Related papers: Teaching students about informatics and astronomy …
In this paper we have evaluated the amount of available telescope time at four interesting sites for astronomical instrumentation. We use the GOES 12 data for the years 2008 and 2009. We use a homogeneous methodology presented in several…
Asteroids detection is a very important research field that received increased attention in the last couple of decades. Some major surveys have their own dedicated people, equipment and detection applications, so they are discovering Near…
Astronomy has a distinguished tradition of using technology to accelerate the quality and effectiveness of science, and data-intensive initiatives such as the Virtual Observatory lead the way amongst other fields of science. However,…
The accuracy of astrometric observations conducted via a space-borne optical interferometer orbiting the Earth is expected to approach a few microarcseconds. Data processing of such extremely high-precision measurements requires access to a…
The Space Interferometry Mission (SIM) will make precise astrometric measurements that can be used to detect planets around nearby stars. Since observational time will be extremely valuable, it is important to consider how the choice of the…
In this work, we identify elements of effective machine learning datasets in astronomy and present suggestions for their design and creation. Machine learning has become an increasingly important tool for analyzing and understanding the…
There are vast educational research works that highlight the serious difficulties that students present in learning astronomical subjects, as well as the prevalence of a traditional education distanced from the observational and…
Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use…
The next generation of telescopes will acquire terabytes of image data on a nightly basis. Collectively, these large images will contain billions of interesting objects, which astronomers call sources. The astronomers' task is to construct…
In recent years, deep learning has been successfully applied in various scientific domains. Following these promising results and performances, it has recently also started being evaluated in the domain of radio astronomy. In particular,…
Recent advances in our understanding of the Universe have revolutionized our view of its structure, composition and evolution. However, these new ideas have not necessarily been used to improve the teaching of introductory astronomy…
Synthetic tracking (ST) has emerged as a potent technique for observing fast-moving near-Earth objects (NEOs), offering enhanced detection sensitivity and astrometric accuracy by avoiding trailing loss. This approach also empowers small…
Activities related to access to astronomical facilities and data could offer an effective, entry-level path for outreach and astronomy education. The Government of Italy proposed the Open Universe initiative that was adopted by the United…
Radio wavelength astrometry of stars and other objects has a long and productive history. The use of that technique to determine whether stars have planets around them would cover a nearly unique part of the parameter space for detection of…
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 nature of scientific and technological data collection is evolving rapidly: data volumes and rates grow exponentially, with increasing complexity and information content, and there has been a transition from static data sets to data…
The detection and study of extrasolar planets is an exciting and thriving field in modern astrophysics, and an increasingly popular topic in introductory astronomy courses. One detection method relies on searching for stars whose light has…
Machine learning has rapidly become a tool of choice for the astronomical community. It is being applied across a wide range of wavelengths and problems, from the classification of transients to neural network emulators of cosmological…
Astronomical images are of crucial importance for astronomers since they contain a lot of information about celestial bodies that can not be directly accessible. Most of the information available for the analysis of these objects starts…
The recent increase in volume and complexity of available astronomical data has led to a wide use of supervised machine learning techniques. Active learning strategies have been proposed as an alternative to optimize the distribution of…