Course description

ASTR 481 provides a practical, comprehensive introduction to astronomical data analysis and observing techniques. These skills are essential not only to plan and carry out your own astronomical observations but to work with archival data. In this course you will learn:

  • The basics of telescope optics, cameras, coordinate systems, and other observational tools.

  • How CCD cameras work and how to reduce and calibrate CCD data.

  • How to prepare observing proposals and use telescopes.

  • How to carry out your own remote observations using a professional telescope.

  • How to work with catalogue data and databases.

  • How to visualise and plot data.

  • How to reduce and calibrate spectroscopic data.

  • How to present your observational results as a scientific paper.

The highlight of the course are the observations that you will be able to carry out using the ARCSAT telescope at Apache Point Observatory. As part of the course you will develop a research project, write an observing proposal, carry out the observations, reduce your data, and present your results as a scientific paper.

This course is eminently practical and hands-on. Students are expected to be familiar with scientific programming in Python and to be able to work with Unix-like systems. Similarly, students are expected to have a basic understanding of astronomy and be able to identify a topic of research and analyse the results independently.

More details about the course contents can be found in the course schedule.

Things to know

  • Webpage: Most of the lectures and materials will be provided in the course website. We will generally only use Canvas for announcements.

  • Textbook: There is no required textbook for this course. All the materials will be provided online. Each lesson will have a list of references and further reading.

  • Late assignments: Late assignments delivered within 24 hours of the due date will be penalised 20% of the total grade. Assignments delivered after 24 hours will not be accepted.

  • Computing: A computer will be needed for this course. We will provide a cloud-based computing environment that you can use, but you are welcome to use your own computer. Tablet and mobile devices are unlikely to be sufficient to complete the assignments. If you need to borrow a computer for this course check the UW Student Technology Loan Program or reach out to the instructor.

  • Academic honesty: You are encouraged to discuss the assignments with your classmates, but the final work must be your own, including in assignments where part of the work will be done in a group. Cheating and/or plagiarism is not tolerated. The examples of academic misconduct in the statement of Student Academic Responsibility are useful for understanding how to avoid plagiarism. If we suspect academic misconduct then we will withhold your grade and report the suspected activity to Community Standards & Student Conduct.

  • Use of AI: The use of AI tools is not allowed in this course. Limited-scope AI tools (for example code auto-completion or Copilot) can be used as long as the student is the one writing the code. Chat bots are not allowed.

  • The University of Washington Department of Astronomy does not tolerate harassment of any kind: Harassment is any behaviour by an individual or group that contributes to a hostile, intimidating, unwelcoming, and/or inaccessible work environment. Anyone can experience harassment. If you believe that you are being harassed, please consult the UW anti-harassment resources and don’t hesitate to contact the instructors.

  • We follow UW Policies: We follow the UW’s guidelines for faculty, including not requiring notes from doctors. For a full list, see UW Syllabus Guidelines and Resources.

Assignments

The course consists of a series of graded assignments due approximately every two weeks. The assignments will follow the practical lectures and require you to develop Python code to analyse astronomical data. For each assignment we will provide a base repository with the necessary data, a set of instructions, and a rubric.

Approximately one week of the beginning of the ARCSAT observations each group will submit an observing proposal. The final project will be due on June 12 and will consist of a paper-like report of the observations, data reduction, and analysis of the proposed project, along with the code used for the analysis. With the exception of of the observing proposal all assignments are individual.

There will be no exams in this class.

Grading

Grading will be based on class participation (10%) and the assignments (90%), of which the final project is worth 40%. The value of each assignment will be provided in the assignment instructions.

Your final grade is determined by transforming your overall percentage to the 4.0 scale. A percentage score of at least 60% is required for credit. A score of 70% guarantees a 2.0 or higher, an 80% guarantees a 3.2 or higher, and a 95% guarantees a 4.0. Note that a 2.0 or higher is required to receive credit toward the astronomy degree, or if you have chosen Satisfactory/Not-Satisfactory grading.

Accommodations & Support

This class provides accommodations for temporary health conditions and permanent disabilities through UW DRS. Support is available to discuss safety and well-being 24 hours / 7 days a week through SafeCampus.

Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organised religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.