Astronomy is an observational science – few experiments are
possible, and theory serves more to explain than to predict new
phenomena. As a result, it is important for everyone
involved in gathering and interpreting data to understand
something about the instruments which filter our view of the
Universe. In this course, we cover the basic principles of
instrumentation and the associated techniques involved in
recovering data from distant objects. We will discuss physical
limits on ideal instruments and some of the real imperfections
that can lead to real systematic effects. The goal of this
course is to understand instrumentation as a coherent whole,
differing only in details from one part of the spectrum to
another. We will draw heavily on examples from the radio
through optical wavelengths to illustrate the basic principles of
instrumentation, but we will also discuss other parts of the
spectrum (UV, X-ray, and gamma-ray) to show how technical details
differ in these regions. This course also includes a review
of basic statistics applied to signal and data analysis.
My expectation is that the students will conduct themselves as graduate students. This means putting electronic distractions to the side during the lectures, following the lecture material, following and reading references after lectures, and in general demonstrating curiosity. Assignments are individual, and should be completed by students independently. That does not mean that students should not be talking to each other about what they are doing (on the contrary, your objective should be to learn!), but it means that each one should arrive at the solutions through their own thought process and understanding (otherwise you are not learning!). I expect students will be curious enough to go above and beyond what I ask in the homeworks, rather than just following my script. Instead of worrying about the grade, worry about exploring and learning and the grade will come with that!
The class meets in room 0201 of the Atlantic
Building from on Tuesdays and Thursdays 2:00-3:15 pm
(14:00-15:15). Because of some travel commitments, a
few individual classes (marked with * in the calendar) will have to be scheduled to other mutually
agreeable times. Classes will consist primarily of intensive
lectures and, I hope, equally intensive questions and discussions
as we move through the course material.
Questions about lecture and problem sets or other topics are
strongly encouraged. Given everyone's varied schedules, we
will do this by appointment or by random encounter. Please
come ask questions early as they emerge. The hour or two
before class on the days problem sets are due seem to be popular
times for questions, but are difficult for me as I prepare for the
lecture. My email, phone, and office number are at the top
of this page.
There will be regular (approximately biweekly) homework
assignments that will count for 40% of the course grade. You
should anticipate spending a considerable amount of time on the
assignments – this is, of course, where you will learn the most.
A number of the homework assignments involve computer
programming. As part of the coursework, I require use of a
higher-level language such as MATLAB, Phython, IDL, or R Python
because of their extensive data manipulation and display
capabilities. There will be two exams: a mid-term exam
which counts for 25% of the course grade and a final exam that
counts for 35%. Both examinations count as Major Grading
Events as defined by the university. A good number of the
problems on these exams will be in the format of the Qualifying
Examination for the Department of Astronomy. As is usual for
graduate classes, I expect that most students will receive an A or
Since we are not following a textbook for this class, attendance
and careful note taking is essential. If you must miss a
class, please arrange to get notes from one of your classmates and
plan to come talk with me about points you find unclear. If
you know you will be away for university-related travel or
religious holidays, please let me know as soon as possible
(technically, within the first two weeks of the semester) so we
can arrange alternate scheduling of homeworks or
exams. This same timeframe holds for students who need
accommodation for documented disabilities.
There are no required
texts for this class. We cover too much ground at too many
levels for one text to suffice, and purchasing an entire set of
texts would be financially ruinous. Here
is a list of my favorite reference books for this class. You may wish to build you library with
one or two of them, depending on your interests.
Bracewell: The Fourier Transform and
its Applications, 3rd Edition.
This wonderful book covers both theory and applications of the Fourier transform.
James, A Student’s Guide to Fourier
Transforms With Applications in Physics and Engineering
A very nice introduction to Fourier transforms and their uses. Paperback: cheap!
A particularly clearly written optics book with considerable information on modern and classical optics.
Born and Wolf, Principles of Optics
Advanced topics in diffraction and other optical theory, optical interferometers.
Schroeder: Astronomical Optics
This book covers astronomical optical systems, telescopes, and spectrometers in considerable technical detail.
Thompson, Moran, Swenson:
Interferometry and Synthesis in Radio Astronomy
Detailed discussions of radio interferometers at a fundamental but advanced level. An indispensable reference for practitioners.
Rohlfs & Wilson: Tools of Radio
This book covers instrumentation and techniques from the radio astronomical perspective, as well as discussing radiation mechanisms and radio astronomy in general.
Rieke: Detection of Radiation
Covers the detection of radiation from radio to gamma rays.
Howell: Handbook of CCD Astronomy
CCD operation, data processing, and instruments.
Ross: Introduction to Probability and
Statistics for Engineers and Scientists
Very clear exposition of classical elementary statistics at the upper-division undergraduate level.
Dalgaard: Introductory Statistics
Clear introduction to statistics common for data analysis and the R language. Most of the examples are geared toward the biological sciences, where R is very popular, but the basics are the same for all sciences.
Lupton: Statistics in Theory and Practice
Intermediate-level statistics book that covers more advanced topics in data analysis with astronomical examples.
Seidelmann: Explanatory Supplement to
the Astronomical Almanac
A fundamental reference for fundamental observers – coordinate systems and transformations, time systems, precession, etc.