论文标题

部分可观测时空混沌系统的无模型预测

Generalized fast quasi-adiabatic population transfer for improved qubit readout, shuttling, and noise mitigation

论文作者

Fehse, F., David, M., Pioro-Ladrière, M., Coish, W. A.

论文摘要

储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。

Population-transfer schemes are commonly used to convert information robustly stored in some quantum system for manipulation and memory into more macroscopic degrees of freedom for measurement. These schemes may include, e.g., spin-to-charge conversion for spins in quantum dots, detuning of charge qubits between a noise-insensitive operating point and a measurement point, spatial shuttling of qubits encoded in spins or ions, and parity-to-charge conversion schemes for qubits based on Majorana zero modes. A common strategy is to use a slow (adiabatic) conversion. However, in an adiabatic scheme, the adiabaticity conditions, on the one hand, and accumulation of errors through dephasing, leakage, and energy relaxation processes on the other hand, limit the fidelity that can be achieved. Here, we give explicit fast quasiadiabatic (fast-QUAD) conversion strategies (pulse shapes) beyond the adiabatic approximation that allow for optimal state conversion. In contrast with many other approaches, here we account for noise in combination with pulse shaping. Although we restrict to noise sources that can be modeled by a classical fluctuating parameter, we allow generally for anisotropic nonGaussian noise that is nevertheless sufficiently weak to lead to a small error. Inspired by analytic methods that have been developed for dynamical decoupling theory, we provide a general framework for unique noise mitigation strategies that can be tailored to the system and environment of interest.

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