Computational physics

Computational physics is a branch of physics that employs numerical analysis and advanced computational methods to solve complex physical problems which are often too difficult to solve analytically. With the advent of computers, computational physics has become a key part of physics research due to its ability to handle large amounts of data, simulate systems, and solve mathematical models.

History

The history of computational physics as a discipline is closely tied to the development of the digital computer. In its early days, it was defined as the numerical solution of mathematical equations that describe physical phenomena. The first example of computational physics in action was during the Manhattan Project when a team led by Richard Feynman used the IBM punch-card machines to calculate the neutron diffusion equations.

Methods

Computational physics uses two main methods: simulations and numerical calculations.

Simulations are used to mimic the behavior of a system by using a model. This model can be a set of mathematical equations (differential, algebraic, etc.) or rules defined on a grid or network. Simulations can be deterministic or stochastic, and they can be discrete or continuous in time.

Numerical calculations are used to solve mathematical equations that are too complex to solve analytically. These calculations are often made using numerical algorithms, which can handle the large amounts of data produced by the simulations.

Applications

Computational physics has been used in a wide variety of fields, including astrophysics, condensed matter physics, quantum mechanics, and statistical physics. It has also been used to model complex systems in biology, chemistry, and economics.

Software

There are many software packages available for computational physics. These include commercial packages like MATLAB and Mathematica, and free software like Python, Octave, and R.

See also

• Computational science
• Computational chemistry
• Computational biology
• Computational fluid dynamics
• Computational electromagnetics