Computational Methods in Materials Science (NANO*3600)
Code and section: NANO*3600*01
Term: Winter 2020
Instructor: Alexandros Gezerlis
8:30 am – 9:50 am
2:30 pm – 4:20 pm
There is no required textbook. I will be posting my lecture notes onto courselink at the end of every week.
- Mark Newman, Computational Physics (Rev. ed., CreateSpace, 2013)
- R. H. Landau, M. J. Paez, and C. C. Bordeianu, Computational Physics: Problem Solving with Python (3rd edition, Wiley, 2015 – custom volume ISBN: 9783527807512)
- Morten Hjorth-Jensen, Computational physics online lecture notes
Online resources on Unix and Python
- Matt Might, Survival guide for Unix newbies
- Michael Stonebank, UNIX Tutorial for Beginners
- The Python Tutorial
- Allen B. Downey, Think Python
This is a first course on what is known as computational science or scientific computing. We will focus on the interplay between science problem, mathematical formulation, and computational implementation. Previous exposure to programming is not required but will certainly be beneficial. We will cover the essentials of the following subjects:
- Unix shell basics
- Programming in Python
- Precision and errors
- Monte Carlo calculations
- Dealing with matrices
- Solving algebraic equations
- Data fitting
- Ordinary differential equations
- 40% Assignments+Labs
- 20% Midterm exam (March 5th, 8:30 am)
- 40% Final exam (In light of the COVID-19 campus restrictions, this will be completed as a take home exam: Due April 21)
If the final exam mark is greater than that of the midterm, the midterm will be dropped and the final exam mark will be weighted as 60% of the final mark.
Since one learns programming by doing, the lab is an integral part of this course. Thus, 5% of the overall grade will be based on lab attendance and performance.
- Tuesdays, 2-4 pm, in my office (MacN 219)
- Feel free to approach me before and after class to discuss scientific computing
- Alternative arrangements can be made by appointment (firstname.lastname@example.org)
Course policy regarding grading
Each homework assignment should be handed in on the due date before the lecture begins. There will be a significant penalty for late assignments, unless special arrangements are made ahead of time.
Course policy regarding use of electronic devices and recording of lectures
Electronic recording of classes is expressly forbidden without consent of the instructor. When recordings are permitted they are solely for the use of the authorized student and may not be reproduced, or transmitted to others, without the express written consent of the instructor.
When you find yourself unable to meet an in-course requirement because of illness or compassionate reasons, please advise the course instructor in writing, with your name, id#, and e-mail contact.
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Course Evaluation Information
Please refer to the Course and Instructor Evaluation Website
The last date to drop one-semester courses, without academic penalty, is April 3, 2020. For regulations and procedures for Dropping Courses, see the Undergraduate Calendar.