Fisika Komputasi

"Dengan menggunakan komputer, kita bisa menghitung suatu sistem fisis yang mendekati kenyataan"
~Dr. Rizal Kurniadi~

Fisika bukan hanya melulu berurusan dengan rumus. Bukan hanya dengan perhitungan yang rumit dan terkadang membuat anak-anak SMA merasa kesulitan mempelajari Fisika. Fisika semestinya dipandang sebagai suatu ide tentang suatu kejadian fisis sehari-hari yang kita alami setiap hari, dan bukan ribetnya rumus dan perhitungannya. Fisika memiliki suatu cabang keilmuan (bisa dikatakan demikian) yang memanfaatkan suatu tools yang dapat dimanfaatkan untuk membuat perhitungan menjadi lebih mudah dan cepat. 

Tools itu adalah komputer dan cabang dari Fisika itu adalah Fisika Komputasi. Komputer dapat dipandang kini bukan hanya untuk mengolah data praktikum atau membuat dokumen ilmiah, namun bisa digunakan untuk menghitung suatu perhitungan yang rumit, yang sulit (bahkan mustahil) diselesaikan dengan tangan (secara analitik). 

Komputer dapat melakukan perhitungan dengan lebih cepat dibandingkan manusia. Secepat-cepatnya manusia menghitung, komputer akan selalu lebih cepat. Dengan demikian, para fisikawan dapat lebih berkonsentrasi pada konsep dan ide yang lebih besar dan menyerahkan perhitungan kepada komputer.

Computational physics is the study and implementation of numerical algorithms to solve problems in physics for which a quantitative theory already exists. It is often regarded as a subdiscipline of theoretical physics but some consider it an intermediate branch between theoretical and experimental physics. It is a subset of computational science (or "scientific computing"), which covers all of science rather than just physics.

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 admit closed-form, analytic solutions. In cases where the equations can only be solved approximately, computational methods are often used.

Applications of computational physics

 

 

Computation now represents an essential component of modern research in accelerator physics, astrophysics, fluid mechanics (computational fluid dynamics), 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. Molecular dynamics, which simulates the motion of interacting atoms and molecules, is an important technique in materials science, chemical physics and the modeling of biomolecules.

Methods and algorithms

 

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 or hardware structure to solve problems. Approaches to solving the problems are often very demanding in terms of processing power and/or memory requests.

Sumber:

1. Wikipedia
2. Christian Fredy Naa, M.Sc.