Advances in quantum entanglement purification
PS Yan, L Zhou, W Zhong, YB Sheng - Science China Physics, Mechanics …, 2023 - Springer
Since its discovery, the quantum entanglement becomes a promising resource in quantum
communication and computation. However, the entanglement is fragile due to the presence …
communication and computation. However, the entanglement is fragile due to the presence …
Near-term quantum computing techniques: Variational quantum algorithms, error mitigation, circuit compilation, benchmarking and classical simulation
Quantum computing is a game-changing technology for global academia, research centers
and industries including computational science, mathematics, finance, pharmaceutical …
and industries including computational science, mathematics, finance, pharmaceutical …
Quantum convolutional neural network for classical data classification
With the rapid advance of quantum machine learning, several proposals for the quantum-
analogue of convolutional neural network (CNN) have emerged. In this work, we benchmark …
analogue of convolutional neural network (CNN) have emerged. In this work, we benchmark …
Amplitude transformed quantum convolutional neural network
S Di, J Xu, G Shu, C Feng, X Ding, Z Shan - Applied Intelligence, 2023 - Springer
With the rapid development of quantum neural networks (QNN), several quantum
simulations of convolutional neural networks (CNN) have been proposed. Among them …
simulations of convolutional neural networks (CNN) have been proposed. Among them …
Recent advances for quantum classifiers
Abstract Machine learning has achieved dramatic success in a broad spectrum of
applications. Its interplay with quantum physics may lead to unprecedented perspectives for …
applications. Its interplay with quantum physics may lead to unprecedented perspectives for …
Multiclass seismic damage detection of buildings using quantum convolutional neural network
The traditional visual inspection technique for damage assessment of buildings immediately
after an earthquake can be time‐consuming, labor‐intensive, and risky. Numerous studies …
after an earthquake can be time‐consuming, labor‐intensive, and risky. Numerous studies …
A survey of NISQ era hybrid quantum-classical machine learning research
G De Luca - Journal of Artificial Intelligence and Technology, 2022 - ojs.istp-press.com
Quantum computing is a rapidly growing field that has received a significant amount of
support in the past decade in industry and academia. Several physical quantum computers …
support in the past decade in industry and academia. Several physical quantum computers …
Better than classical? the subtle art of benchmarking quantum machine learning models
Benchmarking models via classical simulations is one of the main ways to judge ideas in
quantum machine learning before noise-free hardware is available. However, the huge …
quantum machine learning before noise-free hardware is available. However, the huge …
Hybrid quantum-classical convolutional neural network model for image classification
Image classification plays an important role in remote sensing. Earth observation (EO) has
inevitably arrived in the big data era, but the high requirement on computation power has …
inevitably arrived in the big data era, but the high requirement on computation power has …
Circuit complexity of quantum access models for encoding classical data
How to efficiently encode classical data is a fundamental task in quantum computing. While
many existing works treat classical data encoding as a black box in oracle-based quantum …
many existing works treat classical data encoding as a black box in oracle-based quantum …