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, including:
BGO: Observational Astronomy, by Birney, Gonzalez, and Oesper
Chromey: To Measure the Sky, by Frederick Chromey
Howell: Handbook of CCD Astronomy
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 need an account set up on our linux workstations, please see Charley Knox (Sears 568) to get set up ASAP.
|Computer Lab Support:
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 be used on assignments marked with "no extensions".
|Assignment Schedule (due dates subject to change)
Assignments are due at 4pm on the specified date.
Group Work Teams
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. Unexcused absences will impact your score roughly as follows, with late arrivals (>10 mins late) counting as half an absence:
10 or more absences will result in a failing class grade, regardless of performance on written assignments
Final grades are based on a weighted average of course assignments (with weights as given in the Assignments section), modified by the attendance score. There are no exams. The grading scheme works as follows:
|Course Schedule / Topic List
(Italicized topics and links means the material is from previous edition of course and is subject to change.)
After taking this course, students should be able to: