Search

We estimate the total population of near-Earth objects (NEOs) in the Solar System, using an extensive, `Solar System to pixels' fake-asteroid simulation to debias detections of real NEOs by the ATLAS survey. Down to absolute magnitudes $H=25$ and 27.6 (diameters of $\sim 34$ and 10 meters, respectively, for 15% albedo), we find total populations of $(3.72 \pm 0.49) \times 10^5$ and $(1.59 \pm 0.45) \times 10^7$ NEOs, respectively. Most plausible sources of error tend toward underestimation, so the true populations are likely larger. We find the distribution of $H$ magnitudes steepens for NEOs fainter than $H \sim 22.5$, making small asteroids more common than extrapolation from brighter $H$ mags would predict. Our simulation indicates a strong bias against detecting small but dangerous asteroids that encounter Earth with high relative velocities -- i.e., asteroids in highly inclined and/or eccentric orbits. Worldwide NEO discovery statistics indicate this bias affects global NEO detection capability, to the point that an observational census of small asteroids in such orbits is probably not currently feasible. Prompt and aggressive followup of NEO candidates, combined with closer collaborations between segments of the global NEO community, can increase detection rates for these dangerous objects., Comment: 23 pages, 11 figures, accepted by the Planetary Science Journal

Jupiter has nearly 8000~known co-orbital asteroids orbiting in the L4 and L5 Lagrange points called Jupiter Trojan asteroids. Aside from the greater number density of the L4 cloud the two clouds are in many ways considered to be identical. Using sparse photometric data taken by the Asteroid Terrestrial-impact Last Alert System (ATLAS) for 863 L4 Trojans and 380 L5 Trojans we derive the shape distribution for each of the clouds and find that, on average, the L4 asteroids are more elongated than the L5 asteroids. This shape difference is most likely due to the greater collision rate in the L4 cloud that results from its larger population. We additionally present the phase functions and $c-o$ colours of 266~objects., 22 pages, 9 figures, 2 tables. Accepted by PSJ

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.

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 $��> -50^{\circ}$) 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., 27 pages, 12 figures. Accepted for publication in PASP on 2020 May 15

SN 2017dio shows both spectral characteristics of a type-Ic supernova (SN) and signs of a hydrogen-rich circumstellar medium (CSM). Prominent, narrow emission lines of H and He are superposed on the continuum. Subsequent evolution revealed that the SN ejecta are interacting with the CSM. The initial SN Ic identification was confirmed by removing the CSM interaction component from the spectrum and comparing with known SNe Ic, and reversely, adding a CSM interaction component to the spectra of known SNe Ic and comparing them to SN 2017dio. Excellent agreement was obtained with both procedures, reinforcing the SN Ic classification. The light curve constrains the pre-interaction SN Ic peak absolute magnitude to be around $M_g = -17.6$ mag. No evidence of significant extinction is found, ruling out a brighter luminosity required by a SN Ia classification. These pieces of evidence support the view that SN 2017dio is a SN Ic, and therefore the first firm case of a SN Ic with signatures of hydrogen-rich CSM in the early spectrum. The CSM is unlikely to have been shaped by steady-state stellar winds. The mass loss of the progenitor star must have been intense, $\dot{M} \sim 0.02$ $(\epsilon_{H\alpha}/0.01)^{-1}$ $(v_\textrm{wind}/500$ km s$^{-1}$) $(v_\textrm{shock}/10 000$ km s$^{-1})^{-3}$ $M_\odot$~yr$^{-1}$, peaking at a few decades before the SN. Such a high mass loss rate might have been experienced by the progenitor through eruptions or binary stripping., Comment: ApJL, 11 pages, 5 figures (accepted 22 Jan 2018)

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, 22 pages, 6 figures, ApJ in press

The Asteroid Terrestrial-impact Last Alert System (ATLAS) carries out its primary planetary defense mission by surveying about 13000 deg^2 at least four times per night. The resulting data set is useful for the discovery of variable stars to a magnitude limit fainter than r~18, with amplitudes down to 0.01 mag for bright objects. Here we present a Data Release One catalog of variable stars based on analyzing 142 million stars measured at least 100 times in the first two years of ATLAS operations. Using a Lomb-Scargle periodogram and other variability metrics, we identify 4.7 million candidate variables which we analyze in detail. Through Space Telescope Science Institute, we publicly release lightcurves for all of them, together with a vector of 169 classification features for each star. We do this at the level of unconfirmed candidate variables in order to provide the community with a large set of homogeneously analyzed photometry and avoid pre-judging which types of objects others may find most interesting. We use machine learning to classify the candidates into fifteen different broad categories based on lightcurve morphology. About 10% (430,000 stars) pass extensive tests designed to screen out spurious variability detections: we label these as `probable' variables. Of these, 230,000 receive specific classifications as eclipsing binaries, pulsating, Mira-type, or sinusoidal variables: these are the `classified' variables. New discoveries among the probable variables number more than 300,000, while 150,000 of the classified variables are new, including about 10,000 pulsating variables, 2,000 Mira stars, and 70,000 eclipsing binaries., Accepted by AJ; gives instructions for querying ATLAS variable star database; this new version has nicer lightcurve figures