Related papers: Near-Earth Object Orbit Linking with the Large Syn…

Near-infrared spectroscopy of Near-Earth Objects (NEOs) connects diagnostic spectral features to specific surface mineralogies. The combination of spectroscopy with albedos and diameters derived from thermal infrared observations can…

We report a detection of a faint near-Earth asteroid (NEA), which was done using our synthetic tracking technique and the CHIMERA instrument on the Palomar 200-inch telescope. This asteroid, with apparent magnitude of 23, was moving at 5.97…

Robust impact monitoring of near-Earth objects is an essential task of planetary defense. Current systems such as NASA's Sentry-II, the University of Pisa's CLOMON2, and ESA's Aegis have been highly successful, but independent approaches…

Multi-object tracking is a cornerstone capability of any robotic system. The quality of tracking is largely dependent on the quality of the detector used. In many applications, such as autonomous vehicles, it is preferable to over-detect…

The future extremely large telescopes (ELTs) are expected to be powerful tools to probe the atmospheres of extrasolar planets using high-dispersion spectroscopy, with the potential to detect molecular oxygen in Earth-like planets transiting…

Active learning (AL) for real-world object detection faces computational and reliability challenges that limit practical deployment. Developing new AL methods requires training multiple detectors across iterations to compare against…

Asteroids with low orbital perihelion distances experience extreme heating from the Sun that can modify their surfaces and trigger non-typical activity mechanisms. These objects are generally difficult to observe from ground-based…

We present a novel pipeline that uses a convolutional neural network (CNN) to improve the detection capability of near-Earth asteroids (NEAs) in the context of planetary defense. Our work aims to minimize the dependency on human…

In recent years, the retrieval of entire asteroids has received significant attention, with many approaches leveraging the invariant manifolds of the Circular-Restricted Three-body Problem to capture an asteroid into a periodic orbit about…

A method of near real-time detection and tracking of resident space objects (RSOs) using a convolutional neural network (CNN) and linear quadratic estimator (LQE) is proposed. Advances in machine learning architecture allow the use of…

Studies on Near Earth Asteroids (NEAs) throw light on discoveries, identification, orbit prediction and civil alert capabilities, including potential asteroid impact hazards. Due to various new observational programs, the discovery rate of…

Up to 150000 asteroids will be visible in the images of the ESA Euclid space telescope, and the instruments of Euclid offer multiband visual to near-infrared photometry and slitless spectra of these objects. Most asteroids will appear as…

We describe enhancements to the digest2 software, a short-arc orbit classifier for heliocentric orbits. Digest2 is primarily used by the Near-Earth Object (NEO) community to flag newly discovered objects for a immediate follow-up and has…

Context. Orbital similarity measures, such as the D-values, have been extensively used in meteor science to identify meteoroid streams and associate meteorite falls with near-Earth objects (NEOs). However, the chaotic nature of near-Earth…

In this paper we investigate how implementing machine learning could improve the efficiency of the search for Trans-Neptunian Objects (TNOs) within Dark Energy Survey (DES) data when used alongside orbit fitting. The discovery of multiple…

Quantum mechanical calculations of core electron binding energies (CEBEs) leading to 2p hole states are relevant to interpreting L-edge x-ray photo-electron spectroscopy (XPS), as well as higher edges. Orbital-optimized density functional…

The nature and origin of the asteroids orbiting in near-Earth space, including those on a potentially hazardous trajectory, is of both scientific interest and practical importance. We aim here at determining the taxonomy of a large sample…

Multi-object density is a fundamental descriptor of a point process and has ability to describe the randomness of number and values of objects, as well as the statistical correlation between objects. Due to its comprehensive nature, it…

Most modern multiple object tracking (MOT) systems follow the tracking-by-detection paradigm, consisting of a detector followed by a method for associating detections into tracks. There is a long history in tracking of combining motion and…

Previous work has demonstrated that the Large Synoptic Survey Telescope (LSST) has the capability to detect transiting planets around main sequence stars in relatively short ($<$ 20 days) periods and using standard algorithms for transit…