Maria Teresa Delgado

Novel Techniques for Information Reconciliation, Quantum Channel Probing and Link Design for Quantum Key Distribution

In this manuscript, a novel technique for forward error correction based information reconciliation is proposed, exploiting capacity achieving soft-metric based iteratively decoded block codes. The availability of soft metric and information bits reliability is also employed to efficiently perform channel probing and privacy amplification.

Toward a “soft” output quantum channel via Bayesian estimation

We propose a feasible scheme to realize a soft output quantum channel useful for soft-metric-based information reconciliation protocols for quantum key distribution. Our proposal relies on optical qubits encoded into the polarization degree of freedom of coherent states and Bayesian estimation in non-asymptotic regime at the detection stage. We also consider the presence of non-dissipative noise during the propagation.

Soft-metric-based information reconciliation techniques for QKD

This paper deals with soft-information based information reconciliation and data sifting for Quantum Key Distribution (QKD).We propose a novel composite channel model for QKD, which includes both a hard output quantum channel and a soft output classic channel. The metrics derived from the two channels are jointly processed at the receiver, exploiting capacity achieving soft-metric based iteratively decoded block codes. The performance of the proposed mixed-softmetric algorithms are studied via simulations as a function of the system parameters. The core ideas of the paper are: a) employing FEC coding as opposed to two-way communication for information reconciliation, b) exploiting all the available information for data processing at the receiver including information available from the quantum channel, since optimized use of this information can lead to significant performance improvement.

Soft-Metric-Based Channel Decoding for Photon Counting Receivers

We address photon-number-assisted, polarization-based, binary communication systems equipped with photon counting receivers. In these channels, information is encoded in the value of polarization phase-shift but the carrier has an additional degree of freedom, i.e., its photon distribution, which may be exploited to implement binary-input multiple-output (BIMO) channels also in the presence of a phase diffusion noise affecting the polarization. Here, we analyze the performances of these channels, which approach capacity by means of iteratively decoded error correcting codes. In this paper, we use soft-metric-based low-density parity-check codes for this purpose. In order to take full advantage of all the information available at the output of a photon counting receiver, soft information is generated in the form of log-likelihood ratios, leading to improved frame error rate and bit error rate compared to binary symmetric channels. We evaluate the classical capacity of the considered BIMO channel and show the potential gains that may be provided by photon counting detectors in realistic implementations.

Capacity approaching codes for photon counting receivers

[1] a low-complexity photon-counting receiver has been presented, which may be employed for weak-energy optical communications and which is typically modeled through its equivalent Binary Symmetric Channel (BSC) model. In this paper we consider the scheme described in [1], we model it as a time varying Binary Input-Multiple Output (BIMO) channel and analyze its performance in presence of soft-metric based capacity approaching iteratively decoded error correcting codes, and in particular using soft-metric based Low Density Parity Check (LDPC) codes. To take full advantage of such detector, soft information is generated in the form of Log-Likelihood Ratios (LLRs), achieving reduction in Bit Error Rate (BER) and Frame Error Rate (FER) with respect to classical BSC and Additive White Gaussian Noise (AWGN) channel models. Furthermore, we explore the limits of the achievable performance gains when using photon counting detectors as compared to the case when such detectors are not available. To this end, we find the classical capacity of the considered BIMO channel, clearly showing the potential gains that photon counting detectors can provide in the context of a realistic cost-effective scheme from an implementation point of view. Furthermore, we show that from a channel modeling point of view, we can observe that the BIMO channel can be approximated with an AWGN channel for high values of mean photon count Nc, while the AWGN model offers an unreliable result with a low mean photon number Nc, (i.e. with low raw BER). This effect is more evident with lower coding rates.

Improved Key Rates for Quantum Key Distribution Employing Soft Metrics Using Bayesian Inference with Photon Counting Detectors

This paper investigates the potential improvements that may be obtained in terms of the secret key transmission rate in a Quantum Key Distribution (QKD) scheme whereby photon-counting detectors are used at the receiver. To take full advantage of such detectors, soft information is generated in the form of Log-Likelihood Ratios (LLRs) using a Bayesian estimator of phase of the signal pulse which is used to carry the information. The technique is general in a sense that any optical communication scheme whereby the received mean photon count is relatively small, but not necessarily below one and uses the polarization state of light to transmit the binary data may benefit from the soft information processing proposed, although in this paper, we have focused on the QKD application. We demonstrate using simulations the significant reduction in the residual Bit Error Rate (BER) and Frame Error Rate (FER) that is achievable using the proposed soft information processing scheme for a given Quantum BER (QBER) on the quantum link, after the information reconciliation process using LDPC Forward Error Correction (FEC) coding.

Soft-metric based decoding for photon counting receivers

In [1] a low-complexity photon-counting receiver has been presented, which may be employed in long-distance amplification-free classical optical communication schemes, and which is typically modeled through its equivalent Binary Symmetric Channel (BSC) model. In this paper, we consider the scheme described in [1], but we model it as a time varying Binary Input-Multiple Output (BIMO) channel, and analyze its performance in presence of soft-metric based capacity approaching error correcting codes. We show that the classical channel capacity of the suggested BIMO model is higher than the capacity of the BSC model, and that the use of the BIMO model allows to feed the channel decoder with soft information, in the form of Log-Likelihood Ratios (LLRs), achieving a significant reduction in Bit Error Rate (BER) and Frame Error Rate (FER) with respect to classical hard-metric-based schemes which should be used in conjunction with a BSC channel model.

On the generation of entanglement from the interference of Gaussian states of light

We address the interaction of two Gaussian states of light interfering at a balanced beam splitter and analyze the correlations exhibited by the resulting bipartite system. Nonlocal quantum correlations (entanglement) arise if and only if the fidelity between the two input Gaussian states falls under a threshold value depending only on their purities. In particular, our result clarifies the role of squeezing as a prerequisite for entanglement and provide a tool to optimize the generation of entanglement by passive devices.

Classical capacity of a Bayesian inference quantum channel employing photon counting detectors

Recently we investigated the potential improvements in key transmission rate in a Quantum Key Distribution (QKD) scheme whereby photon-counting detectors are used at the receiver. To take full advantage of such detectors, soft information is generated in the form of Log-Likelihood Ratios (LLRs) using a Bayesian estimator of phase of the signal pulse which is used to carry the information. We achieved significant reduction in the residual Bit Error Rate (BER) and Frame Error Rate (FER) using LDPC codes in the information reconciliation process. In this paper we explore the limits of the achievable performance gains when using photon counting detectors as compared to the case when such detectors are not available. To this end, we find the classical capacity of the Bayesian inference channel clearly showing the potential gains that photon counting detectors can provide in the context of a realistic cost-effective scheme from an implementation point of view. While there are binary communication schemes that can achieve a higher capacity for a given mean photon count at the receiver compared to the scheme presented here (e.g., the Dolinar receiver), most such schemes are complex and at times unrealistic from an implementation point of view.