ARCSAT paper

Contents

The goal of the ARCSAT observations is for you to produce a scientific-like paper that describes your observations and analysis. The format and contents of the paper are free but please, see the following guidelines:

  • The paper must be individually written even if the observations were done in teams. You can do the data reduction of your data as a team but the analysis, conclusions, and writing must be done individually. You can discuss the analysis with your team but the final paper must be your own work.

  • The paper must not be longer than 4 pages including figures and bibliography. You can use double column if necessary and a font size not smaller than 10pt. You can write the paper with any software you like (Word, LaTeX, etc.) but please make sure that the final product is a PDF. You must include figures and tables as needed in your paper.

  • The paper must include a title, abstract, introduction, methods, results, discussion, and conclusions. You can rename the sections and organise them as you want but your writing must cover those points.

  • In the paper you must discuss your observations, weather, technical issues, etc.

  • The paper must describe the telescope and instrumentation used for the observations (including filters) and characterise the CCD (gain, readout noise, etc.).

  • You must describe the data reductions in detail, issues found, potential improvements, etc.

  • It is OK if you do not reach a result (e.g. if you conclude that it was not possible to determine the period of a variable star) as long as you describe why that is the case and what you would do to improve the analysis, or what additional data you would need to reach a conclusion.

  • You must include the code that you used to reduce and analyse the data as a separate set of files. This can be a Jupyter Notebook or a series of Python files. The latter is preferred. The goal is to provide a set of scripts, properly commented, that could be used by someone else to reproduce your analysis. We will not try to run your code but we will check that it is well documented and that it does all the steps that you describe in the paper.

  • Your code must live in a repository that you created for this project in your personal GitHub account. Include a link to the repository in your paper.

  • The code for the data reduction can be the same for everybody in the team but each person should create their own repository and include their own analysis code.

Submission

The paper is due on June 12th at 5pm PDT. Please, submit your paper in Canvas.