What is Monte Carlo simulation and how it is useful for condensed matter research?
- You can see this video for understanding montecarlo lmethod
- https://www.youtube.com/watch?v=pDExObTMHTs
Monte Carlo method is a stochastic technique driven by random numbers and probability statistic to sample conformational space when it is infeasible or impossible to compute an exact result with a deterministic algorithm. It applies the theories of statistical physics to the study of macroscopic systems (disordered system, fluids, and cellular structures) as a result of their large degree of freedom and probabilistic nature. The name “Monte Carlo” (a computer simulation of random numbers i.e using random numbers as a tool to compute something that is not random) was originally coined by Metropolis and Ulam during the Manhattan project of World War II as a result of the simulation technique to the game of chance. Monte Carlo simulation (a series of random steps in conformation space, each perturbing some degrees of freedom of the molecule) is a standard method often used to compute several pathways in understanding thermodynamic and kinetics mechanisms of longer chains in the contest of lattice model.
A good example is, it is possible to minimise the energy of a system by using Metropolis algorithm. Ising model is one of the usage of Metropolis algorithm. Simply; choose a spin, change it, calculate the energy of the system, if the energy minimises accept it for calculation, otherwise do not accept. Repeat it until the energy minimises.
Please, see this video.
https://www.youtube.com/watch?v=h1NOS_wxgGg&t=983s
The term of Monte Carlo simulation is huge. It is important to know the possible expected output at the end of simulation. Regarding to material science, different types of applications can be applied. For further examples you can visit my ResearchGate profile. There you will see different types of applications on radiation shielding investigations of amorphous and alloy materials.
Monte Carlo in its wide scope is the generation of random events. The generation is not absolutely random but it is controlled by some restrictions, e.g. the physical laws and the boundary conditions. The simplest example that you can get it is : Calculation of Pi by Monte Carlo Method. Please write that in google.
- Badges
- Science topic
- Similar topics
- Physics
- Condensed Matter Physics