Computational Physics for Aspiring Scientists
A specialized computational physics training academy bridging theoretical physics and real-world numerical simulation.
Solve Complex Physical Systems with Python
The COMPASS program provides students with the skills to apply computational techniques to solve complex physical problems that are difficult to address analytically. The course emphasizes the use of Python to model, simulate, and analyze systems in classical mechanics, electromagnetism, statistical mechanics, and quantum physics.
Students explore numerical differential equations (Euler, Runge-Kutta), numerical integration, Monte Carlo modeling, and scientific visualization (NumPy, SciPy, Matplotlib), culminating in real-world team capstone research projects.
Scientific Python Stack
Master modern scientific computing using Python, NumPy vectorization, Matplotlib 2D/3D visualizations, and SymPy symbolic calculus.
Differential Equations & Orbits
Simulate nonlinear pendulums, chaotic attractors, planetary gravitational n-body orbits, and damped driven oscillators with high precision.
Monte Carlo & Fields
Model stochastic diffusion, thermodynamic gas partitions, electric field flux lines, and quantum wavepacket time evolution.
APPLICANT GUIDE
Frequently Asked Questions
Are there any needed prerequisites?
Background knowledge of basic coding, calculus, and general physics (preferably familiarity with Python or programming logic).
What is the course length and format?
2 weeks intensive training • 3 live interactive sessions per week • 2 hours per session • Conducted 100% virtually with hands-on coding demos.
What is the participation eligibility?
The program is open to high school students (Grade 10 through Grade 12) across Egypt who demonstrate readiness through the entrance problem set.
Do I need to submit problem set solutions?
Yes. In order to be admitted into the cohort, applicants must submit detailed solutions to the entrance problem set formatted cleanly in LaTeX or digital software.
Will there be a final capstone project?
Yes! To synthesize and apply what you learned, 2-member research teams are formed to model, simulate, and present an original computational physics project.
What resources and tools are used?
Curated handouts & slide decks created by the STEM October Physics team • Reference text: Computational Physics: Problem Solving with Python (3rd Edition) by Landau, Páez, and Bordeianu • Google Colab & Jupyter Notebook environments.