相关论文: Detecting Galaxy Tidal Features Using Self-Supervi…
Self-supervised learning allows for better utilization of unlabelled data. The feature representation obtained by self-supervision can be used in downstream tasks such as classification, object detection, segmentation, and anomaly…
Segmenting or detecting objects in sparse Lidar point clouds are two important tasks in autonomous driving to allow a vehicle to act safely in its 3D environment. The best performing methods in 3D semantic segmentation or object detection…
A fundamental prediction of the Lambda Cold Dark Matter (LCDM) cosmology is the centrally divergent cuspy density profile of dark matter haloes. Density cusps render CDM haloes resilient to tides, and protect dwarf galaxies embedded in them…
We extend a machine learning (ML) framework presented previously to model galaxy formation and evolution in a hierarchical universe using N-body + hydrodynamical simulations. In this work, we show that ML is a promising technique to study…
Among those objects formed out of collisional debris during galaxy mergers, the prominent gaseous accumulations observed near the tip of some long tidal tails are the most likely to survive long enough to form genuine recycled galaxies.…
New advancements in radio data post-processing are underway within the SKA precursor community, aiming to facilitate the extraction of scientific results from survey images through a semi-automated approach. Several of these developments…
The rapidly improving quality and resolution of both low surface brightness observations and cosmological simulations of galaxies enables one to address the important question how the formation history is imprinted in the outer, unrelaxed…
Galaxy edges or truncations are low-surface-brightness (LSB) features located in the galaxy outskirts that delimit the distance up to where the gas density enables efficient star formation. As such, they could be interpreted as a…
During the last decade, there has been an explosive growth in survey data and deep learning techniques, both of which have enabled great advances for astronomy. The amount of data from various surveys from multiple epochs with a wide range…
Multi-band images of galaxies reveal a huge amount of information about their morphology and structure. However, inferring properties of the underlying stellar populations such as age, metallicity or kinematics from those images is…
Understanding how galaxies trace the underlying matter density field is essential for characterizing the influence of the large-scale structure on galaxy formation, being therefore a key ingredient in observational cosmology. This…
The internal structure and abundance of dark matter halos and subhalos are powerful probes of the nature of dark matter. In order to compare observations with dark matter models, accurate theoretical predictions of these quantities are…
As the data volume of astronomical imaging surveys rapidly increases, traditional methods for image anomaly detection, such as visual inspection by human experts, are becoming impractical. We introduce a machine-learning-based approach to…
We use the hydrodynamical EAGLE simulation to test if ultra-compact dwarf galaxies (UCDs) can form by tidal stripping by predicting the ages and metallicities of tidally stripped galaxy nuclei in massive galaxy clusters, and compare these…
Modern lidar systems can produce not only dense point clouds but also 360 degrees low-resolution images. This advancement facilitates the application of deep learning (DL) techniques initially developed for conventional RGB cameras and…
We present a new evolutionary model for the far-UV to sub-mm properties of the galaxy population. This combines a semi-analytic galaxy formation model based on hierarchical clustering (GALFORM) with a spectro-photometric code which includes…
Tens of thousands of galaxy-galaxy strong lensing systems are expected to be discovered by the end of the decade. These will form a vast new dataset that can be used to probe subgalactic dark matter structures through its gravitational…
Tidal interactions between massive galaxies and their satellites are fundamental processes in a Universe with L-Cold Dark Matter cosmology, redistributing material into faint features that preserve records of past galactic interactions.…
The analysis of optical images of galaxy-galaxy strong gravitational lensing systems can provide important information about the distribution of dark matter at small scales. However, the modeling and statistical analysis of these images is…
We present a method for automatic detection and classification of galaxies which includes a novel data-augmentation procedure to make trained models more robust against the data taken from different instruments and contrast-stretching…