Advanced quantum technologies最新文献

A silicon crystal hosts an ion implanted phosphorus atom with a nuclear spin surrounded by its simulated donor electron wavefunction in a quantum superposition between the donor atom and a potential well from an isolated surface electrode. A Moiré pattern arises from periodic localisation of the wavefunction around silicon atoms in the crystal that are spaced 0.5 nm apart. More in article number e00675, David N. Jamieson and co-workers.

The image shows a deterministically fabricated quantum-dot single-photon source integrated in a circular Bragg grating microresonator. Precise emitter placement at the resonator centre ensures efficient optical-mode coupling. A backside gold mirror yields highly directional, bright emission. The wavelength matches atom-based quantum memories, making the device a key component for scalable photonic quantum networks and integration. More in article number 2500782, Avijit Barua, Priyabrata Mudi, Stephan Reitzenstein, and co-workers.

The controlled integration of quantum dots (QDs) as single-photon emitters into quantum light sources is essential for the implementation of large-scale quantum networks. In this study, we employ the deterministic in situ electron-beam lithography (iEBL) nanotechnology platform to integrate individual QDs with high accuracy and process yield into a circular Bragg grating (CBG) resonators. Notably, CBG devices comprising just 3 to 4 rings exhibit photon extraction efficiencies comparable to those of structures with more rings. This facilitates faster fabrication, reduces the device footprint, and enables compatibility with electrical contacting. To demonstrate the scalability of this process, we present results of 95 optically active QD-CBG devices fabricated across two lithography sessions. These devices exhibit bright, narrow-linewidth single-photon emission with excellent optical quality. To evaluate QD placement accuracy, we apply a powerful characterization technique that combines cathodoluminescence (CL) mapping and scanning electron microscopy. Statistical analysis of these devices reveals that our iEBL approach enables high alignment accuracy and a process yield of over $��>�90�\%�$ across various CBG geometries. Our findings highlight a reliable route toward the scalable fabrication of high-performance QD-based single-photon sources for use in photonic quantum technology applications.

The Hyperband-QNN algorithm achieves adaptive customization of quantum neural network structure by skilfully integrating the essence of neural networks and the Hyperband optimization algorithm, perfectly matching the needs of various specific tasks. This groundbreaking method not only opens up a new path for the design of quantum neural networks but also sets a model for the deep integration of quantum computing and traditional computing. More in article number 2400178, Zheng Shan and co-workers.

Quantum-noise-driven diffusion models are proposed here as a novel class of quantum generative AI algorithms. These models aim to exploit the intrinsic noise of currently available quantum processing units, not as an issue to be solved by quantum error mitigation and correction, but instead as a beneficial resource to generate artificial, classical or quantum, data sampled from some unknown and usually very complex probability distribution that could be difficult or even impossible to sample from via classical computers. More in article number 2300401, Filippo Caruso and co-workers.

In article number 2400603, Alexey Melnikov and co-workers present a method to enhance the generalization capability of quantum machine learning models through controllable noise regularization. The cover visualizes a quantum circuit in which quantum gates are interleaved with engineered noise channels of tunable strength λ. This structured injection of noise acts as an implicit regularizer, stabilizing the training process and improving the model's predictive performance on previously unseen data.