REVIEW ARTICLE
This Review focuses on the practical implications of quantum machine learning (QML) algorithms and their applicability in real-world domains such as high-energy physics, healthcare, and finance. Despite rising interest in QML, the field contends with numerous challenges, particularly in execution on real quantum devices. This comprehensive exploration of the field delves into those challenges and the proposed solutions to overcome them. The authors provide an extensive survey of different techniques in QML, from data-encoding methods to model types, and offer insight into open questions in the field from a practical standpoint.
Yaswitha Gujju, Atsushi Matsuo, and Rudy Raymond
Phys. Rev. Applied 21, 067001 (2024)
LETTER
Transportable optical clocks are of great interest for applications in geodesy, because they allow the measurement of geopotential differences with high resolution via their relativistic redshift. So far demonstrations have been limited to short distances or low resolution, but this study presents a measurement between two laboratories separated by several hundred kilometers, with physical height resolution at the decimeter level. The authors compare the result to those obtained with the most accurate established methods in geodesy. Their approach is expected to lead to improved continental and global height reference frames, and connection of tide gauges for sea-level monitoring.
J. Grotti et al.
Phys. Rev. Applied 21, L061001 (2024)
LETTER
Active metamaterials promise advanced wave control beyond what is achievable with passive structures. Practical bulk devices have yet to be realized, though, for lack of a method to assess the stability of interacting cells. The authors address this obstacle by developing a general stability analysis that requires only the frequency response of an isolated unit cell to determine the stability of metamaterials of many such cells arranged in arbitrary geometries. This analysis is used to accurately predict the stability bounds of an experimental active acoustic metamaterial, and to reveal key constraints that must be respected when designing e.g. waveguides, cloaks, or noise absorbers.
Dylan A. Kovacevich, Karl Grosh, and Bogdan-Ioan Popa
Phys. Rev. Applied 21, L051002 (2024)
EDITORS' SUGGESTION
The cocktail party effect refers to the brain’s ability to focus on a single auditory stimulus amidst the cacophony of background noise. This selective attention also resonates in electromagnetic telecommunication, where the surge in wireless communication exacerbates signal interference. To address that issue, researchers have developed reconfigurable intelligent surfaces, mirrors that dynamically shape their reflectivity to enhance wireless performance. Drawing inspiration from these advancements, the authors propose to extend this concept to the acoustic domain, where similar issues of signal clarity and interference persist, but over a much wider frequency range.
Constant Bourdeloux, Mathias Fink, and Fabrice Lemoult
Phys. Rev. Applied 21, 054039 (2024)
EDITORS' SUGGESTION
Using cavity quantum electrodynamics to enhance light-matter interaction has been pursued with increasing efforts to develop miniaturized, stable, and fully integrated systems for quantum networks or secure communication. Hybrid systems combining photonic platforms and quantum systems are a valid option, but accessing individual spin states remains challenging. This work explores the combination of silicon nitride photonics and negatively charged silicon-vacancy centers in nanodiamonds as a spin-photon interface and elaborates on the hybrid system’s performance. The results can be used to benchmark and outline future spin-based quantum photonic devices.
Lukas Antoniuk et al.
Phys. Rev. Applied 21, 054032 (2024)
EDITORS' SUGGESTION
Nanomechanical computers promise robust, low-energy information processing, but generally require electronics to handle bits with different oscillation frequencies, limiting scalability. The authors present an acoustically driven logic gate with a single frequency of operation, with the logic states defined by a nonlinear mechanical resonator, allowing purely mechanical information transfer. Since inputs and output all share the same frequency, they are compatible with cascaded chains of gates. This architecture is CMOS-compatible, and with miniaturization could permit energy efficiency approaching the fundamental Landauer limit.
Erick Romero et al.
Phys. Rev. Applied 21, 054029 (2024)
EDITORS' SUGGESTION
Defective devices can severely impact the performance of hardware-based neural networks, in particular resistive crossbar arrays. This study introduces a network training approach that reduces the influence of defective devices, maintaining inference accuracy. The authors demonstrate this approach on a set of dies each containing a crossbar array consisting of 20,000 magnetic tunnel junction devices. They also develop a generalized approach using the statistics of defects and demonstrate similar performance on all dies. These results translate to a manufacturing setting where millions of dies with possible defects are produced, but the performance of even subpar chips can be guaranteed.
William A. Borders et al.
Phys. Rev. Applied 21, 054028 (2024)
PERSPECTIVE
Spin waves and their quanta magnons are the collective excitations of a spin systems of a magnetic material, which offer the potential for higher efficiency and lower energy consumption in solving specific issues in data processing. This Perspective discusses the current challenges in realizing magnonic circuits based on the building blocks developed to date, and further looks at the application of magnons in neuromorphic networks and stochastic, reservoir, and quantum computing, and discusses their advantages over conventional electronics in these areas.
Qi Wang et al.
Phys. Rev. Applied 21, 040503 (2024)
PERSPECTIVE
Dynamic beamforming is critical in applications such as radar detection, holographic imaging, and reconfigurable intelligent surfaces (RIS). This Perspective reviews a revolutionary and economical technique to achieve dynamic beamforming, utilizing the moiré pattern formed by twisted stacked metasurfaces. Research here faces challenges such as far-field calculations and the inverse design of specific radiation patterns, due to our limited understanding of the complex mode coupling between the moiré pattern and the metallic back plate. The authors outline potential solutions and project the future applications and research directions for the reflective moiré metasurface.
Shuo Liu and Tie Jun Cui
Phys. Rev. Applied 21, 040502 (2024)