CS 111: Introduction to Computational Science

 

·       Professor

·       Syllabus

·       Teaching Assistant

·       Textbook

·       Grading Policy

·       Homework

·       Matlab Primer

·       Midterm Review

 

Professor

Name: Frederic G. Gibou
Office: Engineering II Bldg. room 2334
Phone: 893-7152
e-mail: fgibou@engineering.ucsb.edu

Office Hours: TR 1:45-3:15 pm or by appointment.

Lectures: TR 3:30-4:45 pm. Room: SH 1431

Syllabus

A copy of the syllabus can be found here.

 

  • Thursday September 28: Goals for the class – Presentation of the topics that will be covered.
  • Tuesday October 3: Introduction to linear systems of equations – Dense .vs. Sparse matrices and its implications.
  • Thursday October 5: Direct Methods – LU decomposition (Chapter 4.1-4.2).
  • Tuesday October 10: Direct Methods – Gaussian decomposition and Pivoting (Chapter 4.3).
  • Thursday October 12: Direct Methods – Gaussian decomposition and Pivoting (Chapter 4.4).
  • Thursday October 12: Direct Methods – Pivoting and Analysis of Errors (Chapter 4.4).
  • Thursday October 17: Direct Methods – Pivoting and Analysis of Errors (Chapter 4.4).
  • Thursday October 19: Direct Methods – Pivoting and Analysis of Errors (Chapter 4.4).
  • Thursday October 24: Iterative Methods – Iterative Refinement - Gauss-Seidel and Jacobi (Chapter 4.5-4.6).
  • Thursday October 26: Iterative Methods – Iterative Refinement (Chapter 4.5-4.6).
  • Tuesday October 31: Iterative Methods – Iterative Refinement (Chapter 4.5-4.6).
  • Thursday November 2: ODE – Introduction and Euler Method (Chapter 8.1).
  • Tuesday November 7: Review.
  • Thursday November 9: Midterm. The midterm will cover everything we have covered in lecture. Here is a review.
  • Tuesday November 14: ODE –Methods based on Taylor expansions – Order of accuracy.
  • Thursday November 16: ODE – Runge-Kutta Methods.
  • Tuesday November 21: ODE – Multistep Methods – Adams-Bashforth.
  • Thursday November 23: Thanks Giving.
  • Tuesday November 28: ODE – Multistep Methods – Adams-Moulton and Predictor-Correctors.
  • Thursday November 30: Introduction to PDE – The heat equation.
  • Tuesday December 5: Introduction to PDE – The heat equation.
  • Thursday December 7: Review.

 

  • Friday December 15: Final exam – 4:7pm. A Final project can server in lieu of the final examination.

 

 

Teaching Assistants

Svetlin (Alex) Bostandjiev svetlin@umail.ucsb.edu will lead the discussions on Fridays 2-2:50 pm in Phelp 3515. His office hours are on Fridays 3-6 pm in Phelp 1413B.

 

Textbook

The textbook for the course is David Kincaid and Ward Cheney, Numerical Analysis, Brooks/Cole., Second Edition, 1996.

Additional references, lecture notes and slides will be handed out in class or posted on the web.

Grading Policy

Your grade will be based on homework (25%), one midterm (25%) and a final (50%). The midterm will be on Thursday November 9. A review will be given on Tuesday November 7.

Homework

Working together on homework in groups of two or three students is strongly encouraged.

Homework due Thursday October 12: hw1. Solution.

Homework due Thursday October 19: hw2. Solution. Code_Gauss_Pivoting.

Homework due Thursday October 26: hw3. Solution.

Homework due Thursday November 2: hw4. Solution Solution_Jacobi Solution_Jacobi_2 Solution_GS Solution_GS2

No Homework due Thursday November 9 - Midterm. Here is a review.

Homework due Tuesday November 21: hw5. Solution_hw5_Taylor, Solution_hw5_Taylor_Accuracy, Solution_hw5_RK4, Solution_hw5_RK4_Accuracy

Homework due Thursday November 30: hw6. Solution.

Midterm Review

Here is a review. No calculator, books, notes will be allowed. The midterm will cover everything we have covered in lecture.

Matlab Primer

Here is a link to Matlab Primer.