https://github.com/torodata/computational-physics
https://github.com/torodata/computational-physics
Last synced: 10 months ago
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- Host: GitHub
- URL: https://github.com/torodata/computational-physics
- Owner: ToroData
- Created: 2025-07-28T17:37:15.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-08-03T18:19:46.000Z (11 months ago)
- Last Synced: 2025-08-03T20:25:10.083Z (11 months ago)
- Language: Python
- Size: 533 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Computational Physics
This repository contains a curated collection of algorithms, scripts, and computational tools developed in the context of advanced studies in theoretical and computational physics. It serves both as a personal archive of learning and a resource aligned with coursework in the MSc in Advanced Physics.
The work presented here follows, extends, or is inspired by key references in the field, notably:
- *Computational Physics* by J.M. Thijssen
- Other classical and contemporary resources relevant to each topic
## Scope and Topics
The repository is organized around core areas in modern physics where computational methods are essential. These include, but are not limited to:
- **Computational Physics**: Numerical methods, recurrence relations, special functions
- **Electrodynamics**: Field simulation, wave propagation, boundary value problems
- **Quantum Mechanics**: Schrödinger equation solvers, time evolution, basis expansions
- **Quantum Molecular Dynamics**: Simulation of atomic systems, time-dependent behavior
- **Quantum Field Theory**: Discretization techniques, propagators, lattice methods
Each script or module is self-contained, documented, and, where appropriate, tested. The implementations prioritize clarity, numerical stability, and fidelity to physical principles.
## Environment and Tools
The code is written primarily in Python (3.11+), leveraging libraries such as:
- `numpy`, `scipy` for numerical computation
- `matplotlib` for visualization
- `sympy` for symbolic manipulation (when relevant)
- `jupyter` notebooks for exploratory work
Future extensions may include compiled languages (e.g., C++) or parallel computing tools when performance is critical.
## Licensing
Unless stated otherwise, all content in this repository is released under the MIT License. Please cite appropriately if using or adapting the material.
## Contact
This repository is maintained as part of the academic work in the MSc in Advanced Physics. For questions or collaboration, feel free to open an issue or contact directly via GitHub.