Photonic spiking neural network based on excitable VCSELs-SA for sound azimuth detection.

We propose a photonic spiking neural network (SNN) based on excitable vertical-cavity surface-emitting lasers with an embedded saturable absorber (VCSELs-SA) for emulating the sound azimuth detection function of the brain for the first time. Here, the spike encoding and response properties based on the excitability of VCSELs-SA are employed, and the difference between spike timings of two postsynaptic neurons serves as an indication of sound azimuth. Furthermore, the weight matrix contributing to the successful sound azimuth detection is carefully identified, and the effect of the time interval between two presynaptic spikes is considered. It is found that the weight range that can achieve sound azimuth detection decreases gradually with the increase of the time interval between the sound arriving at the left and right ears. Besides, the effective detection range of the time interval between two presynaptic spikes is also identified, which is similar to that of the biological auditory system, but with a much higher resolution which is at the nanosecond time scale. We further discuss the effect of device variations on the photonic sound azimuth detection. Hence, this photonic SNN is biologically plausible, which has comparable low energy consumption and higher resolution compared with the biological system. This work is valuable for brain-inspired information processing and a promising foundation for more complex spiking information processing implemented by photonic neuromorphic computing systems.

Four-channels reservoir computing based on polarization dynamics in mutually coupled VCSELs system.

A novel Four-channels reservoir computing (RC) based on polarization dynamics in mutually coupled vertical cavity surface emitting lasers (MDC-VCSELs) is proposed and demonstrated numerically. Here, the four channels are realized in two orthogonal polarization modes (x-polarization and y-polarization modes) of two VCSELs for the first time. A chaotic time series prediction task is employed to quantitatively evaluated the prediction performance of the proposed system. It is found that the Four-channels RC based on MDC-VCSELs can produce comparable prediction performance with One-channel RC, and it is possible to increase four times information processing rate by using the Four-channels RC. Besides, the effects of injection current, external injection strength, frequency detuning, coupling strength, as well as internal parameters on the prediction performance of the Four-channels RC based on MDC-VCSELs are carefully examined. Moreover, the influences of sampled period of input signal and the number of virtual nodes are also considered. The proposed Four-channels RC based on MDC-VCSELs is valuable for further enhancing the information processing rate of RC-based neuromorphic photonic systems.

Anti-chromatic dispersion transmission of frequency and bandwidth-doubling dual-chirp microwave waveform.

A photonic approach to realizing anti-chromatic dispersion transmission for a frequency and bandwidth-doubling dual-chirp microwave waveform is proposed and experimentally demonstrated. The system has no requirement on polarization devices or optical filters for only the integrated dual-drive dual-parallel Mach-Zehnder modulator employed. To overcome chromatic dispersion, the carrier frequency suppression approach is proposed. The anti-chromatic dispersion process is accomplished in a central station and independent to carrier frequency, fiber length, and dispersion coefficients. An experiment is conducted to verify the analysis. Dual-chirp waveforms at 13 GHz with a bandwidth of 0.8 GHz and time duration of 1 µs are obtained. After 25 km fiber transmission, the proposed approach shows a relatively flat curve in a frequency-power diagram, while the normally carrier-suppressed double-sideband modulation method experiences a significant power fading for fiber dispersion.