Superconducting Cross-Platform Quantum Noise Model: Multi-Round and Single-Round Repetition Code Dataset

This dataset contains comprehensive experimental and simulation data for quantum error correction using repetition codes on multiple superconducting quantum computing platforms. ## Dataset Contents ### Multi-Round Repetition Code Data- Experimental data from IBM Quantum processors (Brisbane, Sherbrooke, Torino)- 21 qubits, 30 measurement rounds- Correlation matrices and detection events- CMA-ES optimized noise parameters- Cross-platform comparative analysis ### Single-Round Repetition Code Data - X-basis and Z-basis measurements- Multiple platforms: IBM, Tencent, Tianyan- 5-21 qubit systems- L1 norm optimization results- Hardware parameters and visualization ## Key Features- Cross-platform universality validation- Physics-based noise model decomposition- Superior accuracy: 12.6× improvement in time errors, 4.8× in space errors- Complete analysis workflows and visualization The data supports research in quantum error correction, noise modeling, and cross-platform quantum computing validation.