Related papers: Teaching with Code: Globular Cluster Distance Lab
Globular clusters are among the first objects used to establish the distance scale of the Universe. In the 1970-ies it has been recognized that the differential magnitude distribution of old globular clusters is very similar in different…
Fundamental changes are taking place in the way we do astronomy. In twenty years time, it is likely that most astronomers will never go near a cutting-edge telescope, which will be much more efficiently operated in service mode. They will…
Many topics in introductory astronomy at the college or high-school level rely implicitly on using astronomical photographs and visual data in class. However, students bring many preconceptions to their understanding of these materials that…
By bringing together code, text, and examples, Jupyter notebooks have become one of the most popular means to produce scientific results in a productive and reproducible way. As many of the notebook authors are experts in their scientific…
Visualisation of data is critical to understanding astronomical phenomena. Today, many instruments produce datasets that are too big to be downloaded to a local computer, yet many of the visualisation tools used by astronomers are deployed…
Image segmentation plays a critical role in unlocking the mysteries of the universe, providing astronomers with a clearer perspective on celestial objects within complex astronomical images and data cubes. Manual segmentation, while…
Accurate visualization of double star astrometric data is essential for effective analysis and interpretation. This article presents a Python toolkit designed for astronomers who need to plot measurements from diverse sources -- historical,…
The volume of data generated by modern astronomical telescopes is extremely large and rapidly growing. However, current high-performance data processing architectures/frameworks are not well suited for astronomers because of their…
Clustering is an effective tool for astronomical spectral analysis, to mine clustering patterns among data. With the implementation of large sky surveys, many clustering methods have been applied to tackle spectroscopic and photometric data…
We developed a Python based framework for astronomical image processing and analysis. Astronomical image loading, normalizing, stacking, and filtering processes represent visible range images from grayscale. Besides, the blending process…
With the volume and availability of astronomical data growing rapidly, astronomers will soon rely on the use of machine learning algorithms in their daily work. This proceeding aims to give an overview of what machine learning is and delve…
Large scale structure of the Universe becomes a leading source of precision cosmological information. We present two particular tools that can be used in cosmological analyses of the redshift space galaxy clustering data: a new open-source…
We shall present with examples how analysis of astronomy data can be used for an educational purpose to train students in methods of data analysis, statistics, programming skills and research problems. Special reference will be made to our…
Astronomy is increasingly encountering two fundamental truths: (1) The field is faced with the task of extracting useful information from extremely large, complex, and high dimensional datasets; (2) The techniques of astroinformatics and…
By collecting distances from the literature, a set of 73 planetary nebulae with mean distances of high accuracy is derived. This sample is used for recalibration of the mass-radius relationship, used by many statistical distance methods. An…
This article introduces a set of distance education astronomy laboratory exercises for use by college students and instructors and discuss first usage results. This General Astronomy Education Source (GEAS) exercise set contains eight…
Astronomy datasets can be challenging to use for high school astronomy classes. Data science education pedagogy can be leveraged to create astronomy activities in which students interrogate data, create visuals, and use statistical thinking…
A holographic microscope captures interference patterns, or holograms, that encode three-dimensional (3D) information about the object being viewed. Computation is essential to extracting that 3D information. By wrapping low-level…
Computation, the use of a computer to solve, simulate, or visualize a physical problem, has revolutionized how physics research is done. Computation is used widely to model systems, to simulate experiments, and to analyze data. Yet, in most…
Bright clusters of galaxies can be seen out to cosmological distances, and thus they can be used to derive cosmological parameters. Although the continuum X-ray emission from the intra-cluster gas is optically thin, the optical depth of…