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Found 8 papers, 5 papers with code
Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm
In recent years, quantum computing has emerged as a transformative force in the field of combinatorial optimization, offering novel approaches to tackling complex problems that have long challenged classical computational methods.
Privacy-preserving quantum federated learning via gradient hiding
Distributed quantum computing, particularly distributed quantum machine learning, has gained substantial prominence for its capacity to harness the collective power of distributed quantum resources, transcending the limitations of individual quantum nodes.
NAPA: Intermediate-level Variational Native-pulse Ansatz for Variational Quantum Algorithms
Therefore, we propose NAPA, a native-pulse ansatz generator framework for VQAs.
Practical distributed quantum information processing with LOCCNet
Here we introduce LOCCNet, a machine learning framework facilitating protocol design and optimization for distributed quantum information processing tasks.
Detecting and quantifying entanglement on near-term quantum devices
Firstly, it decomposes a positive map into a combination of quantum operations implementable on near-term quantum devices.
Quantum Physics Strongly Correlated Electrons
VSQL: Variational Shadow Quantum Learning for Classification
Classification of quantum data is essential for quantum machine learning and near-term quantum technologies.
Variational Quantum Algorithms for Trace Distance and Fidelity Estimation
A novel variational algorithm for trace distance estimation is then derived from this technique, with the assistance of a single ancillary qubit.
Quantum Physics Information Theory Mathematical Physics Information Theory Mathematical Physics Optimization and Control
Variational Quantum Singular Value Decomposition
In this work, we propose a variational quantum algorithm for singular value decomposition (VQSVD).
