Direct coupling coherent quantum observers with discounted mean square performance criteria and penalized back-action
For researchers in quantum control and estimation, this work provides a theoretical framework for optimal coherent quantum filtering with explicit conditions, though it is incremental as it extends existing methods to discounted criteria and back-action penalties.
This paper addresses the problem of designing directly coupled coherent quantum observers for quantum harmonic oscillators, using discounted mean square performance criteria with penalized back-action. The authors derive first-order necessary conditions for optimality and provide a solution for a class of observers with autonomous error dynamics, illustrated with numerical examples.
This paper is concerned with quantum harmonic oscillators consisting of a quantum plant and a directly coupled coherent quantum observer. We employ discounted quadratic performance criteria in the form of exponentially weighted time averages of second-order moments of the system variables. Small-gain-theorem bounds are obtained for the back-action of the observer on the covariance dynamics of the plant in terms of the plant-observer coupling. A coherent quantum filtering (CQF) problem is formulated as the minimization of the discounted mean square of an estimation error, with which the dynamic variables of the observer approximate those of the plant. The cost functional also involves a quadratic penalty on the plant-observer coupling matrix in order to mitigate the back-action effect. For the discounted mean square optimal CQF problem with penalized back-action, we establish first-order necessary conditions of optimality in the form of algebraic matrix equations. By using the Hamiltonian structure of the Heisenberg dynamics and Lie-algebraic techniques, this set of equations is represented in a more explicit form for equally dimensioned plant and observer. For a class of such observers with autonomous estimation error dynamics, we obtain a solution of the CQF problem and outline a homotopy method. The computation of the performance criteria and the observer synthesis are illustrated by numerical examples.