Related papers: Measuring the intracluster light fraction with mac…
The intracluster light (ICL) is a faint diffuse stellar component in clusters made of stars not bound to individual galaxies. We have carried out a large scale study of this component in the nearby Virgo cluster. The diffuse light is traced…
We investigate the near-infrared K-band properties of the brightest cluster galaxies (BCGs) in a sample of 93 galaxy clusters and groups, using data from the Two Micron All Sky Survey. Our cluster sample spans a factor of 70 in mass, making…
We investigate on the role of the halo concentration in the formation of the intra-cluster light (ICL) in galaxy groups and clusters, as predicted by a state-of-art semi-analytic model of galaxy formation, coupled with a set of…
Contrastive Learning (CL) has been proved to be a powerful self-supervised approach for a wide range of domains, including computer vision and graph representation learning. However, the incremental learning issue of CL has rarely been…
The intracluster light (ICL) fraction is a well-known indicator of the dynamical activity in intermediate-redshift clusters. Merging clusters in the redshift interval $0.18<z<0.56$ have a distinctive peak in the ICL fractions measured…
Large-scale Transformer language models (LMs) trained solely on next-token prediction with web-scale data can solve a wide range of tasks after seeing just a few examples. The mechanism behind this capability, known as in-context learning…
A large fraction of the stellar mass in galaxy clusters is thought to be contained in the diffuse low surface brightness intracluster light (ICL). Being bound to the gravitational potential of the cluster rather than any individual galaxy,…
We present a novel clustering objective that learns a neural network classifier from scratch, given only unlabelled data samples. The model discovers clusters that accurately match semantic classes, achieving state-of-the-art results in…
The future Rubin Legacy Survey of Space and Time (LSST) is expected to deliver its first data release in the current of 2025. The upcoming survey will provide us with images of galaxy clusters in the optical to the near-infrared, with…
The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…
We explore several ways to dissect Brightest Cluster Galaxies (BCGs) and their surrounding Intracluster Light (ICL) using a surface brightness cut, a luminosity cut, excess light above a de Vaucouleurs profile, or a double S\'ersic…
We investigate the origin and formation mechanisms of the intra-cluster light (ICL) in The Three Hundred simulations, a set of 324 hydrodynamically resimulated massive galaxy clusters. The ICL, a diffuse component of stars not bound to…
Context. Intracluster Light (ICL) is a faint stellar component of galaxy groups and clusters bound to the cluster potential, and making up a significant fraction of the cluster mass. ICL formation and evolution is strongly linked to the…
Clustering is a class of unsupervised learning methods that has been extensively applied and studied in computer vision. Little work has been done to adapt it to the end-to-end training of visual features on large scale datasets. In this…
We have developed a machine learning algorithm capable of detecting ``out-of-domain data'' for trustworthy cosmological inference. By using data from two separate suites of cosmological simulations, we show that our algorithm is able to…
The evolutionary classification of molecular clumps, crucial for understanding star formation, is commonly based on human-assigned categories derived from infrared (IR) emission and well-established morphological criteria. However, due to…
The intracluster light (ICL) fraction, measured at certain specific wavelengths, has been shown to provide a good marker for determining the dynamical stage of galaxy clusters, i.e., merging versus relaxed, for small to intermediate…
Unsupervised learning has always been appealing to machine learning researchers and practitioners, allowing them to avoid an expensive and complicated process of labeling the data. However, unsupervised learning of complex data is…
The diffuse stellar component of galaxy clusters made up of intergalactic stars is termed the intracluster light (ICL). Though there is a developing understanding of the mechanisms by which the ICL is formed, no strong consensus has yet…
Image clustering is a very useful technique that is widely applied to various areas, including remote sensing. Recently, visual representations by self-supervised learning have greatly improved the performance of image clustering. To…