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Article
Open AccessTheoretical guarantees for permutation-equivariant quantum neural networks
Despite the great promise of quantum machine learning models, there are several challenges one must overcome before unlocking their full potential. For instance, models based on quantum neural networks (QNNs) ...
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Article
Open AccessVariational quantum state eigensolver
Extracting eigenvalues and eigenvectors of exponentially large matrices will be an important application of near-term quantum computers. The variational quantum eigensolver (VQE) treats the case when the matri...
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Article
Variational quantum algorithms
Applications such as simulating complicated quantum systems or solving large-scale linear algebra problems are very challenging for classical computers, owing to the extremely high computational cost. Quantum ...