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Conference on Lasers and Electro-Optics

Adaptive optical phase estimation

D. Nakane, Trevor A. Wheatley, Dominic William Berry, Hidehiro Yonezawa, Hajime Arao, Damian T. Pope, Timothy C. Ralph, Howard M. Wiseman, Elanor H. Huntington, Akira Furusawa

Published Jan 1, 2010• 2 citations
Publisher

Abstract

We experimentally performed adaptive phase estimation using time-symmetric quantum smoothing for a stochastically varying phase on continuous wave coherent beam. We demonstrate better accuracy than conventional methods.
DOI
10.1364/cleo.2010.jthf4

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Quantum parameter estimation has many applications, from gravitational wave detection to quantum key distribution. The most commonly used technique for this type of estimation is quantum filtering, using only past observations. We present the first experimental demonstration of quantum smoothing, a time-symmetric technique that uses past and future observations, for quantum parameter estimation. We consider both adaptive and nonadaptive quantum smoothing, and show that both are better than their filtered counterparts. For the problem of estimating a stochastically varying phase shift on a coherent beam, our theory predicts that adaptive quantum smoothing (the best scheme) gives an estimate with a mean-square error up to 2sqrt[2] times smaller than nonadaptive filtering (the standard quantum limit). The experimentally measured improvement is 2.24+/-0.14.
Quantum phase estimation is one of the most important tools in quantum algorithms. It can be made non-adaptive (meaning all applications of the unitary UφU_φUφ​ happen simultaneously) without using more applications of UφU_φUφ​, albeit at the expense of using many more qubits. It is also known that there is no advantage for adaptive algorithms in the case where the phase that needs to be estimated is arbitrary or is uniformly random. Here we give examples of a special case of phase estimation, with a promise on the values that the unknown phase can take, where adaptive methods are provably better than non-adaptive methods by a factor of nearly 2 in the number of uses of UφU_φUφ​. We also prove some upper bounds on the maximum advantage that adaptive algorithms for phase estimation can achieve over non-adaptive ones.
We present an experimental demonstration of quantum smoothing, a non causal version of quantum parameter estimation that has applications from gravitational wave detection to quantum key distribution. An existing technique for this type of parameter estimation is quantum filtering, which uses past observations only. The technique presented here is time-symmetric that uses past and future observations to obtain a more precise estimate. We couple this innovative estimation technique with an adaptive detection scheme to demonstrate an estimation of the optical phase of light measured to be 2.24 ± 0.14 times better than the standard quantum limit. This approaches our theoretically derived prediction of a mean square error improvement of 2√2 times over the standard quantum limit [1].
Adaptive homodyne estimation of a continuously evolving optical phase using time-symmetric quantum smoothing has been demonstrated experimentally to provide superior accuracy in the phase estimate compared to adaptive or non-adaptive estimation using filtering alone. Here, we illustrate how the mean-square error in the adaptive phase estimate may be further reduced below the standard quantum limit for the stochastic noise process considered by using a Rauch-Tung-Striebel smoother as the estimator, along with an optimal Kalman filter in the feedback loop. Further, the estimation using smoothing can be made robust to uncertainties in the underlying parameters of the noise process modulating the system phase to be estimated. This has been done using a robust fixed-interval smoother designed for uncertain systems satisfying a certain integral quadratic constraint.