We derive simple models for the dynamics of a single atom coupled to a cavity field mode in the absorptive bistable parameter regime by projecting the time evolution of the state of the system onto a suitably chosen nonlinear low-dimensional manifold, which is found by use of local tangent space alignment. The output field from the cavity is detected with a homodyne detector allowing observation of quantum jumps of the system between states with different average numbers of photons in the cavity. We find that the models, which are significantly faster to integrate numerically than the full stochastic master equation, largely reproduce the dynamics of the system, and we demonstrate that they are sufficiently accurate to facilitate feedback control of the state of the system based on the predictions of the models alone.
We derive simple models for the dynamics of a single atom coupled to a cavity field mode in the absorptive bistable parameter regime by projecting the time evolution of the state of the system onto a suitably chosen nonlinear low-dimensional manifold, which is found by use of local tangent space alignment. The output field from the cavity is detected with a homodyne detector allowing observation of quantum jumps of the system between states with different average numbers of photons in the cavity. We find that the models, which are significantly faster to integrate numerically than the full stochastic master equation, largely reproduce the dynamics of the system, and we demonstrate that they are sufficiently accurate to facilitate feedback control of the state of the system based on the predictions of the models alone.
Many quantum mechanical systems require large (potentially infinite) numbers of variables to exactly describe their state. In this thesis, I examine two approaches to develop simple, approximate models for such systems, which capture their essential dynamics. I use two bistable regimes of the Jaynes-Cummings model of cavity quantum electrodynamics as example systems to evaluate the effectiveness of each approach. In the phase bistable regime (which occurs with large driving field, and which I study in an on-resonance "bad cavity" regime to make numerical simulations tractable), the cavity field switches between two states with identical amplitude but opposite phase. In the absorptive bistable regime (which I study with small driving field in an on-resonance "good cavity"'), two stable regions of state space differ in cavity field amplitude as well as their shape and qualitative behavior. After introducing these two regimes and their dynamics, I give a short introduction to projecting dynamical equations onto linear subspaces. Proper Orthogonal Decomposition (POD) allows the algorithmic construction of subspaces onto which the dynamics may be projected. I demonstrate that the application of POD to phase bistability results in effective approximate filters, while the asymmetry of the absorptive bistable case requires extensions to POD, developed in this thesis, to create a functional filter. Local Tangent Space Alignment is one of a class of unsupervised manifold learning algorithms which use the local geometry of high-dimensional data, such as quantum trajectories, to calculate the coordinates of that data on a low-dimensional manifold. I show how this algorithm functions, and characterize the manifolds that result from phase and absorptive bistability. I fit the 3-dimensional phase bistable manifold with a small set of system observables, and create a three-dimensional set of equations (similar to the semi-classical Maxwell-Bloch equations) which perform very well as a filter. Absorptive bistability again proves to be more complicated, but I am able to show that the underlying manifold is small, and make some progress on characterizing its relations with system observables.
Both in classical and quantum stochastic control theory a major role is played by the filtering equation, which recursively updates the information state of the system under observation. Unfortunately, the theory is plagued by infinite-dimensionality of the information state which severely limits its practical applicability, except in a few select cases (e.g. the linear Gaussian case.) One solution proposed in classical filtering theory is that of the projection filter. In this scheme, the filter is constrained to evolve in a finite-dimensional family of densities through orthogonal projection on the tangent space with respect to the Fisher metric. Here we apply this approach to the simple but highly nonlinear quantum model of optical phase bistability of a stongly coupled two-level atom in an optical cavity. We observe near-optimal performance of the quantum projection filter, demonstrating the utility of such an approach.
Both in classical and quantum stochastic control theory a major role is played by the filtering equation, which recursively updates the information state of the system under observation. Unfortunately, the theory is plagued by infinite-dimensionality of the information state which severely limits its practical applicability, except in a few select cases (e.g. the linear Gaussian case.) One solution proposed in classical filtering theory is that of the projection filter. In this scheme, the filter is constrained to evolve in a finite-dimensional family of densities through orthogonal projection on the tangent space with respect to the Fisher metric. Here we apply this approach to the simple but highly nonlinear quantum model of optical phase bistability of a stongly coupled two-level atom in an optical cavity. We observe near-optimal performance of the quantum projection filter, demonstrating the utility of such an approach.
In this paper, we examine an open quantum system that is subject to indirect and imperfect measurements. Specifically, for quantum non-demolition (QND) measurements, we show that the evolution of the system is confined to a properly selected manifold. This allows us to express the exact solution of the quantum filter equation in terms of a lower-dimensional stochastic differential equation, significantly reducing the computational complexity. Motivated by a quantum state reduction result for the predicted dynamics under QND measurement, we propose, in the case when the Hamiltonian and the coupling operator do not commute, a projection filter approach for the quantum state estimation. The efficiency of the proposed quantum projection filter is verified by numerical simulations. The latter suggest that, even when paired with a stabilizing feedback control mechanism that depends on the projected state, the filter maintains its robustness. More generally, our numerical results suggest the effectiveness of the adopted quantum projection filter approach as a method for state estimation and feedback stabilization of open quantum systems.
The cavity is a fundamental ingredient of quantum optical systems. This paper concerns the behavior of a quantum cavity driven by non-classical field in single-photon state. To this end, the number operator has been opted to reveal the number of photons inside the cavity. Then, the quantum filtering equations have been employed to derive a stochastic master equation for the cavity which is driven by single-photon and is observed by either Homodyne or photon-counting detector. Finally, the state of the cavity has been estimated by the derived equations, and the results have been compared with the conventional master equation.
This review develops a control-theoretic perspective on measurement-based feedback for continuously monitored open quantum systems, with the main analysis focused on finite-dimensional systems governed by diffusive stochastic master equations. We introduce the relevant state-space, invariant-subspace, and quantum non-demolition structures, interpret quantum filtering as nonlinear observer dynamics, and review open-loop asymptotics, filter stability, state-feedback stabilization, robustness, and reduced-order observer-based control. Particular emphasis is placed on a recurrence--contraction framework, in which Hamiltonian feedback removes non-target invariant obstructions while measurement-induced dynamics provide local exponential contraction. Although the detailed analysis is developed for finite-dimensional diffusive models, the underlying measurement--estimation--feedback architecture is relevant across a broad range of quantum platforms. We further discuss implementation challenges and open problems involving scalable estimation, sampling and delay, adaptation, hybrid and non-Markovian dynamics, practical stability, optimal control, and learning-based design. By organizing these developments around invariance, estimation, recurrence, and contraction, the review provides a tutorial bridge between measurement-based quantum feedback and nonlinear stochastic control.