NEARBY Platform: Algorithm for Automated Asteroids Detection in Astronomical Images

In the past two decades an increasing interest in discovering Near Earth Objects has been noted in the astronomical community. Dedicated surveys have been operated for data acquisition and processing, resulting in the present discovery of over 18.000 objects that are closer than 30 million miles of Earth. Nevertheless, recent events have shown that there still are many undiscovered asteroids that can be on collision course to Earth. This article presents an original NEO detection algorithm developed in the NEARBY research object, that has been integrated into an automated MOPS processing pipeline aimed at identifying moving space objects based on the blink method. Proposed solution can be considered an approach of Big Data processing and analysis, implementing visual analytics techniques for rapid human data validation.Comment: IEEE 14th International Conference on Intelligent Computer Communication and Processing (ICCP), Sep 6-8, 2018, Cluj-Napoca, Romani

The Deep Lens Survey Transient Search I : Short Timescale and Astrometric Variability

We report on the methodology and first results from the Deep Lens Survey transient search. We utilize image subtraction on survey data to yield all sources of optical variability down to 24th magnitude. Images are analyzed immediately after acquisition, at the telescope and in near-real time, to allow for followup in the case of time-critical events. All classes of transients are posted to the web upon detection. Our observing strategy allows sensitivity to variability over several decades in timescale. The DLS is the first survey to classify and report all types of photometric and astrometric variability detected, including solar system objects, variable stars, supernovae, and short timescale phenomena. Three unusual optical transient events were detected, flaring on thousand-second timescales. All three events were seen in the B passband, suggesting blue color indices for the phenomena. One event (OT 20020115) is determined to be from a flaring Galactic dwarf star of spectral type dM4. From the remaining two events, we find an overall rate of \eta = 1.4 events deg-2 day-1 on thousand-second timescales, with a 95% confidence limit of \eta < 4.3. One of these events (OT 20010326) originated from a compact precursor in the field of galaxy cluster Abell 1836, and its nature is uncertain. For the second (OT 20030305) we find strong evidence for an extended extragalactic host. A dearth of such events in the R passband yields an upper 95% confidence limit on short timescale astronomical variability between 19.5 < R < 23.4 of \eta_R < 5.2. We report also on our ensemble of astrometrically variable objects, as well as an example of photometric variability with an undetected precursor.Comment: 24 pages, 12 figures, 3 tables. Accepted for publication in ApJ. Variability data available at http://dls.bell-labs.com/transients.htm

Low-mass Tertiary Companions to Spectroscopic Binaries. I. Common Proper Motion Survey for Wide Companions Using 2MASS

We report the first results of a multi-epoch search for wide (separations greater than a few tens of AU), low-mass tertiary companions of a volume-limited sample of 118 known spectroscopic binaries within 30 pc of the Sun, using the Two Micron All Sky Survey Point Source Catalog and follow-up observations with the KPNO and CTIO 4 m telescopes. Note that this sample is not volume complete but volume limited, and, thus, there is incompleteness in our reported companion rates. We are sensitive to common proper motion companions with separations from roughly 200 AU to 10,000 AU (~10ˮ → ~ 10'). From 77 sources followed-up to date, we recover 11 previously known tertiaries, 3 previously known candidate tertiaries, of which 2 are spectroscopically confirmed and 1 rejected, and 3 new candidates, of which 2 are confirmed and 1 rejected. This yields an estimated wide tertiary fraction of 19.5^(+5.2)_(–3.7)%. This observed fraction is consistent with predictions set out in star formation simulations where the fraction of wide, low-mass companions to spectroscopic binaries is >10%

The Pan-STARRS Moving Object Processing System

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 non-physical 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 >99.5% efficient at detecting objects on a single night but drops to 80% efficiency at producing orbits for objects detected on multiple nights. 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.Comment: 57 Pages, 26 Figures, 13 Table

Towards Efficient Detection of Small Near-Earth Asteroids Using the Zwicky Transient Facility (ZTF)

We describe ZStreak, a semi-real-time pipeline specialized in detecting small, fast-moving near-Earth asteroids (NEAs) that is currently operating on the data from the newly-commissioned Zwicky Transient Facility (ZTF) survey. Based on a prototype originally developed by Waszczak et al. (2017) for the Palomar Transient Factory (PTF), the predecessor of ZTF, ZStreak features an improved machine-learning model that can cope with the $10\times$ data rate increment between PTF and ZTF. Since its first discovery on 2018 February 5 (2018 CL), ZTF/ZStreak has discovered $45$ confirmed new NEAs over a total of 232 observable nights until 2018 December 31. Most of the discoveries are small NEAs, with diameters less than $\sim100$ m. By analyzing the discovery circumstances, we find that objects having the first to last detection time interval under 2 hr are at risk of being lost. We will further improve real-time follow-up capabilities, and work on suppressing false positives using deep learning.Comment: PASP in pres

Cosmic Ray Rejection by Linear Filtering of Single Images

We present a convolution-based algorithm for finding cosmic rays in single well-sampled astronomical images. The spatial filter used is the point spread function (approximated by a Gaussian) minus a scaled delta function, and cosmic rays are identified by thresholding the filtered image. This filter searches for features with significant power at spatial frequencies too high for legitimate objects. Noise properties of the filtered image are readily calculated, which allows us to compute the probability of rejecting a pixel not contaminated by a cosmic ray (the false alarm probability). We demonstrate that the false alarm probability for a pixel containing object flux will never exceed the corresponding probability for a blank sky pixel, provided we choose the convolution kernel appropriately. This allows confident rejection of cosmic rays superposed on real objects. Identification of multiple-pixel cosmic ray hits can be enhanced by running the algorithm iteratively, replacing flagged pixels with the background level at each iteration.Comment: Accepted for publication in PASP (May 2000 issue). An iraf script implementing the algorithm is available from the author, or from http://sol.stsci.edu/~rhoads/ . 16 pages including 3 figures. Uses AASTeX aaspp4 styl