An augmented neural ODE framework learns single-qubit states and time-dependent dissipation parameters from simulated weak-measurement data, and supports PD and LQR feedback control.
The evolution of the Bloch vec- tor is governed by the ˆY(t) = [ˆx(t),ˆy(t),ˆz(t)]T , and the control fieldsu x(t), uy(t) are applied via the Hamiltonian operatorsA x andA y
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Quantum Filtering and Stabilization of Dissipative Quantum Systems via Augmented Neural Ordinary Differential Equations
An augmented neural ODE framework learns single-qubit states and time-dependent dissipation parameters from simulated weak-measurement data, and supports PD and LQR feedback control.