Observing and Modeling the Universe
Class handouts and assignments
- Course Information and syllabus
(handout at first class; updated November 16)
- Our textbook, Statistics, Data Mining, and Machine
Learning in Astronomy is available
(this may require using a Princeton computer).
- Homework 1, due Monday, September
26, in class.
- Solutions to Homework 1.
- Homework 2, due Wednesday, October
- The quasar spectrum needed for
Homework 2. This is a spectrum from the SDSS; the columns are
wavelength, flux density (in units of 10-17erg/s/cm2/A),
flux density error (same units), and a mask that indicates possible problems
with each pixel. For this homework, you need only use the
first two columns of data.
- Solutions to Homework 2, together
with the Python code needed to do Problems 1 and 2.
- Homework 3, due Monday, October
- The A star spectrum needed for
Homework 3. First two columns are wavelength in Angstroms and flux density
(in units of 10-17erg/s/cm2/A).
- Solutions to Homework 3, together
with the Python code needed to do Problem 3.
- Homework 4, due Monday, November
- Solutions to Homework 4, together
with the Python code needed to do Problem 4.
- Homework 5, due Thursday, November
13. The data file needed for Problem 1.
- Solutions to Homework 5, together
with the Python code needed to do Problem 1.
- Homework 6, due Wednesday, November
- Solutions to Homework 6
- Homework 7, due Tuesday, January 17
(Dean's Date; hand into Michael's office), together with
the sky spectrum needed for Problem 3.
- Resources for the final JWST proposal
project (updated December 1).
Computers and Python resources
- A description of how to get started using
computers in Peyton Hall, including information on python.
- A brief introduction to Unix at
Princeton, by Robert Lupton and Jill Knapp.
- An introduction to X windows (the
window-manager system that many of the computers in the building use), by Robert Lupton.
- An alternative
introduction to Unix; the bare minimum is contained in the first five tutorials.
- A General Introduction
to Python, including numpy and SciPy.
- Programming in
Python, for astronomers.
for Data Analysis, a 470-page textbook available online.
- An introduction to
- Astropy, a project for
building useful utilities for astronomers in Python.
- There is a
associated with the book A Student's Guide to Python for Physical
- AstroML is a website
accompanying the book Statistics, Data Mining, and Machine Learning
ipython notebooks from Jake Vander Plas.
and Python reference page from Physics 209.
- The NIST Digital Library of
Mathematical Functions, an update of the classic handbook by
Abramowitz and Stegun.
- The Second Edition of Numerical Recipes (i.e., not the latest
version) is available for free on the
web in C, Fortran 77, and Fortran 90.
General Astronomy Resources
- Useful astronomical
links. These are from AST 203, so tend to the elementary, and are
a bit dated...
White Papers for the James Webb Space Telescope.
- The weekly
calendar of astrophysics-related talks in the Princeton area.
- ArXiv, the repository of the daily
preprints of the astrophysics community, often referred to as
"astro-ph". There is a page describing how to sign
up to receive a daily update of astrophysics papers, and a website organizing
the Peyton Hall daily discussion of these papers.
- The Astrophysics Data
System, a portal to essentially the complete journal literature of
- AstroBetter, a blog where
professional astronomers share tips and tricks forbeing successful
in the astronomy world.
- Astrobites, a website
run by grad students for undergrads, where they
summarize interesting astro-ph articles and provide general tips.
- The full, downloadable report of ASTRO2010,
The Astronomy and Astrophysics Decadal Survey, and the
Michael Strauss and