Quantum Machine Learning
Stabilizer codes are a class of quantum error-correcting codes that utilize the stabilizer formalism to protect quantum information from errors due to decoherence and noise. They operate by encoding logical qubits into a larger number of physical qubits, enabling the detection and correction of specific types of errors. This framework allows for efficient quantum error correction, which is crucial for the development of reliable quantum computers.
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