# Supplementary Materials: Disorder-Induced Suppression and Load Optimization in Organic Microcavity Quantum Batteries

This archive contains the source code, raw simulation data, and interactive visualizations supporting the manuscript *"Disorder-Induced Suppression and Load Optimization in Organic Microcavity Quantum Batteries"* by Sahil Bhardwaj and Vikas Sidhu.

## Contents

| File | Description |
| :--- | :--- |
| `quantum_battery_final.py` | Main Python script for the QuTiP simulation. Implements the pulsed charge–store–extract protocol, disorder averaging, and parameter sweeps for Figures 1–3. |
| `simulation_data.csv` | Raw numerical results for Figures 1 and 2, including extraction efficiency means and standard deviations across 20 disorder realizations. |
| `fig1_efficiency_vs_disorder.png` | Figure 2 in manuscript: Extraction efficiency vs disorder strength for N=2–6. |
| `fig2_optimal_kappa.png` | Figure 3 in manuscript: Optimal extraction coupling shift for N=4 at σ=0.0 and σ=0.4. |
| `fig3_power_scaling.png` | Figure 5 in manuscript: Stored energy scaling with N under different disorder strengths. |
| `fig4_disordered_ensemble.html` | Interactive 3D visualization of the disordered molecular ensemble and extraction port (Figure 4 in manuscript). Open in any modern web browser. |
| `quantum_battery_lab.html` | Interactive web application that allows exploration of key parameters (N, σ, κₑₓₜ) and displays real‑time predictions based on fitted simulation data. |

## System Requirements

The Python script (`quantum_battery_final.py`) requires:
- Python 3.8 or later
- QuTiP (Quantum Toolbox in Python) – install via `pip install qutip`
- NumPy, SciPy, Matplotlib, Pandas (optional for CSV export)

All dependencies are available through standard package managers.

## Running the Simulation

1. Ensure all dependencies are installed.
2. Execute the script from a terminal:
   ```bash
   python quantum_battery_final.py