Related papers: Detecting streaks in smart telescopes images with …
In August 2025 a workshop was convened to bring together experts to better understand steps that can be taken to mitigate the impact of satellite constellations on astronomical observations. At the time, just over 12,000 operational…
We apply a new deep learning technique to detect, classify, and deblend sources in multi-band astronomical images. We train and evaluate the performance of an artificial neural network built on the Mask R-CNN image processing framework, a…
Microlensing is generally studied in the geometric optics limit. However, diffraction may be important when nearby substellar objects lens occult distant stars. In particular the effects of diffraction become more important as the…
We review some of the recent developments and challenges posed by the data analysis in modern digital sky surveys, which are representative of the information-rich astronomy in the context of Virtual Observatory. Illustrative examples…
We present DeepStreaks, a convolutional-neural-network, deep-learning system designed to efficiently identify streaking fast-moving near-Earth objects that are detected in the data of the Zwicky Transient Facility (ZTF), a wide-field,…
A number of industrial applications, such as smart grids, power plant operation, hybrid system management or energy trading, could benefit from improved short-term solar forecasting, addressing the intermittent energy production from solar…
Deep learning models are being increasingly adopted in wide array of scientific domains, especially to handle high-dimensionality and volume of the scientific data. However, these models tend to be brittle due to their complexity and…
In the coming years, a new generation of sky surveys, in particular, Euclid Space Telescope (2022), and the Rubin Observatory's Legacy Survey of Space and Time (LSST, 2023) will discover more than 200,000 new strong gravitational lenses,…
Upcoming deep optical surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will scan the sky to unprecedented depths and detect billions of galaxies. This amount of detections will however cause the apparent…
The detection of high-energy astrophysical neutrinos by IceCube has opened new windows for neutrino astronomy, but their sources remains largely unresolved. We study a methodology to address this - deep-stacking - that exploits correlations…
Sky survey telescopes play a critical role in modern astronomy, but misalignment of their optical elements can introduce significant variations in point spread functions, leading to reduced data quality. To address this, we need a method to…
Radio-astronomical observations are increasingly contaminated by interference, and suppression techniques become essential. A powerful candidate for interference mitigation is adaptive spatial filtering. We study the effect of spatial…
The Large Synoptic Survey Telescope (LSST) will survey the southern sky from 2022--2032 with unprecedented detail. Since the observing strategy can lead to artifacts in the data, we investigate the effects of telescope-pointing offsets…
Machine learning, and eventually true artificial intelligence techniques, are extremely important advancements in astrophysics and astronomy. We explore the application of deep learning using neural networks in order to automate the…
Over the past several decades, advances in telescope/detector technologies and deep imaging techniques have pushed surface brightness limits to ever fainter levels. We can now both detect and measure the diffuse, extended star light that…
This study details an artificial intelligence (AI)-based methodology for the semantic segmentation of space camera faults. Specifically, we address the segmentation of straylight effects induced by solar presence around the camera's Field…
Wavelets have been used extensively for several years now in astronomy for many purposes, ranging from data filtering and deconvolution, to star and galaxy detection or cosmic ray removal. More recent sparse representations such ridgelets…
Over the past decade, sky surveys such as the Sloan Digital Sky Survey have proven the power of large data sets for answering fundamental astrophysical questions. This observational progress, based on a synergy of advances in telescope…
On 8 April 2024, tens of millions of people across North America will be able to view a total solar eclipse. Such astronomical events have been important throughout history, but with nearly 10,000 satellites in orbit, we question whether…
Current and future large astronomical surveys will yield multiparameter databases on millions or even billions of objects. The scientific exploitation of these will require powerful, robust, and automated classification tools tailored to…