient parameter to distinguish between the C- and S-type taxonomies. The Vesta and Nysa-Polana families are known to display a mixture of taxonomies possibly due to Vesta's differentiated parent body origin and Nysa-Polana actually consisting of two nested families with differing taxonomies. Our data show that the Flora family also displays a large degree of taxonomic mixing and the data reveal a substantial H-magnitude dependence on color. We propose and exclude several interpretations for the observed taxonomic mix. Additionally, we extract rotation periods of all of the targets reported here and find good agreement with targets that have previously reported periods.