This course will enable students to:
Lab work:
Solving Problems related to topics covered in the course by actual Programming and obtaining results.
Matrices: Product of matrices, inversion using iterative methods and accessory
Numerical Linear Algebra: Solution of system of linear equations, direct methods, error analysis.
Curve fitting: Least square fitting methods, linear regression, polynomial regression, iterative methods.
6 Hrs.
(b) Numerical differentiation and integration methods: Numerical methods for derivatives, minima and maxima of a function, numerical integration methods for one dimensional to multi-dimensional integrations using Simpson’s rule, quadrature formula and Monte Carlo methods.
Interpolation: Splines, Numerical methods for ordinary and partial differential equations: Euler’s method, Range-Kutta method for ordinary differential equations; stability and convergence
7 Hrs.
(b) Partial differential equations using matrix method for difference equation, relaxation method, initial value problems, stability, convergence and qualitative properties.
Random numbers, Monte Carlo integral methods, importance of sampling, Fast Fourier Transform.
Quantum Simulations: Time-independent Schrödinger equation in one dimension (radial or linear equations); Scattering from a spherical potential, Born Approximation
Bound State Solutions: Single particle time dependent Schrödinger equation; Hartree Fock Theory: restricted and unrestricted theory applied to atoms; Schrödinger equation in a basis: Matrix operations, Variation properties; Application of basis functions to atomic, molecular and solid state calculations.