基于聚类状态的参数估计
Parameter estimation with cluster states
摘要：
我们提出了一个方案的参数估计与集群状态。我们发现，在多体哈密顿量和可分离的测量下，团簇态的相位估计导致海森堡极限的精度。作为噪声模型，我们研究了去相位，去极化和纯阻尼通道。退相干降低了灵敏度，但我们的方案仍然优于几个参考方案的状态，如最大纠缠态和产品状态。对于小的团簇状态和固定的演化时间，它保持在海森堡极限的量子位数大约是替代方案的2倍。
英文摘要：
We propose a scheme for parameter estimation with cluster states. We find that phase estimation with cluster states under a many-body Hamiltonian and separable measurements leads to a precision at the Heisenberg limit. As noise models we study the dephasing, depolarizing, and pure damping channels. Decoherence reduces the sensitivity but our scheme remains superior over several reference schemes with states such as maximally entangled states and product states. For small cluster states and fixed evolution times it remains at the Heisenberg limit for approximately 2 times as many qubits than alternative schemes.
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