Research Methods: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
|||
| Line 30: | Line 30: | ||
*[http://matplotlib.org/ Matplotlib] | *[http://matplotlib.org/ Matplotlib] | ||
*[http://www.stsci.edu/institute/software_hardware/pyfits Pyfits] | *[http://www.stsci.edu/institute/software_hardware/pyfits Pyfits] | ||
*[http://scikits.appspot.com/scikits Scikits - Scipy toolkits | |||
== Web Application Programming == | == Web Application Programming == | ||
Revision as of 06:56, 16 January 2013
This course is a topical survey of research methodologies that in the Spring 2013 term are drawn primarily from astronomy and astrophysics, but are broadly applicable for graduate students who are engaged in doctoral level research in the physical sciences and engineering. With the objective of providing useful tools and a perspective on how advanced scientific research is conducted, we will cover three topics:
- Syllabus
- On-line resources, databases, and use of LaTeX for scientific writing (Williger)
- Programming with Python for data analysis, modeling, and instrument control (Kielkopf)
- Elements of optical spectroscopy and statistics (Lauroesch)
This is a required course for students in the doctoral program in Physics & Astronomy.
On-Line Resources
- Writing with LaTeX
- NASA Astrophysics Data System Abstract Service (ADS)
- New astrophysics papers on arxiv.org's astro-ph
- SIMBAD astronmical database
- Coordinated universal time (UTC)
- Space Telescope Science Institute
- Mikluski Archive for Space Telescopes (MAST)
- Sloan Digital Sky Survey
Python External Sites
- Python official website
- Python tutorial
- Python language reference
- Numpy
- Scipy
- Matplotlib
- Pyfits
- [http://scikits.appspot.com/scikits Scikits - Scipy toolkits