Scientific Python Projects

Computational physics coursework from my degree at the University of Birmingham: quantum bound states, Fourier analysis, signal filtering and rocket control.

Project	Mark	Main work
Quantum systems	95%	Finite square well, dimensionless equations and numerical root finding
Self-landing rockets	90%	Identifying simulator dynamics, positioning and P/PD feedback
Spectral analysis	80%	Swept-sine signals, FFTs, transfer functions and filtering
Programming worksheets	98% average	Python and numerical problem solving

Try the public examples

The example uses a 1 nm, 10 eV finite well, which has six bound states, and an 80 Hz signal with 320 Hz interference. These are selected demonstration inputs. The signal is synthetic and its clean component is known, so the change in SNR can be calculated directly.

Use Python 3.12:

git clone https://github.com/Robert-Study/Scientific-Python-Projects.git
cd Scientific-Python-Projects
python -m venv .venv

Activate with source .venv/bin/activate on macOS/Linux, or .venv\Scripts\Activate.ps1 in Windows PowerShell. Then:

python -m pip install -r requirements.txt
python demo.py
python -m unittest discover -s tests -v

The plot, signal CSV and numerical results are saved to outputs/demo/. A saved result is included for comparison. The quantum script can also be run directly:

python Project_1_Quantum_Systems.py

What can be reproduced

Component	Available here
Finite-well solver	All bound-state roots for the selected parameters, bracketed between successive half-periods
Signal-processing helpers	Linear frequency sweeps, one-sided spectra and frequency-domain filtering
Standalone demonstration	Quantum energies and filtering of a known synthetic signal
Original audio/filter-box exercise	Requires the university's module_engine package and its supplied data
Original rocket exercise	Requires the university's module_engine simulator
Worksheets	Some file-based exercises require the original data.txt

The university package is not distributed here. Its absence does not prevent importing the numerical helpers or running demo.py. The rocket results are not presented as a public, independently reproducible landing benchmark.

Numerical checks

The test suite compares the well energies with a separate finite-difference Hamiltonian calculation. It also checks the swept-sine phase against SciPy's chirp, verifies removal of a tone at the filter's notch frequency, and checks the Nyquist bin and sampling assumptions.

The sweep phase is the integral of the instantaneous frequency. Using sin(2π f(t)t) for a changing frequency would give the wrong ramp. The well solver likewise avoids tangent poles when bracketing roots.

View the tests · GitHub Actions

The marks refer to the original assessed submissions. The standalone examples, root bracketing and signal-generation corrections were added during later portfolio development.