Direct coupling coherent quantum observers with discounted mean square performance criteria and penalized back-action

TL;DR

This paper develops a framework for designing coherent quantum observers that minimize a discounted mean square estimation error while controlling back-action through penalization, using algebraic conditions and numerical methods.

Contribution

It introduces a new optimal quantum filtering approach with penalized back-action, formulated via algebraic equations and solved for specific observer classes.

Findings

Derived bounds on observer back-action using small-gain theorem

Established first-order optimality conditions for the quantum filtering problem

Provided numerical examples demonstrating the observer synthesis process

Abstract

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.