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Imaging and Applied Optics

Exploiting Fisher Information for Constructing an Efficient Nonlinear Optimization Scheme for Quantum Imaging

Anton Sakovich, Alexander B. Mikhalychev, Ilya Karuseichyk, Dmitri S. Mogilevtsev

Published Jan 1, 2019• 0 citations
Publisher

Abstract

Making use of Fisher information, we show that a broad class of object re construction problems can be accurately and efficiently solved by reconstructing the object iteratively, reconstructing only a subset of parameters at each step.
DOI
10.1364/math.2019.mw3d.4

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Quantum imaging generally leads to nonlinear estimation problems intractable for a larger number of problem parameters. We connect the features of the Fisher information with the parametric locality of the problem and build the efficient iterative scheme reconstructing only a subset of the whole set of parameters in each step. We demonstrate super-resolving reconstruction of grey transmission objects with the experimental data obtained by imaging with entangled twin-photons and pseudo-thermal sources. We predict and experimentally confirm the existence of optimal photon correlations providing for the best image resolution. We also show how an estimation bias may drastically improve the resolution.
Abstract Quantum imaging has a potential of enhancing the precision of objects reconstruction by exploiting quantum correlations of the imaging field, in particular for imaging with low-intensity fields up to the level of a few photons. However, it generally leads to nonlinear estimation problems. The complexity of these problems rapidly increases with the number of parameters describing the object and the correlation order. Here we propose a way to drastically reduce the complexity for a wide class of problems. The key point of our approach is to connect the features of the Fisher information with the parametric locality of the problem, and to reconstruct the whole set of parameters stepwise by an efficient iterative inference scheme that is linear on the total number of parameters. This general inference procedure is experimentally applied to quantum near-field imaging with higher-order correlated light sources, resulting in super-resolving reconstruction of grey compound transmission objects.
Advanced superresolution imaging techniques require specific approaches for accurate and consistent estimation of the achievable spatial resolution. Fisher information supplied to the Cram\'er-Rao bound (CRB) has proved to be a powerful and efficient tool for resolution analysis and optical setups optimization. However, the standard CRB is not applicable to constrained problems violating the unbiasedness condition, while such models are frequently encountered in quantum imaging of complex objects. Complementary to the existing approaches based on modifying CRB, we propose a practical algorithm for approximate construction of a modified Fisher information matrix, which takes the constraints into account and enables accurate estimation of errors for constrained problems by the standard CRB. We demonstrate the efficiency of the proposed technique by applying it to one-, two-, and multiparameter model problems in quantum imaging. The approach provides quantitative explanation of previous results with successful experimental reconstruction of objects with the spatial scale smaller than the theoretical limit predicted by the standard CRB.
Fisher information is a statistical metric whose inverse represents a lower bound on the variance of an unbiased estimator. Naturally, in order to make the best estimates of a given unknown parameter, one would desire to find ways to minimize the value of this lower bound. Thus, the Fisher information can also be used to compare the quality of different estimators for a given parameter: whichever estimator has a lower value for its Fisher information must also provide better estimates. The same holds true in the framework of quantum information theory, where an analog to the Fisher information, dubbed quantum Fisher information, performs the same role as its classical counterpart. This dissertation concerns itself with both types of Fisher information, and so I present two projects in which Fisher information was a helpful tool for determining the quality of our work. In the first project, we examined potential solutions to the problem of optical loss in long-baseline interferometers, which creates a bottleneck in the resolution these arrays of telescopes can achieve. What we suggested was a novel entanglement-assisted scheme that interferes a two-mode squeezed vacuum state with the target astronomical state, and then measures the resulting state by means of homodyne detection. Ultimately, we showed that when the Fisher information is observed, our proposed scheme did not outperform the traditional schemes used in long-baseline interferometry. In the second project, we sought to write code that could determine how to best use dynamical decoupling pulses to correct dephasing error in a nitrogen-vacancy center realization of a memory and spectator qubit system. Through the use of the Python coding language, we were able to write programs that could determine the characteristic time and model the change in fidelity of the system when XY4 pulses are applied. Ultimately, we found that the quantum fidelity of our model closely mirrored the fidelity decay function our system was expected to follow in the case where XY4 pulses are applied.
We compare the performance of quantum imaging schemes based on spatially correlated photon pairs by formulating them as quantum multiparameter estimation problems, in which the object is characterized by transmission coefficients associated with different spatial modes. Our work focuses on standard quantum imaging techniques such as ghost imaging, two-photon imaging, and imaging with undetected photons. Specifically, we compute the quantum Fisher information matrices and show that they are saturated by Fisher information matrices corresponding to measurements in the object-mode basis, which generalize the common detection schemes employed in each imaging configuration. We find that ghost imaging and two-photon imaging generally provide higher precision for transmission estimation than imaging with undetected photons, but the latter is the only one that naturally does not couple transmission estimation across different spatial modes. These results identify which imaging protocols are best suited for specific tasks and provide practical guidelines for the design and optimization of quantum sensing technologies based on spatial correlations.