Results 61 to 70 of about 3,092 (256)
Variational quantum algorithm for node embedding
Quantum machine learning has made remarkable progress in many important tasks. However, the gate complexity of the initial state preparation is seldom considered in lots of quantum machine learning algorithms, making them non-end-to-end. Herein, we propose a quantum algorithm for the node embedding problem that maps a node graph's topological structure
Zeng-rong Zhou, Hang Li, Gui-Lu Long
openaire +3 more sources
Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long +26 more
wiley +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
Reducing quantum resources for attacking S-AES on quantum devices
The Advanced Encryption Standard (AES) is one of the most widely used symmetric block cipher cryptography algorithms. Simplified-AES (S-AES) retains the structural framework of AES, making it an ideal model for elucidating the mechanism of symmetric ...
Zeguo Wang +5 more
doaj +1 more source
Variational quantum optimization with multibasis encodings
Despite extensive research efforts, few quantum algorithms for classical optimization demonstrate a realizable quantum advantage. The utility of many quantum algorithms is limited by high requisite circuit depth and nonconvex optimization landscapes.
Taylor L. Patti +3 more
doaj +1 more source
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Variational quantum algorithm for entanglement quantification
Quantum entanglement is a foundational resource in quantum information science, underpinning applications across physics. However, detecting and quantifying entanglement remains a significant challenge. In this article, we introduce a variational quantum algorithm inspired by Uhlmann's theorem to quantify the Bures entanglement of general quantum ...
Lucas Friedrich +6 more
openaire +2 more sources
Transition metal oxy/carbo‐nitrides show great promise as catalysts for sustainable processes. A Mn‐Mo mixed‐metal oxynitride attains remarkable performance for the direct synthesis of acetonitrile, an important commodity chemical, via sequential C─N and C─C coupling from syngas (C1) and ammonia (N1) feedstocks.
M. Elena Martínez‐Monje +7 more
wiley +1 more source
Self‐Cooling Molecular Spin Qudits
A material made of [GdEr] molecular dimers can encode a qudit and perform as a magnetic refrigerant. Microwave resonant pulses coherently manipulate its 16 spin states, while direct demagnetization measurements cool the material and a device down to temperatures below 1 K.
Elías Palacios +12 more
wiley +1 more source
Verifiable end-to-end delegated variational quantum algorithms
Variational quantum algorithms (VQAs) have emerged as promising candidates for solving complex optimization and machine learning tasks on near-term quantum hardware.
Matteo Inajetovic +2 more
doaj +1 more source

