Computational physics is the study and implementation of numerical algorithms to solve problems in physicstheoretical physics but some consider it an intermediate branch between theoretical and experimental physics. for which a quantitative theory already exists. It is often regarded as a subdiscipline of
Physicists often have a very precise mathematical theory describing how a system will behave. Unfortunately, it is often the case that solving the theory's equations ab initio in order to produce a useful prediction is not practical. This is especially true with quantum mechanics, where only a handful of simple models have complete analytic solutions. In cases where the systems only have numerical solutions, computational methods are used.
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) and solid state 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.
Many other more general numerical problems fall loosely under the domain of computational physics, although they could easily be considered pure mathematics or part of any number of applied areas. These include
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
All these methods (and several others) are used to calculate physical properties of the modeled systems. Computational Physics also encompasses the tuning of the software/hardware structure to solve the problems (as the problems usually can be very large, in processing power need or in memory requests).
Physicists often have a very precise mathematical theory describing how a system will behave. Unfortunately, it is often the case that solving the theory's equations ab initio in order to produce a useful prediction is not practical. This is especially true with quantum mechanics, where only a handful of simple models have complete analytic solutions. In cases where the systems only have numerical solutions, computational methods are used.
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) and solid state 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.
Many other more general numerical problems fall loosely under the domain of computational physics, although they could easily be considered pure mathematics or part of any number of applied areas. These include
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
All these methods (and several others) are used to calculate physical properties of the modeled systems. Computational Physics also encompasses the tuning of the software/hardware structure to solve the problems (as the problems usually can be very large, in processing power need or in memory requests).
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