Related papers: Error dependencies in the space-based CNEOS fireba…
Reliable use of deep neural networks (DNNs) for medical image analysis requires methods to identify inputs that differ significantly from the training data, called out-of-distribution (OOD), to prevent erroneous predictions. OOD detection…
Flares and CMEs can have deleterious effects on their surroundings: they can erode atmospheres of orbiting planets over time and also have high importance in stellar evolution. Most of the CME detections in the literature are single events…
To improve the theoretical prediction power for synthesizing superheavy elements beyond Og, a Bayesian uncertainty quantification method is employed to evaluate the uncertainty of the calculated evaporation residue cross sections (ERCS) for…
Foundation models such as DINOv2 have shown strong performance in few-shot anomaly detection, yet two key questions remain unexamined: (i) how susceptible are these detectors to adversarial perturbations; and (ii) how well do their anomaly…
Statistical interpretation of sparsely sampled event rates has become vital for new transient surveys, particularly those aimed at detecting fast radio bursts (FRBs). We provide an accessible reference for a number of simple, but critical,…
Context. Jupiter-family comets (JFCs), which originate from the Kuiper belt and scattered disk, exhibit low-inclination and chaotic trajectories due to close encounters with Jupiter. Despite their typically short incursions into the inner…
We report the first-time recovery of a fresh meteorite fall using a drone and a machine learning algorithm. A fireball on the 1st April 2021 was observed over Western Australia by the Desert Fireball Network, for which a fall area was…
We have calculated 90% confidence limits on the steady-state rate of catastrophic disruptions of main belt asteroids in terms of the absolute magnitude at which one catastrophic disruption occurs per year (HCL) as a function of the…
We present orbital elements, orbital parallaxes and individual component masses, for fourteen spatially resolved double-line spectroscopic binaries derived doing a simultaneous fit of their visual orbit and radial velocity curve. This was…
The main goal of The Extreme Universe Space Observatory on a Super Pressure Balloon (EUSO-SPB1) was to observe from above extensive air showers caused by ultra-high energy cosmic rays. EUSO-SPB1 uses a fluorescence detector that observes…
We examine meteoroid orbits recorded by the Canadian Meteor Orbit Radar (CMOR) from 2012-2019, consisting of just over 11 million orbits in a search for potential interstellar meteoroids. Our 7.5 year survey consists of an integrated…
The first observational evidence for cosmic acceleration appeared from Type Ia supernovae (SNe Type Ia) Hubble diagram from two different groups. However, the empirical treatment of SNe Type Ia and their ability to show cosmic acceleration…
Thermal infrared measurements of near-Earth objects provide critical data for constraining their physical properties such as size. The NEOWISE mission has been conducting an all-sky infrared survey to gather such data and improve our…
The NASA/IPAC Extragalactic Database (NED) is an impressive tool for finding near-exhaustive information on millions of astrophysical objects. Here, we outline a small systematic error that occurs in NED because a low-redshift approximation…
Distributed AI inference pipelines rely heavily on timestamp-based observability to understand system behavior. This work demonstrates that even small clock skew between nodes can cause observability to become causally incorrect while the…
Neuroscientists have recently shown that images that are difficult to find in visual search elicit similar patterns of firing across a population of recorded neurons. The $L^{1}$ distance between firing rate vectors associated with two…
Based on telescopic observations of Jupiter-family comets (JFCs), there is predicted to be a paucity of objects at sub-kilometre sizes. However, several bright fireballs and some meteorites have been tenuously linked to the JFC population,…
Time Series Anomaly Detection metrics serve as crucial tools for model evaluation. However, existing metrics suffer from several limitations: insufficient discriminative power, strong hyperparameter dependency, sensitivity to perturbations,…
Over the past decade, previous balanced datasets have been used to advance deep learning algorithms for industrial applications. In urban infrastructures and living environments, damage data mining cannot avoid imbalanced data issues…
The kinematics and dynamics of stellar and substellar populations within young, still-forming clusters provides valuable information for constraining theories of formation mechanisms. Using Keck II NIRSPEC+AO data, we have measured radial…