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Difference between revisions of "Research Methods"

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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:
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This course is a topical survey of research methodologies that in the Spring 2017 term focused on computing and programming methods  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 in roughly 5 week sequential segments:
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* Python and javascript for data analysis, instrument control, and image processing (Kielkopf)
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* Advanced Python (Freelon)
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* Root (Banerjee)
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Some on-line course materials are here:
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* [http://prancer.physics.louisville.edu/classes/650/syllabus/p650_sp17.pdf Syllabus]
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* [http://prancer.physics.louisville.edu/astrowiki/index.php/Python_for_Physics_and_Astronomy Programming with Python for data analysis, modeling, and instrument control (Kielkopf)]
  
*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.
 
This is a required course for students in the doctoral program in Physics & Astronomy.
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== Useful On-Line Resources  ==
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*[http://prancer.physics.louisville.edu/classes/650/latex/index.html Writing with LaTeX]
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*[http://adswww.harvard.edu/ads_abstracts.html NASA Astrophysics Data System Abstract Service (ADS)]
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*[http://arxiv.org/list/astro-ph/new New astrophysics papers on arxiv.org's astro-ph]
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*[http://simbad.u-strasbg.fr/simbad/ SIMBAD astronomical database]
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*[http://www.time.gov/timezone.cgi?UTC/s/0/java Coordinated universal time (UTC)]
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*[http://www.stsci.edu/ Space Telescope Science Institute]
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*[http://archive.stsci.edu/ Mikluski Archive for Space Telescopes (MAST)]
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*[http://www.sdss.org/ Sloan Digital Sky Survey]
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== Python External Sites ==
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*[http://www.python.org/ Python official website]
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*[http://docs.python.org/2/tutorial/ Python tutorial]
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*[http://docs.python.org/2/reference/ Python language reference]
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*[http://www.numpy.org/ Numpy]
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*[http://www.scipy.org/ Scipy]
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*[http://matplotlib.org/ Matplotlib]
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*[http://www.stsci.edu/institute/software_hardware/pyfits Pyfits]
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*[http://www.astropy.org/ Astropy]
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*[http://scikits.appspot.com/scikits Scikits - Scipy toolkits]
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*[https://www.enthought.com/academic-subscriptions/ Enthought academic Python distribution]
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== Web Application Programming ==
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*[http://www.w3schools.com/js/default.asp JavaScript tutorial]
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*[https://threejs.org/ Threejs.org]

Latest revision as of 04:23, 12 August 2017

This course is a topical survey of research methodologies that in the Spring 2017 term focused on computing and programming methods 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 in roughly 5 week sequential segments:

  • Python and javascript for data analysis, instrument control, and image processing (Kielkopf)
  • Advanced Python (Freelon)
  • Root (Banerjee)

Some on-line course materials are here:


This is a required course for students in the doctoral program in Physics & Astronomy.


Useful On-Line Resources

Python External Sites


Web Application Programming