Research Methods
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This course is a topical survey of research methodologies that in the Spring 2015 term are drawn primarily from optical physics, 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:
- Python for data analysis, instrument control, and image processing (Kielkopf)
- Lasers (Mendes)
- Ultrafast optics (Smadici)
Course materials are here:
- Syllabus
- Programming with Python for data analysis, modeling, and instrument control (Kielkopf)
- Upload Python homework
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
- Scikits - Scipy toolkits
- Enthought academic Python distribution