Measurement-based Initial Point Smoothing and Control Approach to Quantum Memory Systems

TL;DR

This paper introduces a measurement-based smoothing and control method for quantum memory systems, enhancing initial state preservation amid environmental noise using classical controllers and quantum stochastic differential equations.

Contribution

It proposes a novel initial-point smoothing approach combining quantum and classical control techniques for improved quantum memory stability.

Findings

Effective initial state deviation minimization

Integration of quantum and classical control methods

Enhanced quantum memory fidelity

Abstract

This paper is concerned with a quantum memory system for storing quantum information in the form of its initial dynamic variables in the presence of environmental noise. In order to compensate for the deviation from the initial conditions, the classical parameters of the system Hamiltonian are affected by the actuator output of a measurement-based classical controller. The latter uses an observation process produced by a measuring apparatus from the quantum output field of the memory system. The underlying system is modelled as an open quantum harmonic oscillator whose Heisenberg evolution is governed by linear Hudson-Parthasarathy quantum stochastic differential equations. The controller is organised as a classical linear time-varying system, so that the resulting closed-loop system has quantum and classical dynamic variables. We apply linear-quadratic-Gaussian control and fixed-point smoothing at the level of the first two moments and consider controllers with a separation structure which involve a continuously updated estimate for the initial quantum variables. The initial-point smoother is used for actuator signal formation so as to minimise the sum of a mean-square deviation of the quantum memory system variables at a given time horizon from their initial values and an integral quadratic penalty on the control signal.