31 citations · 41 across the 5 of their papers we have counts for
5 papers
Learning quantum properties from short-range correlations using multi-task networks
Ya-Dong Wu, Yan Zhu, Yuexuan Wang +1
Characterizing multipartite quantum systems is crucial for quantum computing and many-body physics. The problem, however, becomes challenging when the system size is large and the…
Quantum Process Learning Through Neural Emulation
Yan Zhu, Ya-Dong Wu, Qiushi Liu +2
Neural networks are a promising tool for characterizing intermediate-scale quantum devices from limited amounts of measurement data. A challenging problem in this area is to learn…
Quantum Similarity Testing with Convolutional Neural Networks
Ya-Dong Wu, Yan Zhu, Ge Bai +2
The task of testing whether two uncharacterized quantum devices behave in the same way is crucial for benchmarking near-term quantum computers and quantum simulators, but has so fa…
Flexible learning of quantum states with generative query neural networks
Yan Zhu, Ya-Dong Wu, Ge Bai +3
Deep neural networks are a powerful tool for the characterization of quantum states. Existing networks are typically trained with experimental data gathered from the specific quant…
Quantum autoencoders for communication-efficient quantum cloud computing
Yan Zhu, Ge Bai, Yuexuan Wang +2
In the model of quantum cloud computing, the server executes a computation on the quantum data provided by the client. In this scenario, it is important to reduce the amount of qua…