612 research outputs found
Quantum projection filter for a highly nonlinear model in cavity QED
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.Comment: 19 pages, 6 figures. A version with high quality images can be found
at http://minty.caltech.edu/papers.ph
Almost Sure Stabilization for Adaptive Controls of Regime-switching LQ Systems with A Hidden Markov Chain
This work is devoted to the almost sure stabilization of adaptive control
systems that involve an unknown Markov chain. The control system displays
continuous dynamics represented by differential equations and discrete events
given by a hidden Markov chain. Different from previous work on stabilization
of adaptive controlled systems with a hidden Markov chain, where average
criteria were considered, this work focuses on the almost sure stabilization or
sample path stabilization of the underlying processes. Under simple conditions,
it is shown that as long as the feedback controls have linear growth in the
continuous component, the resulting process is regular. Moreover, by
appropriate choice of the Lyapunov functions, it is shown that the adaptive
system is stabilizable almost surely. As a by-product, it is also established
that the controlled process is positive recurrent
A nonlinear filtering approach to changepoint detection problems:direct and differentialg-geometric methods
A benchmark change detection problem is considered which involves the detection of a change of unknown size at an unknown time. Both unknown quantities are modelled by stochastic variables, which allows the problem to be formulated within a Bayesian framework. It turns out that the resulting nonlinear filtering problem is much harder than the well-known detection problem for known sizes of the change, and in particular that it can no longer be solved in a recursive manner. An approximating recursive filter is therefore proposed, which is designed using differential-geometric methods in a suitably chosen space of unnormalized probability densities. The new nonlinear filter can be interpreted as an adaptive version of the celebrated Shiryayev-Wonham equation for the detection of a priori known changes, combined with a modified Kalman filter structure to generate estimates of the unknown size of the change. This intuitively appealing interpretation of the nonlinear filter and its excellent performance in simulation studies indicate that it may be of practical use in realistic change detection problems
Always-On Quantum Error Tracking with Continuous Parity Measurements
We investigate quantum error correction using continuous parity measurements
to correct bit-flip errors with the three-qubit code. Continuous monitoring of
errors brings the benefit of a continuous stream of information, which
facilitates passive error tracking in real time. It reduces overhead from the
standard gate-based approach that periodically entangles and measures
additional ancilla qubits. However, the noisy analog signals from continuous
parity measurements mandate more complicated signal processing to interpret
syndromes accurately. We analyze the performance of several practical filtering
methods for continuous error correction and demonstrate that they are viable
alternatives to the standard ancilla-based approach. As an optimal filter, we
discuss an unnormalized (linear) Bayesian filter, with improved computational
efficiency compared to the related Wonham filter introduced by Mabuchi [New J.
Phys. 11, 105044 (2009)]. We compare this optimal continuous filter to two
practical variations of the simplest periodic boxcar-averaging-and-thresholding
filter, targeting real-time hardware implementations with low-latency
circuitry. As variations, we introduce a non-Markovian ``half-boxcar'' filter
and a Markovian filter with a second adjustable threshold; these filters
eliminate the dominant source of error in the boxcar filter, and compare
favorably to the optimal filter. For each filter, we derive analytic results
for the decay in average fidelity and verify them with numerical simulations.Comment: 34 pages, 7 figures, published versio
Always-On Quantum Error Tracking with Continuous Parity Measurements
We investigate quantum error correction using continuous parity measurements to correct bit-flip errors with the three-qubit code. Continuous monitoring of errors brings the benefit of a continuous stream of information, which facilitates passive error tracking in real time. It reduces overhead from the standard gate-based approach that periodically entangles and measures additional ancilla qubits. However, the noisy analog signals from continuous parity measurements mandate more complicated signal processing to interpret syndromes accurately. We analyze the performance of several practical filtering methods for continuous error correction and demonstrate that they are viable alternatives to the standard ancilla-based approach. As an optimal filter, we discuss an unnormalized (linear) Bayesian filter, with improved computational efficiency compared to the related Wonham filter introduced by Mabuchi [New J. Phys. 11, 105044 (2009)]. We compare this optimal continuous filter to two practical variations of the simplest periodic boxcar-averaging-and-thresholding filter, targeting real-time hardware implementations with low-latency circuitry. As variations, we introduce a non-Markovian ``half-boxcar\u27\u27 filter and a Markovian filter with a second adjustable threshold; these filters eliminate the dominant source of error in the boxcar filter, and compare favorably to the optimal filter. For each filter, we derive analytic results for the decay in average fidelity and verify them with numerical simulations
Singular perturbation, state aggregation and nonlinear filtering
Bibliography: leaf [4].Caption title. "September, 1981."Supported in part by NASA Grant no. 2384 Office of Naval Research under the JSEP Contract N00014-75-C-0648 DOE Grant no. ET-A01-2295T050Omar Hijab, Shankar Sastry
A ROS2 based communication architecture for control in collaborative and intelligent automation systems
Collaborative robots are becoming part of intelligent automation systems in
modern industry. Development and control of such systems differs from
traditional automation methods and consequently leads to new challenges.
Thankfully, Robot Operating System (ROS) provides a communication platform and
a vast variety of tools and utilities that can aid that development. However,
it is hard to use ROS in large-scale automation systems due to communication
issues in a distributed setup, hence the development of ROS2. In this paper, a
ROS2 based communication architecture is presented together with an industrial
use-case of a collaborative and intelligent automation system.Comment: 9 pages, 4 figures, 3 tables, to be published in the proceedings of
29th International Conference on Flexible Automation and Intelligent
Manufacturing (FAIM2019), June 201
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