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Iterative quantum amplitude estimation
DOI:10.1038/s41534-021-00379-1.png)
摘要
En 中文
We introduce a variant of Quantum Amplitude Estimation (QAE), called Iterative QAE (IQAE), which does not rely on Quantum Phase Estimation (QPE) but is only based on Grover's Algorithm, which reduces the required number of qubits and gates. We provide a rigorous analysis of IQAE and prove that it achieves a quadratic speedup up to a double-logarithmic factor compared to classical Monte Carlo simulation with provably small constant overhead. Furthermore, we show with an empirical study that our algorithm outperforms other known QAE variants without QPE, some even by orders of magnitude, i.e., our algorithm requires significantly fewer samples to achieve the same estimation accuracy and confidence level.
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8.3
论文数:
1.4K
被引数:
8.1K
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Quantum Generative Adversarial Networks for learning and loading random distributions用于学习和加载随机分布的量子生成对抗网络

