Connects coherent equalization for linear quantum systems to the classical two-disk H∞ problem to handle a broader class of channels.
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Deep reinforcement learning applied to measurement-based quantum feedback control achieves faster stabilization of random initial states to target entangled states in two- and three-qubit systems than Lyapunov feedback or alternative DRL reward designs.
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A two-disk approach to the synthesis of coherent passive equalizers for linear quantum systems
Connects coherent equalization for linear quantum systems to the classical two-disk H∞ problem to handle a broader class of channels.
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Fast State Stabilization using Deep Reinforcement Learning for Measurement-based Quantum Feedback Control
Deep reinforcement learning applied to measurement-based quantum feedback control achieves faster stabilization of random initial states to target entangled states in two- and three-qubit systems than Lyapunov feedback or alternative DRL reward designs.