An educational web application demonstrating quantum parameter estimation techniques, built on top of the QuanEstimation library.
.
├── src/
│ ├── main.py # FastAPI backend (API endpoints)
│ ├── quantum_estimation.py # Core simulation and visualization routines
│ ├── index.html # Frontend UI with interactive parameter controls
│ └── doc/ # HTML documents explaining each module's principles
│ ├── 1.html # Single Qubit Parameter Estimation
│ ├── 2.html # Two Qubit Parameter Estimation
│ ├── 3.html # Bayesian Quantum Parameter Estimation
│ ├── 4.html # Bayesian vs. Maximum Likelihood Estimation
│ ├── 5.html # Measurement Optimization
│ └── 6.html # State Optimization of LMG Model
└── turorial/
└── QuanEstimation_turorial_git.pdf # Reference tutorial PDF
- Python 3.8+
- QuanEstimation
- QuTiP
- FastAPI + Uvicorn
- NumPy, SciPy, Matplotlib
cd src
uvicorn main:app --host 0.0.0.0 --port 8000Then open http://localhost:8000 in your browser.
The web interface provides 6 interactive tabs:
| Tab | Topic | Description |
|---|---|---|
| 1 | Single Qubit Parameter Estimation | CFI/QFI evolution under Lindblad dissipation |
| 2 | Two Qubit Parameter Estimation | CFIM, QFIM, HCRB, and NHB bounds for two-qubit systems |
| 3 | Bayesian Quantum Parameter Estimation | Prior distribution and Bloch vector Z-component analysis |
| 4 | Bayesian vs. MLE | Posterior distribution (MAP) and likelihood function (MLE) comparison |
| 5 | Measurement Optimization | Projection, LC input, and rotation input measurement optimization |
| 6 | State Optimization | QFI convergence and optimal state distribution for the LMG model |
| Endpoint | Module |
|---|---|
/createImg |
Tab 1: Single Qubit |
/createImgQuantum |
Tab 2: Two Qubit |
/createImgBayesian |
Tab 3: Bayesian |
/createImgQuantumParameter |
Tab 4: MAP vs MLE |
/createImgProjection |
Tab 5-1: Projection Measurement |
/createImgLCInput |
Tab 5-2: LC Input Measurement |
/createImgRotationInput |
Tab 5-3: Rotation Input Measurement |
/createImgStateOpt |
Tab 6: State Optimization |