Need an idea for a computational physics project

In summary, the individual is seeking ideas for a final project for their computational physics course. They have limited experience in physics, having only taken introductory courses and are currently in modern physics. They initially considered using a genetic algorithm to design an antenna, but found it to be more complicated than expected. They are now looking for suggestions for an interesting project that they can complete quickly. Some potential ideas include computationally calculating electric fields, using Monte Carlo to determine coefficients of best fit, and illustrating diffusion through finite element techniques. The individual has a background in computational physics and has completed similar projects in the past.
  • #1
xbomber88
43
0
I need an idea for a final project for my computational physics course. The problem is that I've only had intro mechanics and intro E&M courses so far and I'm currently taking modern physics. It seems like any interesting projects would require more physics than I've had so far. I was thinking of using a genetic algorithm to design an antenna but then I discovered that antennas are actually a lot more complicated than I had imagined. So now I'm back to square one and need to come up with something quickly because I'm running out of time. Can anyone think of some ideas for an interesting project that someone with my background in physics could do?
 
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  • #2
You could computationally calculate the electric field of an "ugly" charge configuration with no standard symmetries.
 
  • #3
I remember in my computational physics course i wrote a simple code to calculate Rayleigh scattering (it does indeed work). I also wrote a polynomial curve fitting program that used Monte Carlo to determine the coefficients of best fit. You could also do a simple illustration of diffusion by using finite element techniques (i.e. discretize the equations of motion) of a bunch of particles and start them in a far corner of an empty box and see how they evenly disperse themselves. I could think of quite a few more if these are the kind of things you were considering (my undergrad degree was actually in Computational Physics so I've done a lot of these sort of projects).
 

1. What is computational physics and how is it different from traditional physics?

Computational physics is a branch of physics that uses numerical methods and computer simulations to solve complex physical problems. It differs from traditional physics in that it involves using computers to model and analyze physical systems, rather than relying solely on theoretical equations and experimental data.

2. Why is it important to have computational physics projects?

Computational physics projects allow scientists to study physical phenomena that are difficult or impossible to observe in real life. They also provide a way to test theories and models, improve our understanding of complex systems, and make predictions about future behavior.

3. What are some examples of computational physics projects?

Some common examples of computational physics projects include simulating the behavior of fluids, modeling the motion of celestial bodies, and studying the properties of materials at the atomic level. Other projects may involve using computational methods to solve equations in quantum mechanics, thermodynamics, or electromagnetism.

4. How can I come up with an idea for a computational physics project?

One way to come up with ideas for a computational physics project is to think about a physical phenomenon that interests you and then consider how you could use computer simulations to study it in more detail. You can also look for gaps in current research or areas where computational methods have not yet been applied.

5. What skills are needed to work on a computational physics project?

A strong foundation in physics and mathematics is essential for working on a computational physics project. You should also have programming skills, as most projects involve writing code to implement simulations and analyze data. Additionally, knowledge of numerical methods and computer science can be beneficial.

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