Optimize qubit state discrimination using Gaussian Mixture Model
Readout Fidelity
99.2%
Cluster Separation
4.5σ
Assignment Error
0.8%
The Gaussian Mixture Model clusters readout outcomes in the IQ plane to distinguish between |g⟩ and |e⟩ states. The separation between clusters determines assignment fidelity, while the decision boundary optimizes error minimization. This calibration is essential for high-fidelity single-shot qubit readout in quantum computing experiments.