An attention-based DRL agent with Transformer encoder and GNN learns heuristics for qubit-to-core allocation in multi-core quantum systems to minimize state transfers and online compilation time.
Pytorch: An imperative style, high-performance deep learning library,
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quant-ph 2years
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Two neural network architectures achieve state-of-the-art performance in quantum state tomography for pure and mixed states by incorporating class information.
citing papers explorer
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Attention-Based Deep Reinforcement Learning for Qubit Allocation in Modular Quantum Architectures
An attention-based DRL agent with Transformer encoder and GNN learns heuristics for qubit-to-core allocation in multi-core quantum systems to minimize state transfers and online compilation time.
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Optical Quantum Mixed-State Reconstruction With Multiple Deep Learning Approaches
Two neural network architectures achieve state-of-the-art performance in quantum state tomography for pure and mixed states by incorporating class information.