DAMP Physics, IITB

Instructor Name: Rekha Kulkarni Course Type: Theory Pre-requisites: None Course Content: Errors, Polynomial interpolation, Numerical intergration, numerical differentiation, Matrix and vector norms, Matrix decompositions, Initial value problem, eigenvalue problem,  Other topics covered: Books: Cante de Boor was the textbook, didn't use it myself though, slides were sufficient  Lectures: 80% attendance is necessary unless DX - this was the initial warning but didn't give any DXes. DXes were given in S2 division though by Shripad Garge Assignments: Tutorial booklet, mostly easy Exams and Grading: 2 quizzes 20%, midsem 30% and endsem 50%; quizzes were easy and objective; midsem and endsem papers were repeated I believe, the papers were okay and the grading was fair too. Online material: Follow-up Courses : Pro-tips:  Proxy attendance is liable to get you severely punished Personal Comments: Interesting course Respondent:...

First response Instructor Name:  Prof. Sivaji Ganesh, Prof. S. Baskar Course Type: Core Pre-requisites:  MA 105, MA 106, MA 108 Course Content:  Error Analysis - Floating Point Representation, Propagation of Errors, Numerical Linear Algebra - algebraic and iterative methods to solve a system of linear eqns, eigenvalue problems, Nonlinear Equations - iterative methods like bisection, Newton-Raphson, Interpolation-finding an interpolating polynomial given a set of data points and errors, Numerical Integration and Differentiation, Numerical Ordinary Differential Equations.  Books:  The lecture notes are more than enough Lectures:  Lectures take place in LA, Slides based teaching. strict 80% attendance policy - several DXs were handed out. Teaching quality is decent. Assignments:  Tutorials are of moderate level and complement the course well. Exams and Grading:  2 quizzes (15%), midsem(30%) and endsem(40%).  Follow up courses:...

Instructor Name Prof. S Sivaji Ganesh, Prof. S. Baskar Course Type Core for EP students Course overview Error Analysis : Floating-point representation, propagation of errors, stability of computation Numerical Linear Algebra : Solving linear system, matrix factorization, locating eigenvalue of matrix, algebraic and iterative methods Nonlinear Equations : Closed and open domain iterative schemes to approximate solution of nonlinear equation were discussed. This included bisection, secant, Newton-Raphson, and fixed point methods, along with a discussion of the order of accuracy of some of these methods. Interpolation - Finding an interpolating polynomial given a set of data points and errors, and analysis of the accuracy of the various interpolation methods. Newton and Lagrange form of interpolation were covered. Numerical calculus : Various methods for numerically approximating integrals and derivatives were discussed, along with the errors for the same Numerical ...