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Quantum Error Correction: Noise-adapted Techniques and Applications
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Quantum Error Correction: Noise-adapted Techniques and Applications
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The quantum computing devices of today have tens to hundreds of qubits that are highly susceptible to noise due to unwanted interactions with their environment. The theory of quantum error correction provides a scheme by which the effects of such noise on quantum states can be mitigated, paving the way for realising robust, scalable quantum computers. In this article we survey the current landscape of quantum error correcting (QEC) codes, focusing on recent theoretical advances in the domain of noise-adapted QEC, and highlighting some key open questions. We also discuss the interesting connections that have emerged between such adaptive QEC techniques and fundamental physics, especially in the areas of many-body physics and cosmology. We conclude with a brief review of the theory of quantum fault tolerance which gives a quantitative estimate of the physical noise threshold below which error-resilient quantum computation is possible.
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Cited by 1 Pith paper
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Backend-Aware Graph Learning for Denoising Outcome Distributions in Quantum Program Testing
Q-BRIDGE, a graph-transformer denoiser conditioned on backend features, reconstructs ideal outcome distributions from noisy quantum executions and markedly improves oracle-based bug detection.
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