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In this article we describe how we successfully incorporated data analysis in Python in a first-year laboratory course without significantly altering the course structure and without overburdening students. We show how we created and used…
Xsuite is a newly developed modular simulation package combining in a single flexible and modern framework the capabilities of different tools developed at CERN in the past decades, notably Sixtrack, Sixtracklib, COMBI and PyHEADTAIL. The…
We present Artificial Stellar Populations (ArtPop), an open-source Python package for synthesizing stellar populations and generating artificial images of fully populated stellar systems. The code is designed to be intuitive to use and as…
Research into the processes of photoionised nebulae plays a significant part in our understanding of stellar evolution. It is extremely difficult to visually represent or model ionised nebula, requiring astronomers to employ sophisticated…
Spectroscopic observations of exoplanet atmospheres can reveal the chemical composition, temperature, cloud properties, and (potentially) the habitability of these distant worlds. The inference of such properties is generally enabled by…
Thin film technology is a most relevant field in terms of number of different applications and, even more, in how widespread the use of the technology is. Virtually all optical devices involving light beams or with imaging capabilities…
swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidates functionality across multiple domains, including data…
HIPSTER (Heavily Ionising Particle Standard Toolkit for Event Recognition) is an open source Python package designed to facilitate the use of TensorFlow in a high energy physics analysis context. The core functionality of the software is…
Space weather is a rapidly growing area not only in scientific and engineering applications but also in physics education and in the interest of the public. We focus especially on space radiation and its impact on space exploration. The…
Hands-On Universe (HOU) is an educational program that enables students to investigate the Universe while applying tools and concepts from science, math, and technology. Using the Internet, HOU participants around the world request…
This paper presents the philosophy, design and feature-set of Neural Network Distiller, an open-source Python package for DNN compression research. Distiller is a library of DNN compression algorithms implementations, with tools, tutorials…
We present a new Python pipeline for processing data from astronomical long-slit spectroscopy observations recorded with CCD detectors. The pipeline is designed to aim for simplicity, manual execution, transparency and robustness. The goal…
The ThEdu series pursues the smooth transition from an intuitive way of doing mathematics at secondary school to a more formal approach to the subject in STEM education, while favouring software support for this transition by exploiting the…
The Lecture-Tutorials for Introductory Astronomy have been designed to help introductory astronomy instructors actively engage their students in developing their conceptual understandings and reasoning abilities across a wide range of…
Eventdisplay is a software package for the analysis and reconstruction of data and Monte Carlo events from ground-based gamma-ray observatories such as VERITAS and CTA. It was originally developed as a display tool for data from the VERITAS…
We present ZodiPy, a modern and easy-to-use Python package for modeling the zodiacal emission seen by an arbitrary Solar System observer, which can be used for the removal of both thermal emission and scattered sunlight from interplanetary…
Astronomy and astrophysics are witnessing dramatic increases in data volume as detectors, telescopes and computers become ever more powerful. During the last decade, sky surveys across the electromagnetic spectrum have collected hundreds of…
Galaxy morphological classification is a fundamental aspect of galaxy formation and evolution studies. Various machine learning tools have been developed for automated pipeline analysis of large-scale surveys, enabling a fast search for…
One of the most computationally demanding aspects of the hydrodynamical modelling of Astrophysical phenomena is the transport of energy by radiation or relativistic particles. Physical processes involving energy transport are ubiquitous and…
We introduce GalaxyGenius, a Python package designed to produce synthetic galaxy images tailored to different telescopes based on hydrodynamical simulations. Its implementation will support and advance research on galaxies in the era of…