athete / Computational-Physics-Lab

Programming assignments completed in the course PHY F313 Computational Physics

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Computational-Physics-Labs

This repository contains the programming assignments completed in the course PHY F313 Computational Physics in Semester 1 2020 - 2021. The course serves as an introduction to numerical methods used in mathematics and physics.

All programming assignments have been implemented using the MATLAB programming language (Version: R2018b)

Numerical Methods Implemented

  1. Bisection Method

The bisection method is a root-finding method that applies to any continuous function for which one knows two function values with opposite signs.

  1. Newton-Raphson Method

The Newton-Raphson method is a root-finding algorithm that successively produces approximations to roots of a real-valued function using an initial guess and the function's derivative.

  1. Gaussian Method

Gaussian elimination is an algorithm in for solving a system of linear equations. It involves a sequence of operations performed on the corresponding matrix of coefficients for the system.

  1. Jacobi Method

The Jacobi method is an iterative algorithm for determining the solutions of a strictly diagonally dominant system of linear equations. Each diagonal element is solved for, and an approximate value is plugged in. The process is then iterated until the method converges.

  1. Power Method

The power method is an eigenvalue algorithm: given a diagonalizable matrix A, the algorithm outputs the largest absolute eigenvalue of A, and its corresponding eigenvector.

  1. Runge-Kutta Methods

The Runge–Kutta methods are a family of implicit and explicit iterative methods used in temporal discretization for the approximate solutions of ordinary differential equations.

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Programming assignments completed in the course PHY F313 Computational Physics


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Language:MATLAB 100.0%