A decoding algorithm is provided for composite deletion-insertion errors in quantum deletion-correcting codes based on quantum Reed-Solomon codes.
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Hybrid feedback with a coherently coupled fast ancilla and a homodyne-current predictor achieves 3-4 times longer qubit T1 than the Wiseman-Milburn limit in Lindblad-derived rates and IBM-scale simulations.
A quantum-native MLD detector using Grover adaptive search with search space reduction achieves optimal performance in overloaded MIMO random access channels while cutting Grover rotations by up to 65%.
MADQRL distributes quantum RL across independent agents to achieve roughly 10% better performance than other distribution strategies and 5% over classical policy models in cooperative multi-agent games.
citing papers explorer
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Decoding Algorithm to Composite Errors Consisting of Deletions and Insertions for Quantum Deletion-Correcting Codes Based on Quantum Reed-Solomon Codes
A decoding algorithm is provided for composite deletion-insertion errors in quantum deletion-correcting codes based on quantum Reed-Solomon codes.
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Hybrid Predictive Quantum Feedback: Extending Qubit Lifetimes Beyond the Wiseman-Milburn Limit
Hybrid feedback with a coherently coupled fast ancilla and a homodyne-current predictor achieves 3-4 times longer qubit T1 than the Wiseman-Milburn limit in Lindblad-derived rates and IBM-scale simulations.
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Quantum-Native Maximum Likelihood Detection in Random Access Channel with Overloaded MIMO
A quantum-native MLD detector using Grover adaptive search with search space reduction achieves optimal performance in overloaded MIMO random access channels while cutting Grover rotations by up to 65%.
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MADQRL: Distributed Quantum Reinforcement Learning Framework for Multi-Agent Environments
MADQRL distributes quantum RL across independent agents to achieve roughly 10% better performance than other distribution strategies and 5% over classical policy models in cooperative multi-agent games.