Self-Guided Quantum State Learning for Mixed States

Self-guided quantum tomography

We introduce a self-learning tomographic technique in which the experiment guides itself to an estimate of its own state. Self-guided quantum tomography (SGQT) uses measurements to directly test hypotheses in an iterative algorithm which converges to the true state. We demonstrate through simulation on many qubits that SGQT is a more efficient and robust alternative to the usual paradigm of taking a large amount of informationally complete data and solving the inverse problem of post-processed state estimation.

正交化自引导量子成像：来自单像素成像的见解

Orthogonalised Self-Guided Quantum Tomography: Insights from Single-Pixel Imaging

本文提出正交化自引导量子成像，通过单像素成像的启发，实现更快更准确的收敛，提升成像 fidelity。

Experimental Demonstration of Self-Guided Quantum Tomography

Robust, accurate and efficient quantum tomography is key for future quantum technologies. Traditional methods are impractical for even medium sized systems and are not robust against noise and errors. Here we report on an experimental demonstration of self-guided quantum tomography; an autonomous, fast, robust and precise technique for measuring quantum states with significantly less computational resources than standard techniques. The quantum state is iteratively learned by treating tomography as a projection measurement optimization problem. We experimentally demonstrate robustness against …

时间-频率量子比特（qudits）的自导引层析

Self-guided tomography of time-frequency qudits

本文提出利用多输出量子脉冲门实现时间-频率高维量子态的自导引层析，无需校准或后处理即可对3维和5维态达到超过99%的保真度，并验证了其在光子匮乏及噪声环境下的鲁棒性。

量子混合态自注意力网络

Quantum Mixed-State Self-Attention Network

提出QMSAN，用混合态量子注意力直接计算查询-键相似度，并以固定量子门实现无额外量子比特的位置编码，文本分类性能优于QSANN且抗量子噪声。