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None of the approximately 750,000 known asteroids and comets in the Solar System is thought to have originated outside it, despite models of the formation of planetary systems suggesting that orbital migration of giant planets ejects a large fraction of the original planetesimals into interstellar space. The high predicted number density of icy interstellar objects (2.4 × 10−4per cubic astronomical unit) suggests that some should have been detected, yet hitherto none has been seen. Many decades of asteroid and comet characterization have yielded formation models that explain the mass distribution, chemical abundances and planetary configuration of the Solar System today, but there has been no way of telling whether the Solar System is typical of planetary systems. Here we report observations and analysis of the object 1I/2017 U1 (‘Oumuamua) that demonstrate its extrasolar trajectory, and that thus enable comparisons to be made between material from another planetary system and from our own. Our observations during the brief visit by the object to the inner Solar System reveal it to be asteroidal, with no hint of cometary activity despite an approach within 0.25 astronomical units of the Sun. Spectroscopic measurements show that the surface of the object is spectrally red, consistent with comets or organic-rich asteroids that reside within the Solar System. Light-curve observations indicate that the object has an extremely oblong shape, with a length about ten times its width, and a mean radius of about 102 metres assuming an albedo of 0.04. No known objects in the Solar System have such extreme dimensions. The presence of ‘Oumuamua in the Solar System suggests that previous estimates of the number density of interstellar objects, based on the assumption that all such objects were cometary, were pessimistically low. Planned upgrades to contemporary asteroid survey instruments and improved data processing techniques are likely to result in the detection of more interstellar objects in the coming years.

Most near-Earth objects came from the asteroid belt and drifted via non-gravitational thermal forces into resonant escape routes that, in turn, pushed them onto planet-crossing orbits. Models predict that numerous asteroids should be found on orbits that closely approach the Sun, but few have been seen. In addition, even though the near-Earth-object population in general is an even mix of low-albedo (less than ten per cent of incident radiation is reflected) and high-albedo (more than ten per cent of incident radiation is reflected) asteroids, the characterized asteroids near the Sun typically have high albedos. Here we report a quantitative comparison of actual asteroid detections and a near-Earth-object model (which accounts for observational selection effects). We conclude that the deficit of low-albedo objects near the Sun arises from the super-catastrophic breakup (that is, almost complete disintegration) of a substantial fraction of asteroids when they achieve perihelion distances of a few tens of solar radii. The distance at which destruction occurs is greater for smaller asteroids, and their temperatures during perihelion passages are too low for evaporation to explain their disappearance. Although both bright and dark (high- and low-albedo) asteroids eventually break up, we find that low-albedo asteroids are more likely to be destroyed farther from the Sun, which explains the apparent excess of high-albedo near-Earth objects and suggests that low-albedo asteroids break up more easily as a result of thermal effects.

We study the time evolution of the impact probability for synthetic, but realistic, impacting and close-approaching asteroids detected in a simulated all-sky survey. We use the impact probability to calculate the impact warning time (tw) as the time interval between when an object reaches a Palermo Scale value of -2 and when it impacts Earth. A simple argument shows that tw? Dx, with the exponent in the range [1.0,1.5], and our derived value was x= 1.3 ± 0.1. The low-precision astrometry from the single simulated all-sky survey could require many days or weeks to establish an imminent impact for asteroids larger than 100 m in diameter that are discovered far from Earth. Most close-approaching asteroids are quickly identified as not being impactors, but a size-dependent percentage, even for those larger than 50 m diameter, have a persistent impact probability of greater than 10-6on the day of closest approach. Thus, a single all-sky survey can be of tremendous value in identifying Earth-impacting and close-approaching asteroids in advance of their closest approach, but it can not solve the problem on its own: high-precision astrometry from other optical or radar systems is necessary to rapidly establish an object as an impactor or close approacher. We show that the parallax afforded by surveying the sky from two sites is only of benefit for a small fraction of the smallest objects detected within a couple days before impact: probably not enough to justify the increased operating costs of a two-site survey. Finally, the survey cadence within a fixed time span is relatively unimportant to the impact probability calculation. We tested three different reasonable cadences and found that one provided ?10 times higher (better) value for the impact probability on the discovery night for the smallest (10 m diameter) objects, but the consequences on the overall impact probability calculation are negligible.

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves >99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a nonphysical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss, and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains highly efficient at detecting objects but drops to 80% efficiency at producing orbits. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.

