Background: computational condensed matter physics

In summary, a PhD in computational physics would require expertise in FORTRAN programming, as well as knowledge in a certain area of physics.
  • #1
teame Yitbarek
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0
I have my MSc in 'Computational condensed matter physics'. I used VASP package for simulation during my MSc. and i am also well experienced in FORTRAN programming language. Can anyone give me short note about 'PhD in computational physics'? so that can continue my PhD in 'Computational Physics'.
 
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  • #2
Summary:: Interested in doing 'PhD in Computational Physics' .

I want to discuss about computational physics for PhD. i have an experience in FORTRAN, vasp. what example titles or areas of study are there in computational physics (PhD)?
 
  • #3
Do not restrict yourself to computational physics. Many researchers in astrophysics that I know did much of their work running models written in FORTRAN. I think the same could be said for fluid dynamics, theoretical nuclear physics, geodesy, chaos, perhaps numerical relativity, and mathematics. You may be able to approach a research advisor or an employer more broadly. For example, if your MS was solving a transport problem in solid state physics, you may find a nuclear physics position interesting, in that a similar transport problem. Nucleons move, and stars move too. The downside is you will have to develop expertise in another area.

In short, I think you may have a hard time finding a position in doing computational physics alone, if you mean solely developing algorithms to calculate physical quantities easily. You may need to find a allied field to apply the computational physics to.

Many so called "modern" programmers are pushing python right now.

However, a lot of earlier (legacy) code is in FORTRAN. I find organizations need (unfortunately they do not always value as much as I think they should) scientists that can program and know FORTRAN enough to understand what the old code did? Why the software was important, and how it can be used effectively in the future? Without knowing these answers, rewriting the code in a "modern" language is pointless.
 
  • #4
I second that you should under no circumstances limit yourself to Computation. I myself have done my masters on nested sampling (Python and very little fortran). For Condensed matter, I would suggest you look into DFT (there's a lot of mathematics that lends well to Computation), and some abstract topics. I would suggest you put the what before the how and computation is pretty much the how.
 

Related to Background: computational condensed matter physics

What is computational condensed matter physics?

Computational condensed matter physics is a branch of physics that uses computer simulations and mathematical models to study the properties of materials at the atomic and molecular level. It involves the use of algorithms and computer programs to simulate and analyze the behavior of materials under various conditions.

What are the applications of computational condensed matter physics?

Computational condensed matter physics has a wide range of applications, including the study of electronic, magnetic, and optical properties of materials, the design of new materials for various industrial and technological purposes, and the understanding of complex phenomena such as phase transitions and superconductivity.

What are the main techniques used in computational condensed matter physics?

The main techniques used in computational condensed matter physics include density functional theory, molecular dynamics simulations, Monte Carlo simulations, and quantum mechanical calculations. These techniques allow scientists to model and analyze the behavior of materials at the atomic and molecular level.

What are the advantages of using computational methods in condensed matter physics?

Computational methods offer several advantages in condensed matter physics, including the ability to study complex systems that are difficult to observe experimentally, the ability to control and manipulate parameters to understand the underlying mechanisms of material behavior, and the ability to quickly and efficiently analyze large amounts of data.

What are the challenges in computational condensed matter physics?

Some of the challenges in computational condensed matter physics include the need for accurate and efficient algorithms, the difficulty of accurately representing complex systems, and the limitations of current computational power. Additionally, the interpretation of simulation results and their comparison to experimental data can also be challenging.

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