Paris Physics Master
Paris Physics Master
Numerical methods for physics
Numerical methods for physics
Academic year 2026-2027
Academic year 2026-2027
Welcome to the Numerical Methods for Physics course webpage. This page is kept up-to-date. Check it out regularly!
Lecturers: Sebastien Charnoz (Univ. Paris-Cite) Andrea Ciardi (Sorbonne Univ.)
Time and Location: All classes take place in Sorbonne Université, Campus Pierre et Marie Curie. For time and rooms see the schedule below.
Always bring your own laptop.
Date Time Location Lecture Topic Prof
Team up in groups of 3 students (strict maximum). Choose a physics (or very closely related) problem and a numerical method to solve it. Choose your projects and team by October 1st and fill in this FORM.
The oral presentations will be on the 18th of December 2026, more details about the presentations are given below.
Projects from previous years.
Network Analysis
Numerical methods in High Energy Physics, Quantum Tunneling
Using Cellular Automata to Simulate Cancer Cell Growth
Variational Quantum Eigensolvers
Finite size effects on Bose Einstein condensate
Solving Eigenvalue equations
Solution of Fokker-Planck equation with different stochastic processes
Physics Parameter analysis in exclusive B-Decay
Equilibrium analysis of 2D lattice in Ising Model
SIR Model of Epidemic
Solving optimization problems with classical and quantum Ising-Models
Neural Networks For Image Recognition
Toda oscillator
Solving differential equation in Finance using ML
Predator Prey / Lotka- Volterra
Percolation theory applied to fire propagation
Molecular dynamics
Newtonian Dynamics of a Fluid
Turbocodes
Analysis of the Lorenz Attractor System
N-body simulations
etc...
Practical aspects : read carefuly
Presentations are 12 mins + 8 mins of questions. You must strictly keep to the allocated time (12 mins within 30 seconds) or you will be severely penalised. The presentations will be on the Campus Pierre et Marie Curie (Jussieu campus): room to be announced
Before the 17.12.2026 midnight, you must upload your presentation (PDF only), a single Jupyter notebook and, if necessary, any other python files that you have developed for your project. Upload link will appear here soon.
Uploaded files should be named using the prefix assigned to your group, for example: g4.pdf for the presentation, g4.ipynb for the notebook and g4_1.py and g4_2.py for other python files. Make sure that the names of all group members appear in all files. For the presentation you can use the computer available in class. We will use the PDF uploaded by you the day before, However, if you have animations in your presentations you can bring a USB key with the file in powerpoint format and we will try to use that, or you can use your computer, but be aware that compatibility cannot be guaranteed. Only a PDF is a safe bet.
Criteria for Assessing the Oral Presentations.
The following guidelines aim to assist groups in preparing and delivering clear, comprehensive, and informative presentations of their numerical physics projects as a team, ensuring equal contribution, collaboration among members, and highlighting their understanding of the physics problem along with collective efforts in utilizing numerical methods to solve it.
1. Content Knowledge: - Show collective understanding of numerical methods and apply them effectively. - Apply physics concepts to the problem statement, ensuring clarity and coherence.
2. Methodology: - Jointly choose and justify the numerical techniques used, highlighting collective decision-making skills. - Describe the code building process, specifying individual contributions. - Discuss the tests to ensure accuracy and precision in solutions. - Describe how the work was organized and shared, demonstrating effective teamwork.
3. Presentation Skills: - Organize and structure the presentation coherently as a team. - All members take an equal share of time. - Ensure slides are clear and well-constructed. - Ensure figures are readable, axes are labelled, and units are displayed. - DO NOT SHOW PYTHON CODE, DO NOT SHOW SCREENSHOTS OF JUPYTER NOTEBOOKS
4. Depth of Analysis and Interpretation:- Collaboratively interpret and analyze the results obtained. - Demonstrate critical thinking as a team in evaluating solutions and drawing conclusions. - Emphasize the problems you have encountered, approximations and limitations of your code and discuss future possible improvements.
5. Question & Answer Session: - All team members actively participate in responding to questions, - You are expected to display in depth knowledge beyond the presentation content.
Short and basic introduction to Scientific computing with numpy. This is part of a lecture course on scientific computing with python given to students with no previous knowledge of programming.
Python and associated tools installation
Anaconda: https://www.anaconda.com/download
Excellent place to learn how to use Python for scientific computing:
Introduction to programming in Python
Excellent tools for newcomers to programming and Python:
Fortran and Python (and Cython)
This is an excellent extension for ipython to write fortran code in the console on the fly:
Cython
Pythran
Astropy is "a community-driven package intended to contain much of the core functionality and some common tools needed for performing astronomy and astrophysics with Python."
Useful docs
http://pyformat.info/ string formatting
Other
2014 Argonne Training Program on Extreme Scale Computing: link