相关论文: Detecting Tidal Features using Self-Supervised Rep…
Low surface brightness substructures around galaxies, known as tidal features, are a valuable tool in the detection of past or ongoing galaxy mergers, and their properties can answer questions about the progenitor galaxies involved in the…
Interactions between galaxies leave distinguishable imprints in the form of tidal features which hold important clues about their mass assembly. Unfortunately, these structures are difficult to detect because they are low surface brightness…
Faint tidal features around galaxies record their merger and interaction histories over cosmic time. Due to their low surface brightnesses and complex morphologies, existing automated methods struggle to detect such features and most work…
We measure the radial $g-i$ colour profiles of $\sim$32,000 galaxies drawn from the Hyper Suprime-Cam Subaru Strategic Program optical imaging survey, including 1415 exhibiting tidal features. We compare the colour profiles of galaxies with…
In hierarchical models of galaxy formation, stellar tidal streams are expected around most, if not all, galaxies. Although these features may provide useful diagnostics of the $\Lambda$CDM model, their observational properties remain poorly…
Identifying mergers from observational data has been a crucial aspect of studying galaxy evolution and formation. Tidal features, typically fainter than 26 ${\rm mag\,arcsec^{-2}}$, exhibit a diverse range of appearances depending on the…
Like massive galaxies, dwarf galaxies are expected to undergo major mergers with other dwarfs. However, the end state of these mergers and the role that merging plays in regulating dwarf star formation is uncertain. Using imaging from the…
Tidal features in the outskirts of galaxies yield unique information about their past interactions and are a key prediction of the hierarchical structure formation paradigm. The Vera C. Rubin Observatory is poised to deliver deep…
Hierarchical galactic evolution models predict that mergers drive galaxy growth, producing low surface brightness (LSB) tidal features that trace galaxies' late assembly. These faint structures encode information about past mergers and are…
Slow rotator galaxies are distinct amongst galaxy populations, with simulations suggesting that a mix of minor and major mergers are responsible for their formation. A promising path to resolve outstanding questions on the type of merger…
The role of major mergers in galaxy evolution remains a key open question. Existing empirical merger identification methods use non-parametric and subjective visual classifications which can pose systematic challenges to constraining merger…
Tidal features are a key observable prediction of the hierarchical model of galaxy formation and contain a wealth of information about the properties and history of a galaxy. Modern wide-field surveys such as LSST and Euclid will…
From the $\Lambda$ cold dark matter paradigm it is expected that galaxies merge and grow in their environments. These processes form various tidal features depending on the merger mass ratio, orbital parameters, and gas richness. We…
We present 1,201 galaxies at $0.05<z<0.45$ that host tidal features, detected from the first $\sim\! 200$ deg$^2$ of imaging from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). All galaxies in the present sample have…
Unsupervised learning, a branch of machine learning that can operate on unlabelled data, has proven to be a powerful tool for data exploration and discovery in astronomy. As large surveys and new telescopes drive a rapid increase in data…
Vessel segmentation is an essential task in many clinical applications. Although supervised methods have achieved state-of-art performance, acquiring expert annotation is laborious and mostly limited for two-dimensional datasets with a…
Self-supervised learning on point clouds has gained a lot of attention recently, since it addresses the label-efficiency and domain-gap problems on point cloud tasks. In this paper, we propose a novel self-supervised framework to learn…
Detecting and evaluating surface coating defects is important for marine vessel maintenance. Currently, the assessment is carried out manually by qualified inspectors using international standards and their own experience. Automating the…
State-of-the-art lidar-based 3D object detection methods rely on supervised learning and large labeled datasets. However, annotating lidar data is resource-consuming, and depending only on supervised learning limits the applicability of…
Retinal vessel segmentation based on deep learning requires a lot of manual labeled data. That is time-consuming, laborious and professional. What is worse, the acquisition of abundant fundus images is difficult. These problems are more…