AI 中文总结
本文提出基于灰箱响应模型的资源受限框架，评估开放量子系统实际可控性，通过实例验证有限控制资源与系统噪声共同制约门性能，为相关基准测试提供方法。
AI 中文摘要
本文开发了一种资源受限框架，用于使用训练后的灰箱响应模型评估开放量子系统的实际可控性。该方法未将可控性视为理想化哈密顿量模型的二元属性，而是在明确的控制约束下，评估有限的硬件可实现脉冲族能达到的最佳过程保真度。灰箱模型保留已知的相干动力学，同时从脉冲响应数据中学习依赖控制的开放系统失真。所得的替代预测用于重构已实现的过程，并将其与Haar随机目标门进行比较。随后通过最佳可达失真值的分布和基于面积的汇总指标来表征实际可控性。该框架针对受驱动量子比特，在闭系统、经典噪声以及量子加经典组合噪声动力学下进行了演示，采用脉冲幅度和逆高斯宽度作为控制资源坐标。结果表明，有限的控制资源和开放系统噪声如何共同限制所选脉冲族可达到的门性能。
英文摘要
This paper develops a resource-bounded framework for evaluating practical controllability in open quantum systems using a trained graybox response model. Rather than treating controllability as a binary property of an idealised Hamiltonian model, the proposed approach evaluates the best-achievable process fidelity over a finite, hardware-realisable pulse family under explicit control constraints. The graybox model retains the known coherent dynamics while learning control-dependent open-system distortions from pulse-response data. The resulting surrogate predictions are used to reconstruct the implemented processes and compare them with Haar-random target gates. Practical controllability is then characterised through the distribution of best-achievable infidelities and an area-based summary metric. The framework is demonstrated for a driven qubit under closed-system, classical-noise, and combined quantum-plus-classical-noise dynamics, with pulse amplitude and inverse Gaussian width used as the control-resource coordinates. The results show how finite control resources and open-system noise jointly constrain the gate performance attainable by the chosen pulse family.
