QKAN is a quantum algorithmic framework using block-encodings and QSVT to implement wide-and-shallow networks for quantum learning and compositional state preparation.
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QuNetQFL is a quantum federated learning protocol using distributed quantum keys for secure aggregation, experimentally validated on a four-client quantum network with scalability simulations to 200 clients and applications to quantum datasets and hybrid language models.
A two-step method minimizes entanglement entropy of target states before using matrix product state representations to achieve high-accuracy quantum state preparation on NISQ devices.
citing papers explorer
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QKAN: quantum Kolmogorov-Arnold networks with applications in machine learning and multivariate state preparation
QKAN is a quantum algorithmic framework using block-encodings and QSVT to implement wide-and-shallow networks for quantum learning and compositional state preparation.
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Experimentally validated quantum-secure federated learning over a multi-user quantum network
QuNetQFL is a quantum federated learning protocol using distributed quantum keys for secure aggregation, experimentally validated on a four-client quantum network with scalability simulations to 200 clients and applications to quantum datasets and hybrid language models.
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Minimizing entanglement entropy for enhanced quantum state preparation
A two-step method minimizes entanglement entropy of target states before using matrix product state representations to achieve high-accuracy quantum state preparation on NISQ devices.