Variational quantum circuits are one of the promising ways to exploit the advantages of quantum computing in the noisy intermediate-scale quantum technology era. The design of the quantum circuit architecture might greatly affect the performance capability of the quantum algorithms. The quantum architecture search is the process of automatically designing quantum circuit architecture, aiming at finding the optimal quantum circuit composition architecture by the algorithm for a given task, so that the algorithm can learn to design the circuit architecture. Compared to manual design, quantum architecture search algorithms are more effective in finding quantum circuits with better performance capabilities. In this paper, based on the deep reinforcement learning, we propose an approach for quantum circuit architecture search. The sampling of the circuit architecture is learnt through reinforcement learning-based controller. Layer-based search is also used to accelerate the computational efficiency of the search algorithm. Applying to data classification tasks, we show that the method can search for quantum circuit architectures with better accuracies. Moreover, the circuit has a smaller number of quantum gates and parameters.

We provide a class of positive and trace-preserving maps based on symmetric measurements. From these positive maps we present separability criteria, entanglement witnesses, and the lower bounds of concurrence. We show by detailed examples that our separability criteria, entanglement witnesses, and lower bounds can detect and estimate the quantum entanglement better than existing related results.

作者：Qing-Hua Zhang, Shao-Ming Fei（通讯作者） 期刊名称： J. Phys. A 57 (2024) 235301 摘要：Quantum coherence constitutes a foundational characteristic of quantum mechanics and is integral to emerging quantum resource theories. However, quantum coherence is severely restricted by environmental noise in general quantum processing, indicated by the loss of information of a quantum system. Such processing can be described by the trade-offs between the coherence and the mixedness. Based on the $l_2$ norm coherence, conditional von Neumann entropy and Wigner–Yanase skew information, we derive basis-independent constraints on the attainable quantum coherence imposed by the mixedness of a quantum state, which generalize the prior basis-dependent relations, provide fundamental insights into the latent coherence resources present within arbitrary quantum systems that undergo decoherence and quantify the inherent limits on extractable coherence imposed by environmental noise.

作者：黄岚馨、苏加宝（通讯作者） 论文题目：Multiple positive solutions of the quasilinear Schrodinger-Poisson system with critical exponent in D^{1,p}(R^3) 期刊名称： Journal of Mathematical Physics, 65 (2024), 050512

作者：费少明 研究员（通讯作者）
出版物：Quant. Inform. Processing

作者：费少明 研究员（其他）
出版刊物：Results in Physics60 (2024) 107671

作者：杜瑶、苏加宝（通讯作者） Journal of Mathematical Analysis and Applications, 536 (2024), 128272.

作者：杜瑶、苏加宝（通讯作者） 期刊：Differential and Integral Equations, 37, 7/8(2024), 423--546。

作者：费少明 研究员（其他）
出版刊物：Cell Reports Physical Science 5，101840