Asteroid detections in astronomical images may appear as trails due to a combination of their apparent rate of motion and exposure duration. Nearby asteroids in particular typically have high apparent rates of motion and acceleration. Their recovery, especially on their discovery apparition, depends upon obtaining good astrometry from the trailed detections. We present an analytic function describing a trailed detection under the assumption of a Gaussian point spread function (PSF) and constant rate of motion. We have fit the function to both synthetic and real trailed asteroid detections from the Pan-STARRS1 survey telescope to obtain accurate astrometry and photometry. For short trails our trailing function yields the same astrometric and photometry accuracy as a functionally simpler two-dimensional Gaussian but the latter underestimates the length of the trail-a parameter that can be important for measuring the object's rate of motion and assessing its cometary activity. For trails longer than about 10 pixels (?3× PSF) our trail fitting provides ?3× better astrometric accuracy and up to two magnitudes improvement in the photometry. The trail fitting algorithm can be implemented at the source detection level for alldetections to provide trail length and position angle that can be used to reduce the false tracklet rate.

We present here the Pan-STARRS Moving Object Processing System (MOPS) Synthetic Solar System Model (S3M), the first-ever attempt at building a comprehensive flux-limited model of the major small-body populations in the solar system. The goal of the S3M is to provide a valuable tool in the design and testing of the MOPS software, and will be used in the monitoring of the upcoming Pan-STARRS 1 all-sky survey, which started science operations during late spring of 2010. The model is composed of synthetic populations of near-Earth objects (NEOs with a subpopulation of Earth impactors), the main-belt asteroids (MBAs), Jovian Trojans, Centaurs, trans-Neptunian objects (classical, resonant, and scattered trans-Neptunian objects [TNOs]), Jupiter-family comets (JFCs), long-period comets (LPCs), and interstellar comets. The model reasonably reproduces the true populations to a minimum of V= 24.5, corresponding to approximately the expected limiting magnitude for Pan-STARRS's ability to detect moving objects. The NEO synthetic population has been extended to H< 25 (corresponding to objects of about 50 m in diameter), allowing for close flybys of the Earth to be modeled.

We present simulations on the asteroid photometric data that will be provided by the Pan-STARRS (Panoramic Survey Telescope and Rapid Response System). The simulations were performed using realistic shape and light-scattering models, random orientation of spin axes, and rotation periods in the range 2–24 h. We show that physical models of asteroids can be reconstructed from this data with some limitations (possible multiple pole solutions). We emphasize the potential of sparse photometric data to produce models of a large number of asteroids within the next decade and we outline further tests with fast and slow rotators, tumblers, and binary asteroids.

Numerical models of the collisional evolution of the main-belt asteroids lead to a new interpretation of the shape of the observed size distribution. Using recent hydrocode predictions of shattering and disruption criteria as starting points, we adjust the size–strength scaling relation for asteroidal strengths within our collisional model until a best least-squares fit to the observed size distribution is obtained. We show for the first time general agreement between the predictions of hydrocodes, results of numerical collisional models, and the observed size distribution of the main-belt population.

We describe the ${digest}2$ software package, a fast, short-arc orbit classifier for small solar system bodies. The ${digest}2$ algorithm has been serving the community for more than 13 yr. The code provides a score, ${D}_{2}$, which represents a pseudo-probability that a tracklet belongs to a given solar system orbit type. ${digest}2$ is primarily used as a classifier for Near-Earth Object (NEO) candidates, to identify those to be prioritized for follow-up observation. We describe the historical development of ${digest}2$ and demonstrate its use on real and synthetic data. We find that ${digest}2$ can accurately and precisely distinguish NEOs from non-NEOs. At the time of detection, 14% of NEO tracklets and 98.5% of non-NEOs tracklets have ${D}_{2}$ below the critical value of ${D}_{2}=65.94 \% $ of our simulated NEOs achieved the maximum ${D}_{2}=100 \% $ and 99.6% of NEOs achieved ${D}_{2}\geqslant 65$ at least once during the simulated 10-year timeframe. We demonstrate that ${D}_{2}$ varies as a function of time, rate of motion, magnitude and sky-plane location, and show that NEOs tend to have lower ${D}_{2}$ at low Solar elongations close to the ecliptic. We use our findings to recommend future development directions for the ${digest}2$ code.

We describe the software package, a fast, short-arc orbit classifier for small solar system bodies. The algorithm has been serving the community for more than 13 yr. The code provides a score, , which represents a pseudo-probability that a tracklet belongs to a given solar system orbit type. is primarily used as a classifier for Near-Earth Object (NEO) candidates, to identify those to be prioritized for follow-up observation. We describe the historical development of and demonstrate its use on real and synthetic data. We find that can accurately and precisely distinguish NEOs from non-NEOs. At the time of detection, 14% of NEO tracklets and 98.5% of non-NEOs tracklets have below the critical value of of our simulated NEOs achieved the maximum and 99.6% of NEOs achieved at least once during the simulated 10-year timeframe. We demonstrate that varies as a function of time, rate of motion, magnitude and sky-plane location, and show that NEOs tend to have lower at low Solar elongations close to the ecliptic. We use our findings to recommend future development directions for the code.