Applications of computational physics?

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Discussion Overview

The discussion centers around the practical applications of computational physics across various fields, including materials science, experimental physics, and finance. Participants explore how advancements in computing power and algorithms have enabled more complex modeling and simulations in research.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants suggest that computational physics has applications in nearly all areas of physics research, particularly through the use of computer simulations to compare with experimental data.
  • One participant mentions using particle-in-cell (PIC) simulations to model complex situations in tokamak experiments, highlighting the limitations of analytical solutions.
  • There is a significant amount of computational work in condensed matter physics, focusing on aspects like electron structures and dielectric constants.
  • Another participant points to resources from the American Physical Society (APS) that provide links to various branches of physics, including computational physics.
  • Some participants note that computational physicists often transition to fields like finance, where they model complex, non-linear behaviors, using techniques such as Ising Models to analyze socio-economic variations.

Areas of Agreement / Disagreement

Participants generally agree on the broad applicability of computational physics but express varying perspectives on specific fields and examples. The discussion remains open-ended with no consensus on a definitive list of applications.

Contextual Notes

Limitations include the dependence on specific examples and the varying levels of detail provided by participants regarding different applications. Some claims may rely on assumptions that are not explicitly stated.

Who May Find This Useful

Researchers and students interested in the applications of computational physics in various fields, including materials science, experimental physics, and finance, may find this discussion valuable.

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What are some of the more practical applications, if there are any, of computational physics?
 
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Actually I can think of quite a lot - and this is mostly possible due to the increases in computing power and better algorithms over the last 2 decades.

Here is a good overview from Caltech - http://library.caltech.edu/sherman/collections.htm

Science and engineering memebers of the Materials Research Society publish quite a lot about computational physics as applied to materials - e.g. http://www.mrs.org/meetings/spring2000/program/updsym/ProgramBookO.html

I am sure ZapperZ and Gokul could add quite a bit on this subject.
 
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Computational physics has applications to pretty much all research going on in physics. Typically you can use more complex models to compare with experiment by using computer simulations. I'm doing stuff like this right now involving some probes on a tokamak. The situation in the vicinity of the probe is just too complicated to come up with any sort of decent analytical solution, so it turns out that it is better to use what is called a particle-in-cell (PIC) simulation to model the situation in order to interpret the data collected by the probe.
 
There's huge amount of computational work done in condensed matter physics. Electron structures, dielectric constants and so on..
 
My standard answer in something like this is to to go the American Physical Society website (www.aps.org) and look at the specific division/units under the APS. Practically all branches of physics are represented here. If you go to each of the division/units page, you'll find a wealth of links for that particular field of study.

For example, you'll find this for the Divisionn of Computational Physics

http://www.aps.org/units/dcomp/

Zz.
 
A reasonable number of computational physicists switch fields and work in Wall-Street (or elsewhere in the finance sector) modeling extremely complex, non-linear behavior.

http://guava.physics.uiuc.edu/~nigel/finance.html

http://www.google.com/search?hl=en&q=physicist+finance+modeling&btnG=Google+Search

The point is that, as a computational physicist, you learn to model very tricky stuff. For instance, there's a grad student in my dept. (Physics) using Ising Models and related statistical mechanics methods to simulate and predict geographical variations in socio-economic behavior.
 

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