Related papers: MASSCLEAN - MASSive CLuster Evolution and ANalysis…
We present a machine learning (ML) pipeline to identify star clusters in the multi{color images of nearby galaxies, from observations obtained with the Hubble Space Telescope as part of the Treasury Project LEGUS (Legacy ExtraGalactic…
Stellar population synthesis techniques for predicting the observable light emitted by a stellar population have extensive applications in numerous areas of astronomy. However, accurate predictions for small populations of young stars, such…
We address the presently exciting issue of the presence of stellar clusters in the periphery of the Magellanic Clouds (MCs) and beyond by making use of a wealth of wide-field high-quality images released in advance from the Magellanic…
We introduce Deep-CEE (Deep Learning for Galaxy Cluster Extraction and Evaluation), a proof of concept for a novel deep learning technique, applied directly to wide-field colour imaging to search for galaxy clusters, without the need for…
Grids of stellar models are useful tools to derive the properties of stellar clusters, in particular young clusters hosting massive stars, and to provide information on the star formation process in various mass ranges. Because of their…
We investigate the color-magnitude diagram (CMD) of cluster galaxies in the hierarchical $\Lambda$-CDM cosmological scenario using both single stellar populations and simple galaxy models. First, we analyze the effect of bursts and mergers…
The IMACS Cluster Building Survey uses the wide field spectroscopic capabilities of the IMACS spectrograph on the 6.5m Baade Telescope to survey the large-scale environment surrounding rich intermediate-redshift clusters of galaxies. The…
Context: Understanding the evolution of the dark matter halos of galaxies after they become part of a cluster is essential for understanding the evolution of these satellite galaxies. Aims: We investigate the potential of galaxy-galaxy…
Abridged: ATLASGAL is an unbiased 870 micron submillimetre survey of the inner Galactic plane. It provides a large and systematic inventory of all massive, dense clumps in the Galaxy (>1000 Msun) and includes representative samples of all…
This article is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our aim is to quantify the…
The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological…
High-redshift clusters of galaxies are amongst the largest cosmic structures. Their properties and evolution are key ingredients to our understanding of cosmology: to study the growth of structure from the inhomogeneities of the cosmic…
We present a deep machine learning (ML) approach to constraining cosmological parameters with multi-wavelength observations of galaxy clusters. The ML approach has two components: an encoder that builds a compressed representation of each…
Classification will be an important first step for upcoming surveys that will detect billions of new sources such as LSST and Euclid, as well as DESI, 4MOST and MOONS. The application of traditional methods of model fitting and…
High resolution spectral models for simple stellar populations (SSP) developed in the past few years have become a standard ingredient in studies of stellar population of galaxies. As more such models become available, it becomes…
Clustering algorithms can help reconstruct the assembly history of the Milky Way by identifying groups of stars sharing similar properties in a kinematical or chemical abundance space. Despite being promising tools, their efficiency has not…
We present the novel, semi-automated clustering tool ASPECT for analysing voluminous archives of spectra. The heart of the program is a neural network in form of Kohonen's self-organizing map. The resulting map is designed as an icon map…
(Abridged) We introduce a novel technique to construct spatially resolved maps of stellar mass surface density in galaxies based on optical and near IR imaging. We use optical/NIR colour(s) to infer effective stellar mass-to-light ratios…
We present the first stable release of Halotools (v0.2), a community-driven Python package designed to build and test models of the galaxy-halo connection. Halotools provides a modular platform for creating mock universes of galaxies…
We discuss the mass assembly history both on cluster and galaxy scales and their impact on galaxy evolution. On cluster scale, we introduce our on-going PISCES project on Subaru, which plans to target ~15 clusters at 0.4<z<1.3 using the…