Computational Physics - Applications of Computational Physics

Applications of Computational Physics

Computation now represents an essential component of modern research in accelerator physics, astrophysics, fluid mechanics, lattice field theory/lattice gauge theory (especially lattice quantum chromodynamics), plasma physics (see plasma modeling), solid state physics and soft condensed matter physics. Computational solid state physics, for example, uses density functional theory to calculate properties of solids, a method similar to that used by chemists to study molecules.

As these topics are explored, many more general numerical and mathematical problems are encountered in the process of calculating physical properties of the modeled systems. These include, but are not limited to

• Solving differential equations
• Evaluating integrals
• Stochastic methods, especially Monte Carlo methods
• Specialized partial differential equation methods, for example the finite difference method and the finite element method
• The matrix eigenvalue problem – the problem of finding eigenvalues of very large matrices, and their corresponding eigenvectors (eigenstates in quantum physics)
• The pseudo-spectral method

Computational physics also encompasses the tuning of the software/hardware structure to solve problems. Approaches to solving the problems are often very demanding in terms of processing power and/or memory requests.