GrayStar: A Web application for pedagogical stellar atmosphere and spectral line modelling and visualisation. GrayStar is a stellar atmospheric and spectral line modelling, post-processing, and visualisation code, suitable for classroom demonstrations and laboratory-style assignments, that has been developed in Java and deployed in JavaScript and HTML. The only software needed to compute models and post-processed observables, and to visualise the resulting atmospheric structure and observables, is a common Web browser. Therefore, the code will run on any common PC or related X86 (-64) computer of the type that typically serves classroom data projectors, is found in undergraduate computer laboratories, or that students themselves own, including those with highly portable form-factors such as net-books and tablets. The user requires no experience with compiling source code, reading data files, or using plotting packages. More advanced students can view the JavaScript source code using the developer tools provided by common Web browsers. The code is based on the approximate gray atmospheric solution and runs quickly enough on current common PCs to provide near-instantaneous results, allowing for real time exploration of parameter space. I describe the user interface and its inputs and outputs and suggest specific pedagogical applications and projects. Therefore, this paper may serve as a GrayStar user manual for both instructors and students. In an accompanying paper, I describe the computational strategy and methodology as necessitated by Java and JavaScript. I have made the application itself, and the HTML, CSS, JavaScript, and Java source files available to the community. The Web application and source files may be found at ishort/GrayStar.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 1 article )

Showing result 1 of 1.
Sorted by year (citations)

  1. C. Ian Short, Jason H.T. Bayer, Lindsey M. Burns: ChromaStarPy: A stellar atmosphere and spectrum modeling and visualization lab in python (2018) arXiv