Results 121 to 130 of about 23,653 (255)
Quantum machine learning with canonical variables [PDF]
Utilising dynamic electromagnetic field control over charged particles serves as the basis for a quantum machine learning platform that operates on observables rather than directly on states. Such a platform can be physically realised in ion traps or particle confinement devices that utilise electromagnetic fields as the source of control.
openaire +2 more sources
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang +5 more
wiley +1 more source
Stress‐to‐Light Conversion in an Earth‐Abundant Oxide Semiconductor
Stress‐to‐light conversion in solids represents a unique photonic functionality, yet it has never been realized in a chemically simple and sustainable material. Here, we show that sustainable semiconductor ZnO exhibits strong near‐infrared (NIR) luminescence under elastic stress when defect‐engineered to stabilize the p‐type state.
Tomoki Uchiyama +7 more
wiley +1 more source
Flexoelectricity in Photoconversion: Fundamentals, Materials, and Outlooks
Mechanical bending of a flexible cantilever induces a strain gradient in the photoactive material. The resulting flexoelectric field couples with photovoltaic and photoconductive effects, modulating charge generation, separation, and collection. A comparative analysis of oxide perovskites, halide perovskites, and two‐dimensional materials is presented,
Xiang Huang, Feng Li, Rongkun Zheng
wiley +1 more source
Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh +8 more
wiley +1 more source
Quantum ensemble learning with a programmable superconducting processor
Quantum machine learning is among the most exciting potential applications of quantum computing. However, the vulnerability of quantum information to environmental noises and the consequent high cost for realizing fault tolerance has impeded the quantum ...
Jiachen Chen +32 more
doaj +1 more source
Bias‐Tunable Two‐Terminal Organic Photodetector for Intelligent Imaging
A vertically stacked two‐terminal photodetector with a symmetric donor–acceptor–donor trilayer active exhibits reconfigurable photoresponse with bias‐tunable magnitude and polarity, together with sub‐millisecond response speed and a wide tunable output window.
Sangin Hahn +2 more
wiley +1 more source
Implementation and empirical evaluation of a quantum machine learning pipeline for local classification. [PDF]
Zardini E, Blanzieri E, Pastorello D.
europepmc +1 more source
Quantum memristors for neuromorphic quantum machine learning
Invited ...
openaire +2 more sources
This work proposes and constructs the Hefei‐NAMD‐S framework based on machine learning stacked models to investigate the relationship between local polarization and non‐radiative recombination. The results indicate that, compared with A‐site local polarization, B‐site local polarization shows a more evident association with the non‐radiative ...
Bing Yang +13 more
wiley +1 more source

