Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?

Variational Quantum Algorithms (VQAs) are often viewed as the best hope for near-term quantum advantage. However, recent studies have shown that noise can severely limit the trainability of VQAs, e.g., by exponentially flattening the cost landscape and suppressing the magnitudes of cost gradients. E...

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Main Authors: Samson Wang, Piotr Czarnik, Andrew Arrasmith, M. Cerezo, Lukasz Cincio, Patrick J. Coles
格式: 文件
语言:English
出版: Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften 2024-03-01
丛编:Quantum
在线阅读:https://quantum-journal.org/papers/q-2024-03-14-1287/pdf/