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.
Trans-Neptunian objects provide a window into the history of the solar system, but they can be challenging to observe due to their distance from the Sun and relatively low brightness. Here we report the detection of 75 moving objects that we could not link to any other known objects, the faintest of which has a VR magnitude of 25.02 ± 0.93 using the Kernel-Based Moving Object Detection (KBMOD) platform. We recover an additional 24 sources with previously known orbits. We place constraints on the barycentric distance, inclination, and longitude of ascending node of these objects. The unidentified objects have a median barycentric distance of 41.28 au, placing them in the outer solar system. The observed inclination and magnitude distribution of all detected objects is consistent with previously published KBO distributions. We describe extensions to KBMOD, including a robust percentile-based lightcurve filter, an in-line graphics-processing unit filter, new coadded stamp generation, and a convolutional neural network stamp filter, which allow KBMOD to take advantage of difference images. These enhancements mark a significant improvement in the readiness of KBMOD for deployment on future big data surveys such as LSST.
Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work we describe a new linear feature detection algorithm designed specifically for implementation in Big Data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars, galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.
Given the current limited knowledge of meteor plasma micro-physics and its interaction with the surrounding atmosphere and ionosphere, meteors are a highly interesting observational target for high-resolution wide-field astronomical surveys. Such surveys are capable of resolving the physical size of meteor plasma heads, but they produce large volumes of images that need to be automatically inspected for possible existence of long linear features produced by meteors. Here we show how big aperture sky survey telescopes detect meteors as defocused tracks with a central brightness depression. We derive an analytic expression for a defocused point source meteor track and use it to calculate brightness profiles of meteors modeled as uniform brightness disks. We apply our modeling to meteor images as seen by the SDSS and LSST telescopes. The expression is validated by Monte Carlo ray-tracing simulations of photons traveling through the atmosphere and the LSST telescope optics. We show that estimates of the meteor distance and size can be extracted from the measured FWHM and the strength of the central dip in the observed brightness profile. However, this extraction becomes difficult when the defocused meteor track is distorted by the atmospheric seeing or contaminated by a long lasting glowing meteor trail. The FWHM of satellites tracks is distinctly narrower than meteor values, which enables removal of a possible confusion between satellites and meteors.
A foundational goal of the Large Synoptic Survey Telescope (LSST) is to map the Solar System small body populations that provide key windows into understanding of its formation and evolution (Ivezić et al., 2008; LSST Science Collaboration et al., 2009). This is especially true of the populations of the Outer Solar System -objects at the orbit of Neptune r > 30 AU and beyond.In this whitepaper, we propose a minimal change to the LSST cadence that can greatly enhance LSST's ability to discover faint distant Solar System objects across the entire wide-fast-deep (WFD) survey area. Specifically, we propose that the WFD cadence be constrained so as to deliver least one sequence of 10 visits per year taken in a ∼ 10 day period in any combination of g, r, and i bands. Combined with advanced shift-and-stack algorithms (e.g. Whidden et al., 2019) this modification would enable a nearly complete census of the outer Solar System to ∼ 25.5 magnitude, yielding 4 − 8x more KBO discoveries than with single-epoch baseline, and enabling rapid identification and follow-up of unusual distant Solar System objects in 5x greater volume of space.These increases would enhance the science cases discussed in Schwamb et al. 2018 whitepaper, including probing Neptune's past migration history as well as discovering hypothesized planet(s) beyond the orbit of Neptune (or at least placing significant constraints on their existence).
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