High-dimensional (dimension d > 2) quantum key distribution (QKD) protocols that encode information in the temporal degree of freedom promise to overcome some of the challenges of qubit-based (d = 2) QKD systems. In particular, the long recovery time of single-photon detectors and large channel noise at long distance both limit the rate at which a final secure key can be generated in a low-dimension QKD system. We propose and demonstrate a practical discrete-variable time-frequency protocol with d = 4 at a wavelength of 1550 nm, where the temporal states are secured by transmitting and detecting their dual states under Fourier transformation, known as the frequency-basis states, augmented by a decoy-state protocol. We show that the discrete temporal and frequency states can be generated and detected using commercially-available equipment with high timing and spectral efficiency. In our initial experiments, we only have access to detectors that have low efficiency (1%) at 1550 nm. Together with other component losses, our system is equivalent to a QKD system with ideal components and a 50-km-long optical-fiber quantum channel. We find that our system maintains a spectral visibility of over 99.0% with a quantum bit error rate of 2.3%, which is largely due to the finite extinction ratio of the intensity modulators used in the transmitter. The estimated secure key rate of this system is 7.7×104 KHz, which should improve drastically when we use detectors optimized for 1550 nm.
Semiconductor lasers under external perturbations can manifest a broad variety of complex dynamics in their output power, from periodicity to high dimensional chaos. One of their characteristic behaviors, when submitted to optical feedback, is their excitability. These optical excitable devices, that mimic neuronal behavior, can serve as building-blocks for novel, brain-inspired information processing systems. Neuronal systems represent and process the information of a weak external input through correlated electrical spikes. Semiconductor lasers with low to moderate optical feedback, i.e. in the low frequency fluctuations (LFF) regime, display optical spikes with intrinsic temporal correlations, similar to those of biological neurons. Here we study the laser optical spiking dynamics under the influence of direct pump current modulation, focusing on the influence of the modulation frequency and amplitude. We characterize time correlations in the sequence of optical spikes by using symbolic ordinal analysis. This powerful tool allows detecting symbolic patterns in the laser output, and to quantify the effect of the frequency and amplitude of the modulation on the patterns probabilities. The experimental results are in good qualitative agreement with simulations of the Lang and Kobayashi model.
Fibre lasers have been shown to manifest a laminar-to-turbulent transition when increasing its pump power. In order to study the dynamical complexity of this transition we use advanced statistical tools of time-series analysis. We apply ordinal analysis and the horizontal visibility graph to the experimentally measured laser output intensity. This reveal the presence of temporal correlations during the transition from the laminar to the turbulent lasing regimes. Both methods allow us to unveil coherent structures with well defined time-scales and strong correlations both, in the timing of the laser pulses and in their peak intensities.
We investigate the symbolic dynamics of an excitable optical system under periodic forcing. Particularly, we consider the low-frequency fluctuation (LFF) dynamics of a semiconductor laser with periodically-modulated injection current and optical feedback. We use a method of symbolic time-series analysis that allows us to unveil serial correlations in the sequence of intensity dropouts. By transforming the sequence of inter-dropout intervals into a sequence of ordinal patterns and analyzing the statistics of the patterns, we uncover correlations among several consecutive dropouts and we identify definite changes in the dynamics as the modulation amplitude increases. We confirm the robustness of the observations by conducting the experiments with two different lasers under different feedback conditions. The results are also shown to be robust to variations of the threshold used for detecting the dropouts. Simulations of the Lang-Kobayashi (LK) model, including spontaneous emission noise, are found to be in good qualitative agreement with the observations, providing an interpretation of the correlations present in the dropout sequence as due to the interplay of the underlying attractor topology, the periodic forcing, and the noise that sustains the dropout events.
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