How to Keep Quantum Information Alive for Machine Learning

Quantum information is exceptionally fragile due to decoherence, presenting a major obstacle for scalable quantum machine learning. Unlike classical bits, quantum states cannot be copied for backup or measured without collapsing their state, a challenge addressed by Quantum Error Correction (QEC). Unwanted environmental disturbances, or noise, are modeled abstractly as quantum channels that can introduce errors. Many of these errors can be understood in terms of three fundamental operations known as Pauli errors: the X (bit-flip), Z (phase-flip), and Y errors. These basic error types form the building blocks for creating codes to protect quantum computations.