5,045 research outputs found
Coherent-Classical Estimation versus Purely-Classical Estimation for Linear Quantum Systems
We consider a coherent-classical estimation scheme for a class of linear
quantum systems. It comprises an estimator that is a mixed quantum-classical
system without involving coherent feedback. The estimator yields a classical
estimate of a variable for the quantum plant. We demonstrate that for a passive
plant that can be characterized by annihilation operators only, such
coherent-classical estimation provides no improvement over purely-classical
estimation. An example is also given which shows that if the plant is not
assumed to be an annihilation operator only quantum system, it is possible to
get better estimates with such coherent-classical estimation compared with
purely-classical estimation.Comment: 7 pages, 5 figures. Minor corrections. Accepted, 2014 Conference on
Decision and Contro
Robust Filtering for Adaptive Homodyne Estimation of Continuously Varying Optical Phase
Recently, it has been demonstrated experimentally that adaptive estimation of
a continuously varying optical phase provides superior accuracy in the phase
estimate compared to static estimation. Here, we show that the mean-square
error in the adaptive phase estimate may be further reduced for the stochastic
noise process considered by using an optimal Kalman filter in the feedback
loop. Further, the estimation process can be made robust to fluctuations in the
underlying parameters of the noise process modulating the system phase to be
estimated. This has been done using a guaranteed cost robust filter.Comment: 5 pages, 6 figures, Proceedings of the 2012 Australian Control
Conferenc
Robust Estimation of Optical Phase Varying as a Continuous Resonant Process
It is well-known that adaptive homodyne estimation of continuously varying
optical phase provides superior accuracy in the phase estimate as compared to
adaptive or non-adaptive static estimation. However, most phase estimation
schemes rely on precise knowledge of the underlying parameters of the system
under measurement, and performance deteriorates significantly with changes in
these parameters; hence it is desired to develop robust estimation techniques
immune to such uncertainties. In related works, we have already shown how
adaptive homodyne estimation can be made robust to uncertainty in an underlying
parameter of the phase varying as a simplistic Ornstein-Uhlenbeck stochastic
noise process. Here, we demonstrate robust phase estimation for a more
complicated resonant noise process using a guaranteed cost robust filter.Comment: 5 pages, 10 figures, Proceedings of the 2013 Multi-Conference on
Systems and Contro
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