Entanglement detection with artificial neural networks
Quantum entanglement is one of the essential resources involved in quantum information
processing tasks. However, its detection for usage remains a challenge. The Bell-type …
processing tasks. However, its detection for usage remains a challenge. The Bell-type …
Direct fidelity estimation of quantum states using machine learning
X Zhang, M Luo, Z Wen, Q Feng, S Pang, W Luo… - Physical Review Letters, 2021 - APS
In almost all quantum applications, one of the key steps is to verify that the fidelity of the
prepared quantum state meets expectations. In this Letter, we propose a new approach …
prepared quantum state meets expectations. In this Letter, we propose a new approach …
Detecting quantum entanglement with unsupervised learning
Quantum properties, such as entanglement and coherence, are indispensable resources in
various quantum information processing tasks. However, there still lacks an efficient and …
various quantum information processing tasks. However, there still lacks an efficient and …
Entanglement verification with deep semisupervised machine learning
L Zhang, Z Chen, SM Fei - Physical Review A, 2023 - APS
Quantum entanglement lies at the heart of quantum information-processing tasks. Although
many criteria have been proposed, efficient and scalable methods to detect the …
many criteria have been proposed, efficient and scalable methods to detect the …
Automated machine learning for secure key rate in discrete-modulated continuous-variable quantum key distribution
Continuous-variable quantum key distribution (CV QKD) with discrete modulation has
attracted increasing attention due to its experimental simplicity, lower-cost implementation …
attracted increasing attention due to its experimental simplicity, lower-cost implementation …
Building separable approximations for quantum states via neural networks
Finding the closest separable state to a given target state is a notoriously difficult task, even
more difficult than deciding whether a state is entangled or separable. To tackle this task, we …
more difficult than deciding whether a state is entangled or separable. To tackle this task, we …
Efficient learning of mixed-state tomography for photonic quantum walk
QQ Wang, S Dong, XW Li, XY Xu, C Wang, S Han… - Science …, 2024 - science.org
Noise-enhanced applications in open quantum walk (QW) has recently seen a surge due to
their ability to improve performance. However, verifying the success of open QW is …
their ability to improve performance. However, verifying the success of open QW is …
Quantifying entanglement for unknown quantum states via artificial neural networks
GZ Pan, M Yang, J Zhou, H Yuan, C Miao, G Zhang - Scientific Reports, 2024 - nature.com
Quantum entanglement acts as a crucial part in quantum computation and quantum
information, hence quantifying unknown entanglement is an important task. Due to the fact …
information, hence quantifying unknown entanglement is an important task. Due to the fact …
Neural network-based prediction of the secret-key rate of quantum key distribution
Numerical methods are widely used to calculate the secure key rate of many quantum key
distribution protocols in practice, but they consume many computing resources and are too …
distribution protocols in practice, but they consume many computing resources and are too …
Efficient bipartite entanglement detection scheme with a quantum adversarial solver
The recognition of entanglement states is a notoriously difficult problem when no prior
information is available. Here, we propose an efficient quantum adversarial bipartite …
information is available. Here, we propose an efficient quantum adversarial bipartite …