Interlaboratory study on Sb2S3 interplay between structure, dielectric function, and morphous-to-crystalline phase change for photonics

Antimony sulfide, Sb2S3, is interesting as the phase-change material for applications requiring high transmission from the visible to telecom wavelengths, with its band gap tunable from 2.2 to 1.6 eV, depending on the amorphous and crystalline phase. Here we present results from an interlaboratory study on the interplay between the structural change and resulting optical contrast during the amorphous-to-crystalline transformation triggered both thermally and optically. By statistical analysis of Raman and ellipsometric spectroscopic data, we have identified two regimes of crystallization, namely 250_C % T < 300_C, resulting in Type-I spherulitic crystallization yielding an optical contrast Dn _ 0.4, and 300 % T < 350 _ C, yielding Type-II crystallization bended spherulitic structure with different dielectric function and optical contrast Dn _ 0.2 below 1.5 eV. Based on our findings, applications of on-chip reconfigurable nanophotonic phase modulators and of a reconfigurable high-refractive-index core/phase-change shell nanoantenna are designed and proposed.The authors acknowledge the support from the European Union’s Horizon 2020 research and innovation program (No 899598 - PHEMTRONICS)

Integrated programmable spectral filter for frequency-multiplexed neuromorphic computers

Artificial neural networks (ANN) are a groundbreaking technology massively employed in a plethora of fields. Currently, ANNs are mostly implemented through electronic digital computers, but analog photonic implementations are very interesting mainly because of low power consumption and high bandwidth. We recently demonstrated a photonic neuromorphic computing system based on frequency multiplexing that executes ANNs algorithms as reservoir computing and Extreme Learning Machines. Neuron signals are encoded in the amplitude of the lines of a frequency comb, and neuron interconnections are realized through frequency-domain interference. Here we present an integrated programmable spectral filter designed to manipulate the optical frequency comb in our frequency multiplexing neuromorphic computing platform. The programmable filter controls the attenuation of 16 independent wavelength channels with a 20 GHz spacing. We discuss the design and the results of the chip characterization, and we preliminary demonstrate, through a numerical simulation, that the produced chip is suitable for the envisioned neuromorphic computing application.info:eu-repo/semantics/publishe

Numerical Analysis of a Self-Calibrating Time-Spatial Interleaving Photonic Convolutional Accelerator

Convolutional Neural Networks (CNNs) are fundamental machine learning tools to process image, speech, or audio signal inputs. The convolutional layer is the core building block of a CNN, and it is where most of the computation occurs. Here, we propose an integrated photonic convolutional accelerator based on time-spatial interleaving utilizing standard generic building blocks to reduce hardware complexity. The architecture is suitable for addressing both 2D and 1D convolutional kernels enabling scalability to more complex networks. Furthermore, a numerical simulation demonstrates the viability of a supervised online learning algorithm for loading the kernel weights both in amplitude and in phase taking in consideration fabrication tolerances and thermal cross-talk.info:eu-repo/semantics/publishe

Large scale programmable photonic circuits using silicon photonic MEMS

We demonstrate low-power and non-volatile MEMS actuators on an industrially established silicon photonics platform. The compact electrostatically actuated phase shifters and tunable couplers enable large-scale programmable photonic integrated circuits

Programmable Photonic Circuits powered by Silicon Photonic MEMS Technology

Programmable photonic chips allow flexible reconfiguration of on-chip optical connections, controlled through electronics and software. We will present the recent progress of such complex photonic circuits powered by silicon photonic MEMS actuators.</jats:p

Programmable silicon photonic circuits powered by MEMS

We present our work to extend silicon photonics with MEMS actuators to enable low-power, large scale programmable photonic circuits. For this, we start from the existing iSiPP50G silicon photonics platform of IMEC, where we add free-standing movable waveguides using a few post-processing steps. This allows us to implement phase shifters and tunable couplers using electrostatically actuated MEMS, while at the same time maintaining all the original functionality of the silicon photonics platform. The MEMS devices are protected using a wafer-level sealing approach and interfaced with custom multi-channel driver and readout electronics

MORPHIC : MEMS enhanced silicon photonics for programmable photonics

We present our work in the European project MORPHIC to extend an established silicon photonics platform with low-power and non-volatile micro-electromechanical (MEMS) actuators to demonstrate large-scale programmable photonic integrated circuits (PICs)