Physics 300, University of Nevada Las Vegas
Introduction to Physics and Scientific Computing
Location: BPB-248
Schedule: Mon/Weds 2:30 - 3:45 pm
| Instructor | Prof. Qiang Zhu |
|---|---|
| [email protected] | |
| Website | http://www.physics.unlv.edu/~qzhu/ |
| Office | BPB 232 |
| Office hours | Mon/Weds 9 - 10 am |
Course Outline
| Weeks | Subjects |
|---|---|
| 1 | Python basics I (installation, variables, list, loops) |
| 2 | Python basics II (function, advanced libraries) |
| 3 | Integrals/derivatives |
| 4 | Fitting/interpolation |
| 5 | Fourier transform |
| 6 | Random numbers |
| 7 | Monte carlo |
| 8 | Optmization I |
| 9 | Optmization II |
| 10 | Optmization III |
| 11 | Machine Learning I (Algorithms) |
| 12 | Machine Learning II (Applications) |
| 13 | Machine Learning III (Neural Networks) |
Prerequisites: PHYS 152, PHYS 152L or PHYS 180
Credit Hours: 3
Textbook: Computational Physics, M. Newman (not required)
Grade Distribution:
| Items | Percentage |
|---|---|
| Attendance | 10% |
| Homeworks | 25% |
| Midterm Project | 25% |
| Final Project | 40% |
Course Description
This course is open to all students who are interested in scientific programming and data analysis. It will teach students to write programs to solve simple physics programs on the computer and to manage their codes via github. There will be weekly assignments and two projects during the semester, plus an oral exam in the end of semester. Please bring your laptop to class. All the practices will be based on Python 3. Barring documentable emergencies or observance of a certifable regious holiday, all exams must be taken at the time and place specified.
Appendix
In addtion to the code page, we also have a wiki page which has extended discussions on some focused topics. Most of them were created by the students.
Notebook viewer
Sometimes the GitHub does not render the jupyter notebook properly. We recommend the use of nbviewer to view the notebook.
Instruction to submit your homework.
- register an account in GitHub.
- log into your github profile, and search for the github repo of qzhu2017/ComputationalPhysics300/, click the fork icon.
- after your log into your github account, you will have the forked github repo.
- complete homework by your own in the format of jupiter notebook. Upload the notebook to the homework directory by time.