Extracting quantum dynamics from genetic learning algorithms through principal control analysis

Experimentally Attainable Optimal Pulse Shapes Obtained with the Aid of Genetic Algorithms

We propose a methodology to design optimal pulses for achieving quantum optimal control on molecular systems. Our approach constrains pulse shapes to linear combinations of a fixed number of experimentally relevant pulse functions. Quantum optimal control is obtained by maximizing a multi-target fitness function with genetic algorithms. As a first application of the methodology we generated an optimal pulse that successfully maximized the yield on a selected dissociation channel of a diatomic molecule. Our pulse is obtained as a linear combination of linearly chirped pulse functions. Data reco…

A Low Complexity Quantum Principal Component Analysis Algorithm

In this paper, we propose a low complexity quantum principal component analysis (qPCA) algorithm. Similar to the state-of-the-art qPCA, it achieves dimension reduction by extracting principal components of the data matrix, rather than all components of the data matrix, to quantum registers, so that samples of measurement required can be reduced considerably. However, the major advantage of our qPCA over the state-of-the-art qPCA is that it requires much less quantum gates. In addition, it is more accurate due to the simplification of the quantum circuit. We implement the proposed qPCA on the I…

通过均值导数投影从超导纳米线单光子探测器轨迹中提取光子数信息

Extracting Photon-Number Information from Superconducting Nanowire Single-Photon Detectors Traces via Mean-Derivative Projection

本文通过PCA与新读出技术结合，揭示了SNSPDs的光子数分辨能力，发现光子数信息存在于单个主成分中，基于Bhattacharyya系数提出新置信度指标，表明在FPGA上可实现高可扩展性的实时光子计数。

AutoQML：利用遗传算法在灰度图像上自动生成和训练鲁棒量子启发分类器

AutoQML: Automatic Generation and Training of Robust Quantum-Inspired Classifiers by Using Genetic Algorithms on Grayscale Images

本文提出AutoQML，利用多目标遗传算法自动生成并训练量子启发分类器，通过动态适应度函数和降维预处理，在灰度图像上实现高准确率与鲁棒性。

Robust Control of Quantum Dynamics under Input and Parameter Uncertainty

Despite significant progress in theoretical and laboratory quantum control, engineering quantum systems remains principally challenging due to manifestation of noise and uncertainties associated with the field and Hamiltonian parameters. In this paper, we extend and generalize the asymptotic quantum control robustness analysis method -- which provides more accurate estimates of quantum control objective moments than standard leading order techniques -- to diverse quantum observables, gates and moments thereof, and also introduce the Pontryagin Maximum Principle for quantum robust control. In a…