Related papers: Advances in Deep Space Exploration via Simulators …
Star trackers are primarily optical devices that are used to estimate the attitude of a spacecraft by recognising and tracking star patterns. Currently, most star trackers use conventional optical sensors. In this application paper, we…
As the NASA Transiting Exoplanet Survey Satellite (TESS) fulfills its primary mission it is executing an unprecedented all-sky survey with the potential to discover distant planets in our own solar system, as well as hundreds of…
The lack of tangible evidence for non-gravitational interactions between dark and visible sectors drives the need for exploring new avenues of inferring dark matter properties through purely gravitational probes. In particular, addressing…
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…
With the discovery of the first transiting extrasolar planetary system back to 1999, a great number of projects started to hunt for other similar systems. Because of the incidence rate of such systems was unknown and the length of the…
Deep imaging programs, such as MATLAS which has just been completed at the CFHT, allows us to study with their diffuse light the outer stellar populations around large number of galaxies. We have carried out a systematic census of their…
Image deblurring is an economic way to reduce certain degradations (blur and noise) in acquired images. Thus, it has become essential tool in high resolution imaging in many applications, e.g., astronomy, microscopy or computational…
We tackle the problem of exploiting Radar for perception in the context of self-driving as Radar provides complementary information to other sensors such as LiDAR or cameras in the form of Doppler velocity. The main challenges of using…
Exoplanet imaging is a major challenge in astrophysics due to the need for high angular resolution and high contrast. We present a multi-scale statistical model for the nuisance component corrupting multivariate image series at high…
Estimating redshift is a central task in astrophysics, but its measurement is costly and time-consuming. In addition, current image-based methods are often validated on homogeneous datasets. The development and comparison of networks able…
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…
We investigate the merits of a massive forward modeling of ground-based optical imaging as a diagnostic for the strong lensing nature of Early-Type Galaxies, in the light of which blurred and faint Einstein rings can hide. We simulate…
With upcoming wide field surveys from the ground and space the number of known dwarf galaxies at $\lesssim 25$ Mpc is expected to dramatically increase. Insight into their nature and analyses of these systems' intrinsic properties will rely…
Satellite image restoration aims to improve image quality by compensating for degradations (e.g., noise and blur) introduced by the imaging system and acquisition conditions. As a fundamental preprocessing step, restoration directly impacts…
The Star-Planet Activity Research CubeSat (SPARCS) is a NASA-funded 6U-CubeSat mission designed to monitor ultraviolet (UV) radiation from low-mass stars. These stars' relatively high-frequency and high-energy UV flares significantly affect…
This paper tackles the challenge of autonomous target search using unmanned aerial vehicles (UAVs) in complex unknown environments. To fill the gap in systematic approaches for this task, we introduce Star-Searcher, an aerial system…
The abundance of dark matter (DM) subhalos orbiting a host galaxy is a generic prediction of the cosmological framework, and is a promising way to constrain the nature of DM. In this paper, we investigate the use of machine learning-based…
It has recently been demonstrated that deep learning has significant potential to automate parts of the exoplanet detection pipeline using light curve data from satellites such as Kepler \cite{borucki2010kepler} \cite{koch2010kepler} and…
Direct detection and characterization of Earth-like planets around Sun-like stars is a core task for evaluating the prevalence of habitability and life in the Universe. Here, we discuss a promising option for achieving this goal, which is…
Cosmological surveys aim at answering fundamental questions about our Universe, including the nature of dark matter or the reason of unexpected accelerated expansion of the Universe. In order to answer these questions, two important…