ASTR 306/406 - Astronomical TechniquesT/Th 11:30-12:45am, Sears 552
This course will focus on research techniques used by astronomers, including observational studies using ground- and space-based telescopes, and data mining of large on-line astronomical datasets. We will also emphasize the variety of technical writing that astronomers do, including observing/funding proposals, journal articles, and technical reviews. This course is an approved SAGES departmental seminar.
No required textbooks. Readings will come from a variety of sources available online and in the astronomy lab and library.
This course will involve hands-on data analysis, in-class group work, and class discussions. These kinds of interactive class activities cannot be made up, and therefore on-time attendance is required. Absences will be noted, as will late arrivals, and attendance will be factored into the final course grade (see below).
There will be a variety of homework sets geared towards the development of technical skills. These assignments will often be coordinated with in-class activities. Typical assignments could include conducting a simple photometric analysis of astronomical image data, or downloading and analyzing appropriate astronomical datasets off of the web.
In addition, there will be several writing assignments throughout the semester which might include
General tips on HW assignments.
Submitting Assignments: Assignments should be turned in by 4pm on the due date. Hardcopy only; electronic files are not accepted unless specifically requested.
ASTR 406: Graduate students will have additional problems assigned, and will be asked to do more in-depth analysis and interpretation of data.
Late Homework Policy: You get one "free" late homework, which must be turned in no later than one week past the due date. After that, there will be a penalty of 20% for every day late, unless you have a prearranged, excused reason. Note: Your "free" late homework cannot involve assignments marked with "no extensions".
Final grades are based on a weighted average of course assignments (with weights as given in the Assignments section). There are no exams. The grading scheme works as follows:
Unexcused absences will impact your score roughly as follows:
Programming and data analysis will be required. I strongly encourage you to install the Anaconda python distribution on your computer, which also installs the astropy package by default.
We will also work with the data reduction package PyRAF. You do not need to install it on your own machine; it will be available for use in class on the linux workstations in the classroom.
If you do not have an account on our linux workstations, please see Charley Knox (Sears 568) to get set up ASAP.
|Course Schedule / Topic List
|Assignments (due dates subject to change)
Assignments are due at 4pm on the specified date.
Group Work Teams
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