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The purpose of this paper is to study the mixed linear quadratic Gaussian (LQG) andH∞optimal control problem for linear quantum stochastic systems, where the controller itself is also a quantum system, often referred to as ‘coherent feedback controller’. A lower bound of the LQG control is proved. Then two different methods, rank-constrained linear matrix inequality method and genetic algorithm are for controller design. A passive system (cavity) and a non-passive one (degenerate parametric amplifier) demonstrate the effectiveness of these two proposed algorithms. [ABSTRACT FROM PUBLISHER]

The purpose of this article is to present an efficient coherent feedback control technique for squeezing enhancement of degenerate parametric amplifiers (DPAs). The feedback controllers to be designed are in the form of linear quantum stochastic systems which can be described by quantum feedback networks theory recently developed. The problem of squeezing enhancement is formulated as a non-convex constrained nonlinear programming problem, whose solution yields the coherent feedback controllers to be designed. Compared with the previous study, the proposed approach reveals clear advantage when DPAs are lossy, as is always the case in practice. Based on the recently developed quantum network synthesis theory, we show how the designed coherent feedback controllers can be implemented by means of quantum optical devices. [ABSTRACT FROM AUTHOR]