Advanced quantum technologies最新文献

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.

This image illustrates the process of Rydberg-based quantum-enhanced simulated annealing (QESA), which achieves faster computational performance than classical simulated annealing (SA). Harnessing Rydberg interactions tailored to the maximum independent set problem, QESA demonstrates a clear quantum advantage in heuristic optimization, pointing to a promising route for tackling complex combinatorial problems more efficiently than classical methods. More in article number 2500070, Jaewook Ahn and co-workers.

In the current quantum computing paradigm, significant focus is placed on the reduction or mitigation of quantum decoherence. When designing new quantum processing units, the general objective is to reduce the amount of noise qubits are subject to, and in algorithm design, a large effort is underway to provide scalable error correction or mitigation techniques. Yet some previous work has indicated that certain classes of quantum algorithms, such as quantum machine learning, may, in fact, be intrinsically robust to or even benefit from the presence of a small amount of noise. Here, we demonstrate that noise levels in quantum hardware can be effectively tuned to enhance the ability of quantum neural networks to generalize data, acting akin to regularisation in classical neural networks. As an example, we consider two regression tasks, where, by tuning the noise level in the circuit, we demonstrated improvement of the validation mean squared error loss. Moreover, we demonstrate the method's effectiveness by numerically simulating QNN training on a realistic model of a noisy superconducting quantum computer.

Bose-Einstein condensates (BECs) provide an ideal platform for exploring novel quantum states (QTs) in synthetic spin-orbit coupling (SOC). In article number 2500431, Yun Liu and Zu-Jian Ying analyse the interplay of SOC with other interactions and potential geometry by BECs in concentric annular traps. Various exotic QTs emerge, including facial-makeup states, fissure states, stripe states, half-disk states, half-skyrmion fence, etc. Peculiar density-phase separation is noticed. The study illustrates manipulations of exotic QTs and supplies abundant quantum resources for potential applications.

Research on the quantum nature of matter and light has flourished in recent years, as the field has grown for theorists and experimentalists alike. New research directions, such as the study of novel phases in quantum materials, have laid the ground for new foundational theories and future quantum technologies. In particular, novel topological materials and superconducting hybrid systems are promising for the development of novel superconductors and quantum computers.

This Focus Issue aims to highlight some of the latest achievements in the field of quantum matter. It includes 3 Reviews, 1 Perspective, and 3 Research Articles on a range of topics, including single-photon emitters for quantum technologies, topological quantum materials, and quantum sensing and metrology:

Rare-Earth Doped Thin Films for Optical Quantum Technologies (Philippe Goldner et al., 10.1002/qute.202500026): A Review article on rare earth-doped thin films—materials that are highly promising for use in on-chip photonic circuits thanks to their excellent coherence properties. The integration of rare-earth thin films into photonic platforms could potentially enable photonic quantum technologies, such as optical quantum memories, which are relevant for communications and processing.

Cuprate twistronics for quantum hardware (Nicola Poccia et al., 10.1002/qute.202500203): A topical Review on the emerging field of cuprate twistronics, which involves stacking and twisting ultrathin layers of cuprate superconductors. This technique creates Moiré patterns and new electronic states, uncovering new opportunities in both applied (e.g., quantum hardware) and fundamental physics.

Quantum spin Hall effects in van der Waals materials (Qiong Ma et al., 10.1002/qute.202500327): A Review of the Quantum Spin Hall (QSH) effect in two-dimensional van der Waals (vdW) materials. The QSH effect is promising for the development of low-power electronics and topological quantum computing. The article explores the main developments in the field, emerging research directions, as well as experimental challenges.

Beyond kagome: p-bands in kagome metals (Alexander Tsirlin et al., 10.1002/qute.202500336): A Perspective arguing that p-bands (electron bands from non-transition metals) play a critical, often overlooked, role in the electronic instabilities, such as charge-density waves and superconductivity, observed in kagome lattice metals.

High-purity single-photon emission in the telecom O-band from droplet-epitaxy InAs quantum dots integrated into a GaAs/AlGaAs planar microcavity on vicinal GaAs(111) (Battulga Munkhbat et al., 10.1002/qute.202500159): A Research article on developing a reliable source of single photons in the telecom O-band (a critical wavelength for fibre communication) using InAs quantum dots grown via droplet epitaxy. Single-photon emission from such sources could potentially be u

In article number 2500263, Zu-Jian Ying, Simone Felicetti, Daniel Braak, and co-workers propose a practical solution by introducing a feasible neutral quartic term to the standard two-photon quantum Rabi model. This modification prevents spectral collapse, turning it into a well-defined quantum phase transition. This work offers a paradigmatic approach to overcoming instability in NLLMIs, paving the way towards critical quantum sensing applications.