A hardware-realizable tunable partial-SWAP is introduced to control the rate of memory dissipation in recurrent quantum reservoir computing architectures, validated via simulation and IBM QPUs.
Feedback-driven recurrent quantum neural network universality, 2026
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The paper unifies fading memory, echo states, and related memory notions in RNNs via new equivalences, implications, and alternative proofs.
Recurrent quantum feature maps achieve lower mean squared error than echo state networks and multilayer perceptrons on Mackey-Glass prediction using compact quantum circuits.
citing papers explorer
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Controllable Quantum Memory Capacity in Quantum Reservoir Networks with Tunable partial-SWAPs
A hardware-realizable tunable partial-SWAP is introduced to control the rate of memory dissipation in recurrent quantum reservoir computing architectures, validated via simulation and IBM QPUs.
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Echoes of the Past: A Unified Perspective on Fading memory and Echo States
The paper unifies fading memory, echo states, and related memory notions in RNNs via new equivalences, implications, and alternative proofs.
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Recurrent Quantum Feature Maps for Reservoir Computing
Recurrent quantum feature maps achieve lower mean squared error than echo state networks and multilayer perceptrons on Mackey-Glass prediction using compact quantum circuits.