Now and then someone in my family or an acquaintance asks me what I do. Typically the conversation goes: "Science; I do research". "So you wear a lab coat all day?" "No, not that kind of science". "Do you build bombs/spread uncurable diseases?". I wrote up a few things to answer those kinds of questions.
- Hot Stuff: an article I wrote for Physics News (published by the Indian Physics Association) in October 2012 explaining my work on the statistical mechanics of elementary particles, and how it relates to the properties of matter found in the first microsecond after the big bang.
- Chiral Symmetry: an introduction to the subject which I gave to undergraduate students.
- An introduction to particle physics: the power point of a talk I gave a couple of times to undergraduate students.
- Symmetries of particle physics: space-time and local gauge symmetries: an article in Resonance based on a talk I gave in IIT Bombay.
- Plasmas: using dimensional analysis to understand this state of matter: an article I wrote for Physics Education (Univ of Pune).
- The convoluted history of the strong interactions, or how the universe got its mass
From time to time I give courses for research students. These can be accessed in a separate web page.
Statistical analysis and probability
Much of the grungy work in science, whether you do experiments or computer simulations, has to do with questions of statistical accuracy. Here is a tutorial which introduces you to modern methods of statistical analysis. This was part of a course on statistical mechanics which I'd given in 1995. You might also want to look through an introduction to probability and statistical analysis, which was part of a course I'd given in 2002.
The Mathematica computer algebra system is currently very useful (in spite of its high cost, many people prefer it to its peers, at least for now). Here is a notebook which you can use as a quick Mathematica tutorial.
You'll spend a lot of time writing up accounts of your work. The best system for doing this is TeX. Here is an example file which some have found useful: compare the source and the pdf output to see what construct gives rise to which effect.
Writing a paper
What are you most likely to write? A paper, of course. There are simple ways to make this complicated and tedious job into a simple and straightforward task. Here is a tried-and-tested method.
Here is a list of the essential papers on a few useful topics:
- The phase diagram of QCD
- The generation and testing of random numbers
- The colour octet model for quarkonia
The wide use of computers and even wider mobile computing devices (laptops, cell phones, etc) could be harnessed to teach physics. A few years ago I organized a discussion meeting with teachers in order to share experiences and set up a dialogue. The proceedings are here.
In teaching quantum mechanics an emphasis on symmetries is an old pedagogical method. It was developed beautifully by Feynman in the simplest of contexts: a two-state system. Since then this example has become a staple of text books. I gave an introductory course in quantum mechanics in 2008 where I used this example and introduced SU(2) early on as the unitary evolution operators for these two state systems. Then, while teaching angular momentum, I introduced direct products and their reduction to bypass traditional methods of teaching Clebsch-Gordan coefficients. What would have been a very abstract view of group theory earlier, was made totally concrete by the use of computer algebra systems to reduce direct products to direct sums. My course notes show how I developed this. I would be happy to hear from you if you want to try this out, or have already done something like this.
In teaching numerical analysis to physics students, the emphasis is often laid on efficient programming and solution of programming problems. It has also become fashionable to convert this to something called "Computational Physics" where physics problems are solved, largely using black boxes for programs. I tried to negotiate a middle path where I recognized that most students will now not code the algorithm, but will take it as a black box from some source. I tried to build a numerical analysis course in 2010 whose main motivation was two-fold: analysis of error propagation and prior estimations of program run times. My course notes show how I developed this. I would be happy to hear from you if you want to try this out, or have already done something like this.
Copyright: Sourendu Gupta ; Last modified on 22 May, 2019.