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arXiv:1307.0128 · Physical Review A

Adaptive discrimination scheme for quantum pulse-position-modulation signals

Nicola Dalla Pozza, Nicola Laurenti

Published Jan 31, 2014• 11 citations
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Abstract

In the communication scenario, we consider the problem of the discrimination between the signals of the quantum pulse position modulation. We propose a receiver scheme that employs repeated local measurements in distinct temporal slots within the symbol time interval, adaptively chosen on the basis of the outcomes in the previous slots. By employing dynamic programming to optimize each measurement, we approach the theoretical performance limit much closer than existing receiver schemes.

DOI
10.1103/physreva.89.012339

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In the communication scenario, we consider the problem of the discrimination between the signals of the quantum pulse position modulation. We propose a receiver scheme that employs repeated local measurements in distinct temporal slots within the symbol time interval, adaptively chosen on the basis of the outcomes in the previous slots. By employing dynamic programming to optimize each measurement, we approach the theoretical performance limit much closer than existing receiver schemes.
In optical communication, the transmitter encodes information into a set of light states defined by the modulation format, selected to accommodate specific channel conditions and to remain sufficiently distinguishable at the output. Various receiver architectures have been designed to improve the demodulation performance, ultimately limited by quantum theory. In this work, I introduce a new receiver based on a locally optimal greedy algorithm and apply it to pulse position modulation. The receiver reduces the error probabilities of previously proposed strategies in all signal strength regimes and achieves results comparable with those obtained by numerical optimization of the detection process. In contrast, however, it is conceptually simple and, therefore, can be scaled to arbitrarily high modulation orders for which numerical methods become intractable. In the photon-starved regime characteristic of deep space optical communication, the greedy receiver approaches the quantum-optimal Helstrom bound on state discrimination error probability. In the regime of few-photon pulses, the error reduction offered over the other methods grows up to an order of magnitude.
We theoretically study the quantum receivers with adaptive measurements feedback for discriminating quadrature amplitude modulation (QAM) coherent states in terms of average symbol error rate. For rectangular 16-QAM signal set, with different stages of adaptive measurements, the effects of realistic imperfection parameters including the sub-unity quantum efficiency and the dark counts of on-off detectors, as well as the transmittance of beam splitters and the mode mismatch factor between the signal and local oscillating fields on the symbol error rate are separately investigated through Monte Carlo simulations. Using photon-number-resolving detectors (PNRD) instead of on-off detectors, all the effects on the symbol error rate due to the above four imperfections can be suppressed in a certain degree. The finite resolution and PNR capability of PNRDs are also considered. We find that for currently available technology, the receiver shows a reasonable gain from the standard quantum limit (SQL) with moderate stages.
High-dimensional quantum key distribution (QKD) systems that exploit temporal correlation among entangled photons are of growing practical interest. In such systems, the observation time is typically partitioned into frames of fixed duration, with pulse-position modulation (PPM) coding used within each frame, via which a secret key is established between the parties. Such schemes can be very inefficient in their use of photons, since only a fraction of the frames can be used. As an alternative, we describe an efficient class of schemes with adaptive frame size whose performance can converge to the fundamental limit much more quickly. We analyze and compare the performances of both fixed and adaptive PPM schemes, taking into account photon transmission and detection losses. Further numerical results reveal the significant performance gain of adaptive PPM relative to fixed PPM.
Discrimination between quantum states is a fundamental task in quantum information theory. Given two arbitrary tensor-product quantum states (TPQS) ρ±=ρ±(1)⊗⋯⊗ρ±(N)ρ_{\pm} = ρ_{\pm}^{(1)} \otimes \cdots \otimes ρ_{\pm}^{(N)}ρ±​=ρ±(1)​⊗⋯⊗ρ±(N)​, determining the joint NNN-system measurement to optimally distinguish between the two states is a hard problem. Thus, there is great interest in identifying local measurement schemes that are optimal or close-to-optimal. In this work, we focus on distinguishing between two general TPQS. We begin by generalizing previous work by Acin et al. (Phys. Rev. A 71, 032338) to show that a locally greedy (LG) scheme using Bayesian updating can optimally distinguish between two states that can be written as tensor products of arbitrary pure states. Then, we show that even in the limit of large NNN the same algorithm cannot distinguish tensor products of mixed states with vanishing error probability. This poor asymptotic behavior occurs because the Helstrom measurement becomes trivial for sufficiently biased priors. Based on this, we introduce a modified locally greedy (MLG) scheme with strictly better performance. In the second part of this work, we compare these simple local schemes with a general dynamic programming (DP) approach that finds the optimal series of local measurements to distinguish the two states. When the subsystems are non-identical, we demonstrate that the ordering of the systems affects performance and we extend the DP technique to determine the optimal ordering adaptively. Finally, in contrast to the binary optimal collective measurement, we show that adaptive protocols on sufficiently large (e.g., qutrit) subsystems must contain non-binary measurements to be optimal. (The code that produced the simulation results in this paper can be found at: https://github.com/SarahBrandsen/AdaptiveStateDiscrimination)