We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the solar system, exploring the transient optical sky, and mapping the Milky Way. LSST will be a large, wide-field ground-based system designed to obtain repeated images covering the sky visible from Cerro Pachón in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg 2 field of view, a 3.2-gigapixel camera, and six filters (ugrizy) covering the wavelength range 320-1050 nm. The project is in the construction phase and will begin regular survey operations by 2022. About 90% of the observing time will be devoted to a deep-wide-fast survey mode that will uniformly observe a 18,000 deg 2 region about 800 times (summed over all six bands) during the anticipated 10 yr of operations and will yield a co-added map to r∼27.5. These data will result in databases including about 32 trillion observations of 20 billion galaxies and a similar number of stars, and they will serve the majority of the primary science programs. The remaining 10% of the observing time will be allocated to special projects such as Very Deep and Very Fast time domain surveys, whose details are currently under discussion. We illustrate how the LSST science drivers led to these choices of system parameters, and we describe the expected data products and their characteristics.

We report on g, r and i band observations of the Interstellar Object 1I/'Oumuamua (1I) taken on 2017 October 29 from 04:28 to 08:40 UTC by the Apache Point Observatory (APO) 3.5m telescope's ARCTIC camera. We find that 1I's colors are g − r = 0.41 ± 0.24 and r − i = 0.23 ± 0.25, consistent with visible spectra (Masiero 2017; Ye et al. 2017;Fitzsimmons et al. 2017) and most comparable to the population of Solar System C/D asteroids, Trojans, or comets. We find no evidence of any cometary activity at a heliocentric distance of 1.46 au, approximately 1.5 months after 1I's closest approach distance to the Sun. Significant brightness variability was seen in the r observations, with the object becoming notably brighter towards the end of the run. By combining our APO photometric time series data with the Discovery Channel Telescope (DCT) data of Knight et al. (2017), taken 20 h later on 2017 October 30, we construct an almost complete lightcurve with a most probable single-peaked lightcurve period of P 4 h. Our results imply a double peaked rotation period of 8.1 ± 0.02 h, with a peak-to-trough amplitude of 1.5 -2.1 mags. Assuming that 1I's shape can be approximated by an ellipsoid, the amplitude constraint implies that 1I has an axial ratio of 3.5 to 10.3, which is strikingly elongated. Assuming that 1I is rotating above its critical break up limit, our results are compatible with 1I having modest cohesive strength and may have obtained its elongated shape during a tidal distortion event before being ejected from its home system.

Using the most recent prototypes, design, and as-built system information, we test and quantify the capability of the Large Synoptic Survey Telescope (LSST) to discover Potentially Hazardous Asteroids (PHAs) and Near-Earth Objects (NEOs). We empirically estimate an expected upper limit to the false detection rate in LSST image differencing, using measurements on DECam data and prototype LSST software and find it to be about 450 deg −2 . We show that this rate is already tractable with current prototype of the LSST Moving Object Processing System (MOPS) by processing a 30-day simulation consistent with measured false detection rates. We proceed to evaluate the performance of the LSST baseline survey strategy for PHAs and NEOs using a high-fidelity simulated survey pointing history. We find that LSST alone, using its baseline survey strategy, will detect 66% of the PHA and 61% of the NEO population objects brighter than H = 22, with the uncertainty in the estimate of ±5 percentage points. By generating and examining variations on the baseline survey strategy, we show it is possible to further improve the discovery yields. In particular, we find that extending the LSST survey by two additional years and doubling the MOPS search window increases the completeness for PHAs to 86% (including those discovered by contemporaneous surveys) without jeopardizing other LSST science goals (77% for NEOs). This equates to reducing the undiscovered population of PHAs by additional 26% (15% for NEOs), relative to the baseline survey.-3the Ecliptic, at the faint fluxes probed by LSST, is a few arcminutes (object counts are dominated by main-belt asteroids). Typical asteroid motion during several days is larger (of the order a degree or more) and thus, without additional information, detections of individual objects are "scrambled". However, with two detections per night, the motion vector can be estimated. The motion vector makes the linking problem much easier because positions from one night can be approximately extrapolated to future (or past) nights. The predicted position's uncertainty is typically of the order of several arcminutes, rather than a degree, which effectively "de-scrambles" detections from different nights (for a detailed discussion of this algorithm, see Kubica et al. 2007 as well as Appendix A for a theoretical derivation of expected scalings).Early simulations of LSST performance presented by Ivezić et al. (2007) showed that the 10-year baseline cadence would result in 75% completeness for PHAs greater than 140 m (more precisely, for PHAs with H < 22). They also suggested that with additional optimizations of the observing cadence, LSST could achieve 90% completeness. An example of such an optimization was discussed by Ivezić et al. (2008) who reported that, to reach 90% completeness, about 15% of observing time would have to be dedicated to NEOs, and the survey would have to run for 12 years. More recently, estimates of LSST yields have been revisited by Grav et al. (2016) (predicted PHA completeness of 62% fo...

We introduce a new computational technique for searching for faint moving sources in astronomical images. Starting from a maximum likelihood estimate for the probability of the detection of a source within a series of images, we develop a massively parallel algorithm for searching through candidate asteroid trajectories that utilizes Graphics Processing Units (GPU). This technique can search over 10 10 possible asteroid trajectories in stacks of the order 10-15 4K x 4K images in under a minute using a single consumer grade GPU. We apply this algorithm to data from the 2015 campaign of the High Cadence Transient Survey (HiTS) obtained with the Dark Energy Camera (DECam). We find 39 previously unknown Kuiper Belt Objects in the 150 square degrees of the survey. Comparing these asteroids to an existing model for the inclination distribution of the Kuiper Belt we demonstrate that we recover a KBO population above our detection limit consistent with previous studies. Software used in this analysis is made available as an open source package.

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