Computational physics course or numerical analysis course

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SUMMARY

The discussion centers on the decision between enrolling in a computational physics course versus a numerical analysis course at the graduate level. The individual has a background in computational physics and experience with MATLAB and the SciPy library but lacks a deep understanding of numerical methods such as Newton's method and interpolation. The consensus among respondents suggests that while computational physics may cover some numerical analysis concepts, a dedicated numerical analysis course would provide a more thorough understanding of the underlying algorithms and techniques necessary for implementing custom solutions in scientific computing.

PREREQUISITES
  • Understanding of linear algebra and differential equations
  • Familiarity with MATLAB and SciPy for scientific computing
  • Basic knowledge of numerical methods such as root finding and interpolation
  • Experience in computational physics research
NEXT STEPS
  • Explore the curriculum of a graduate-level numerical analysis course
  • Study Newton's method and its applications in root finding
  • Learn about implicit ODE algorithms and their implementations
  • Investigate quantum Monte Carlo methods in condensed matter physics
USEFUL FOR

Graduate students in physics or mathematics, computational physicists, and researchers looking to deepen their understanding of numerical methods and their applications in scientific computing.

td21
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A question for those who are computational physicist:
Dear Computational physicist,
I am struggling between computational physics course or numerical analysis. They are both in graduate level (so very intensive), one in physics department and another in math. Both are taught by leading experts in scientific computing field.

I have 3 plus years in computational physics research background and recently finished a parallelized research project. The reason I want to take these courses is in the past I use MATLAB functions, scipy library to do integration, root finding and stuff, but actually I do not really understand the inner working. So for example if i want to implement my own implicit ode algorithm , I cannot but just copy it from somewhere else and unable to develop my own to suit my specific problem.

I am also not familiar with Newton's method, interpolation and root finding as in numerical analysis, but very familiar with linear algebra and somewhat familiar with differentiation, integration and differential equations (I read these chapters from a numerical analysis book) . On the other hands, I am not interested in molecular dynamics or chemistry stuff, but I am interested in quantum monte carlo in condensed matter physics. Will computational physics also cover basic numerical analysis?

I also want to ask: Which one do you take in the past? or did you take both?

Thank you very much for your advice.
 
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It would help if you could list the contents of the courses.
 

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