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Skyline plays a pivotal role in mountainous visual geo-localization and localization/navigation of planetary rovers/UAVs and virtual/augmented reality applications. We present a novel mountainous skyline detection approach where we adapt a…
Context. Models of hierarchical structure formation predict the accretion of smaller satellite galaxies onto more massive systems and this process should be accompanied by a disintegration of the smaller companions visible, e.g., in tidal…
Aims:The Gaia astrometric survey mission will, as a consequence of its scanning law, obtain low resolution optical (330-1000 nm) spectrophotometry of several million unresolved galaxies brighter than V=22. We present the first steps in a…
We introduce the Southern Stellar Stream Spectroscopy Survey (${S}^5$), an on-going program to map the kinematics and chemistry of stellar streams in the Southern Hemisphere. The initial focus of ${S}^5$ has been spectroscopic observations…
The traditional techniques for extracting polycrystalline grain structures from microscopy images, such as transmission electron microscopy (TEM) and scanning electron microscopy (SEM), are labour-intensive, subjective, and time-consuming,…
This paper uses Gaussian mixture techniques to dissect the Milky Way (MW) stellar halo in angular momentum space. Application to a catalogue of 5389 stars near the plane of the Sagittarius (Sgr) stream with full 6D phase-space coordinates…
The presence of Gaia DR3 provides a large sample of stars with complete 6D information, offering a fertile ground for the exploration of stellar objects that were accreted to the Milky Way through ancient merger events. In this study, we…
GAIA is a short-listed candidate for the ESA Cornerstone mission C5, meeting the ESA Survey Committee requirement for an observatory mission, dedicated to astrometry, providing 10 micro-arcsecond accuracy at 15th magnitude. The GAIA mission…
The problem of searching for unmodeled gravitational-wave bursts can be thought of as a pattern recognition problem: how to find statistically significant clusters in spectrograms of strain power when the precise signal morphology is…
Nearby galaxies provide populations of stellar and non-stellar sources at a common distance and in quantifiable environments. All are observed through the Milky Way foreground, with varying degrees of contamination that depend on observed…
Clouds and haze often occlude optical satellite images, hindering continuous, dense monitoring of the Earth's surface. Although modern deep learning methods can implicitly learn to ignore such occlusions, explicit cloud removal as…
Data from the Gaia satellite show that the solar neighbourhood of the Milky Way's stellar halo is imprinted with substructure from several accretion events. Evidence of these events is found in "the Shards", stars clustering with high…
There are expected to be physical relationships between the globular clusters (GCs) and stellar substructures in the Milky Way, not all of which have yet been found. We search for such substructures from a combined halo sample of SDSS blue…
NGC 288 is a Galactic globular cluster having observed extra tidal structure, without confirmed tidal tails. $Gaia$ DR2 provides photometric and astrometric data for many of the stars in NGC 288 and its extra tidal structure. To compare…
In the real world, data streams are ubiquitous -- think of network traffic or sensor data. Mining patterns, e.g., outliers or clusters, from such data must take place in real time. This is challenging because (1) streams often have high…
Since its launch in 2013, the Gaia space telescope has provided precise measurements of the positions and magnitudes of over 1 billion stars. This has enabled extensive searches for stellar and sub-stellar companions through astrometric and…
The astrometric satellite Gaia recently released part of its third data set, which provides a good opportunity to hunt for more open clusters in the Milky Way. In this work, we conduct a blind search for open clusters in the Galactic disk…
A new generative technique is presented in this paper that uses Deep Learning to reconstruct stellar spectra based on a set of stellar parameters. Two different Neural Networks were trained allowing the generation of new spectra. First, an…
Stellar streams are key players in many aspects of Milky Way studies and, in particular, studying their orbital dynamics is crucial for furthering our understanding of the Milky Way's gravitational potential. Although this is not a trivial…
Over the last two decades, machine learning models have been widely applied and have proven effective in classifying variable stars, particularly with the adoption of deep learning architectures such as convolutional neural networks,…