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A new approach for imaging that is solely based on the time of flight of photons coming from the entire imaged scene, combined with a novel machine learning algorithm for image reconstruction: a spiking convolutional neural network (SCNN) named Spike-SPI (Spiking - Single Pixel Imager). The approach uses a single point detector and the corresponding time-counting electronics, which provide the arrival time of photons in the form of spikes distributed over time. This data is transformed into a temporal histogram containing the number of photons per arrival time. A SCNN that converts the 1D temporal histograms into a 3D image (2D image with depth map) by exploiting the feature extraction capabilities of convolutional neural networks (CNNs), the high dimensional compressed latent space representations of a variational encoder-decoder network structure, and the asynchronous processing capabilities of a spiking neural network (SNN). The performance of the proposed SCNN is analysed to demonstrate the state-of-the-art feature extraction capabilities of CNNs and the low latency asynchronous processing of SNNs that offer both higher throughput and higher accuracy in image reconstruction from the ToF data, when compared to standard ANNs. The results of Spike-SPI show an increase in spatial accuracy of 15% over then ANN, using the Intersection of Union (IoU) for the objects in the scene. While also delivering a 100% increase over then ANN in object reconstruction signal to noise ratio (RSNR) from ~3dB to ~6dB. These results are also consistent across a range of IRF (Instrument Response Functions) values and photo counts, highlighting the robust nature of the new network structure. Moreover, the asynchronous processing nature of the spiking neurons allow for a faster throughput and less computational overhead, benefiting from the operational sparsity in the single point sensor.

In recent years the integration of graphene on nanoscale waveguides has attracted much attention as it allows using well-established CMOS technology for constructing next-generation photonic integrated circuits. However, important challenges need to be overcome regarding the fabrication and patterning of graphene-covered waveguide devices. In addition, a more in-depth investigation of the fundamental optical properties of graphene-covered waveguides, and in particular their nonlinear optical characteristics, is required. The latter are promising for, amongst others, generating spectrally broadband light useful for a wide range of application domains including telecommunications and sensing. In this paper we present a novel approach for patterning graphene on top of waveguides, and provide new insights in the nonlinear optical properties of graphene-covered waveguides. The patterning approach that we developed is chemicals-free and based on laser ablation and plasma etching, removing the graphene top layer without damaging the underlying material. Regarding graphene's nonlinear optical properties, we focus on the nonlinear-refraction process of self-phase modulation causing spectral broadening of laser pulses in graphene-covered waveguides. We show that the underlying physics is not based on refraction induced by graphene's conventional third-order susceptibility, but instead on a much more complex phenomenon that we call saturable photoexcited carrier refraction.

Photonic components responsive to external optical stimuli are attracting increasing interest, because their properties can be manipulated by light with fast switching times, high spatial definition, and potentially remote control. These aspects can be further enhanced by novel architectures, which have been recently enabled by the availability of 3D printing and additive manufacturing technologies. However, current methods are still limited to passive optical materials, whereas photo-responsive materials would require the development of 3D printing techniques able to preserve the optical properties of photoactive compounds and to achieve high spatial resolution to precisely control the propagation of light. Also, optical losses in 3D printed materials are an issue to be addressed. Here we report on advanced additive manufacturing technologies, specifically designed to embed photo-responsive compounds in 3D optical devices. The properties of 3D printed devices can be controlled by external UV and visible light beams, with characteristic switching times in the range 1-10 s., Comment: 7 pages, 3 Figures