通过泽曼模型解析Rodeo算法
Unraveling Rodeo Algorithm Through the Zeeman Model
AI总结：
通过泽曼模型解析Rodeo算法，提出新方法确定一般哈密顿量的本征态和本征值谱，并通过实验验证算法性能改进。
摘要：
我们解析Rodeo算法以确定一般哈密顿量在任意初始状态下的本征态和本征值谱。通过提出一种新方法，我们详细描述了原始方法并展示了如何在不事先了解本征态的情况下定义所有属性。为此，我们利用Pennylane和Qiskit平台的资源，分析了当哈密顿量由单个和两个自旋的泽曼模型描述时的情况。我们还介绍了改进算法性能的策略和技术，通过调整其内在参数和减少数据分布固有的波动。首先，我们探索单个量子比特在Xanadu模拟器上的动态，以设置优化方法性能的参数并选择最佳策略执行算法。随后，我们将该方法扩展到双元系统，讨论当退化和纠缠被考虑时算法的工作方式。最后，我们将预测与IBM Q Experience程序提供的真实超导设备的结果进行比较，建立提高多量子比特系统协议效率的条件。
英文摘要：
We unravel the Rodeo Algorithm to determine the eigenstates and eigenvalues spectrum for a general Hamiltonian considering arbitrary initial states. By presenting a novel methodology, we detail the original method and show how to define all properties without having prior knowledge regarding the eigenstates. To this end, we exploit Pennylane and Qiskit platforms resources to analyze scenarios where the Hamiltonians are described by the Zeeman model for one and two spins. We also introduce strategies and techniques to improve the algorithm's performance by adjusting its intrinsic parameters and reducing the fluctuations inherent to data distribution. First, we explore the dynamics of a single qubit on Xanadu simulators to set the parameters that optimize the method performance and select the best strategies to execute the algorithm. On the sequence, we extend the methodology for bipartite systems to discuss how the algorithm works when degeneracy and entanglement are taken into account. Finally, we compare the predictions with the results obtained on a real superconducting device provided by the IBM Q Experience program, establishing the conditions to increase the protocol efficiency for multi-qubit systems.
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