Related papers: Teaching with Code: Globular Cluster Distance Lab
Current and upcoming cosmological experiments open a new era of precision cosmology, thus demanding accurate theoretical predictions for cosmological observables. Because of the complexity of the codes delivering such predictions, reaching…
Clusters of galaxies are used in a variety of ways to do cosmology. Some of them are presented here. Their X-ray emitting gas allows us to determine the baryon fraction, dark matter distribution and the matter density $\Omega_{m}$ of the…
The dark matter distribution of the Milky Way remains among the major unsolved problems about our home galaxy. The masses of other spiral galaxies can be determined from their rotation curves through long-slit spectroscopy. But for the…
The use of Python is noticeably growing among the scientific community, and Astronomy is not an exception. The power of Python consists of being an extremely versatile high-level language, easy to program that combines both traditional…
The work of astronomers is getting more complex and advanced as the progress of computer development occurs. With improved computing capabilities and increased data flow, more sophisticated software is required in order to interpret, and…
Accurate distances to local molecular clouds are critical for understanding the star and planet formation process, yet distance measurements are often obtained inhomogeneously on a cloud-by-cloud basis. We have recently developed a method…
With the advent of research-grade robotic telescopes (and professional archives) coupled with the wide availability of the Internet in schools, getting high-quality data in the classroom has become much easier than ever before. Robotic…
The field of astronomy is experiencing a data explosion driven by significant advances in observational instrumentation, and classical methods often fall short of addressing the complexity of modern astronomical datasets. Probabilistic…
This review summarizes popular unsupervised learning methods, and gives an overview of their past, current, and future uses in astronomy. Unsupervised learning aims to organise the information content of a dataset, in such a way that…
We present a new analysis of the Sloan Digital Sky Survey data aimed at producing a detailed map of the nearby (z < 0.5) universe. Using neural networks trained on the available spectroscopic base of knowledge we derived distance estimates…
The measurement of angular diameter distance to galaxy clusters, through combined Sunyaev-Zel'dovich (SZ) effect data with X-ray emission observations, is now a well-known probe of cosmology. Using a combination of SZ data and a map of the…
Variable stars have been used for over one hundred years as probes for determining astronomical distances; these distances can be used to map the three-dimensional (3D) structure of nearby galaxies. Exploiting the effect that moving to the…
Machine learning, and eventually true artificial intelligence techniques, are extremely important advancements in astrophysics and astronomy. We explore the application of deep learning using neural networks in order to automate the…
We present a device, created by us and named Stellector, composed by a laser pointer which is precisely guided by two step motors with the purpose to explore and teach astronomy concepts having the real night sky in the background. The…
Electronically Assisted Astronomy consists in capturing deep sky images with a digital camera coupled to a telescope to display views of celestial objects that would have been invisible through direct observation. This practice generates a…
Most galaxies in the nearby Universe are gravitationally bound to a cluster or group of galaxies. Their optical contents, such as optical richness, are crucial for understanding the co-evolution of galaxies and large-scale structures in…
Major advancements in space science and detector technology brought about a revolution in global astrometry, the science of measuring distances and motions of stars in the Milky Way and in the local universe. From the first ESA astrometric…
Distances to stars are key to revealing a three-dimensional view of the Milky Way, yet their determination is a major challenge in astronomy. Whilst the brightest nearby stars benefit from direct parallax measurements, fainter stars are…
The Kepler space telescope has proven to be a gold mine for the study of variable stars. Unfortunately, Kepler only returns a handful of pixels surrounding each star on the target list, which omits a large number of stars in the Kepler…
Research-based active learning approaches are critical for the teaching and learning of undergraduate STEM majors. Course-based undergraduate research experiences (CUREs) are becoming more commonplace in traditional, in-person academic…