Neuromorphic photonics with electro-absorption modulators.

Photonic neural networks benefit from both the high-channel capacity and the wave nature of light acting as an effective weighting mechanism through linear optics. Incorporating a nonlinear activation function by using active integrated photonic components allows neural networks with multiple layers to be built monolithically, eliminating the need for energy and latency costs due to external conversion. Interferometer-based modulators, while popular in communications, have been shown to require more area than absorption-based modulators, resulting in a reduced neural network density. Here, we develop a model for absorption modulators in an electro-optic fully connected neural network, including noise, and compare the network's performance with the activation functions produced intrinsically by five types of absorption modulators. Our results show the quantum well absorption modulator-based electro-optic neuron has the best performance allowing for 96% prediction accuracy with 1.7×10-12 J/MAC excluding laser power when performing MNIST classification in a 2 hidden layer feed-forward photonic neural network.

Waveguide-based electro-absorption modulator performance: comparative analysis.

Electro-optic modulators perform a key function for data processing and communication. Rapid growth in data volume and increasing bits per second rates demand increased transmitter and thus modulator performance. Recent years have seen the introduction of new materials and modulator designs to include polaritonic optical modes aimed at achieving advanced performance in terms of speed, energy efficiency, and footprint. Such ad hoc modulator designs, however, leave a universal design for these novel material classes of devices missing. Here we execute a holistic performance analysis for waveguide-based electro-absorption modulators and use the performance metric switching energy per unit bandwidth (speed). We show that the performance is fundamentally determined by the ratio of the differential absorption cross-section of the switching material's broadening and the waveguide effective mode area. We find that the former shows highest performance for a broad class of materials relying on Pauli-blocking (absorption saturation), such as semiconductor quantum wells, quantum dots, graphene, and other 2D materials, but is quite similar amongst these classes. In this respect these materials are clearly superior to those relying on free carrier absorption, such as Si and ITO. The performance improvement on the material side is fundamentally limited by the oscillator sum rule and thermal broadening of the Fermi-Dirac distribution. We also find that performance scales with modal waveguide confinement. Thus, we find highest energy-bandwidth-ratio modulator designs to be graphene, QD, QW, or 2D material-based plasmonic slot waveguides where the electric field is in-plane with the switching material dimension. We show that this improvement always comes at the expense of increased insertion loss. Incorporating fundamental device physics, design trade-offs, and resulting performance, this analysis aims to guide future experimental modulator explorations.

Attojoule-efficient graphene optical modulators.

Electro-optic modulation is a technology-relevant function for signal keying, beam steering, or neuromorphic computing through providing the nonlinear activation function of a perceptron. With silicon-based modulators being bulky and inefficient, here we discuss graphene-based devices heterogeneously integrated. This study provides a critical and encompassing discussion of the physics and performance of graphene. We provide a holistic analysis of the underlying physics of modulators including graphene's index tunability, the underlying optical mode, and discuss resulting performance vectors for this novel class of hybrid modulators. Our results show that reducing the modal area and reducing the effective broadening of the active material are key to improving device performance defined by the ratio of energy-bandwidth and footprint. We further show how the waveguide's polarization must be in-plane with graphene, such as given by plasmonic-slot structures, for performance improvements. A high device performance can be obtained by introducing multi- or bi-layer graphene modulator designs. Lastly, we present recent results of a graphene-based hybrid-photon-plasmon modulator on a silicon platform and discuss electron beam lithography treatments for transferred graphene for the relevant Fermi level tuning. Being physically compact, this 100 aJ/bit modulator opens the path towards a novel class of attojoule efficient opto-electronics.

Heterogeneously integrated ITO plasmonic Mach-Zehnder interferometric modulator on SOI.

Densely integrated active photonics is key for next generation on-chip networks for addressing both footprint and energy budget concerns. However, the weak light-matter interaction in traditional active Silicon optoelectronics mandates rather sizable device lengths. The ideal active material choice should avail high index modulation while being easily integrated into Silicon photonics platforms. Indium tin oxide (ITO) offers such functionalities and has shown promising modulation capacity recently. Interestingly, the nanometer-thin unity-strong index modulation of ITO synergistically combines the high group-index in hybrid plasmonic with nanoscale optical modes. Following this design paradigm, here, we demonstrate a spectrally broadband, GHz-fast Mach-Zehnder interferometric modulator, exhibiting a high efficiency signified by a miniscule VπL of 95 V µm, deploying a one-micrometer compact electrostatically tunable plasmonic phase-shifter, based on heterogeneously integrated ITO thin films into silicon photonics. Furthermore we show, that this device paradigm enables spectrally broadband operation across the entire telecommunication near infrared C-band. Such sub-wavelength short efficient and fast modulators monolithically integrated into Silicon platform open up new possibilities for high-density photonic circuitry, which is critical for high interconnect density of photonic neural networks or applications in GHz-fast optical phased-arrays, for example.

Towards integrated metatronics: a holistic approach on precise optical and electrical properties of Indium Tin Oxide.

The class of transparent conductive oxides includes the material indium tin oxide (ITO) and has become a widely used material of modern every-day life such as in touch screens of smart phones and watches, but also used as an optically transparent low electrically-resistive contract in the photovoltaics industry. More recently ITO has shown epsilon-near-zero (ENZ) behavior in the telecommunication frequency band enabling both strong index modulation and other optically-exotic applications such as metatronics. However, the ability to precisely obtain targeted electrical and optical material properties in ITO is still challenging due to complex intrinsic effects in ITO and as such no integrated metatronic platform has been demonstrated to-date. Here we deliver an extensive and accurate description process parameter of RF-sputtering, showing a holistic control of the quality of ITO thin films in the visible and particularly near-infrared spectral region. We are able to custom-engineer the ENZ point across the telecommunication band by explicitly controlling the sputtering process conditions. Exploiting this control, we design a functional sub-wavelength-scale filter based on lumped circuit-elements, towards the realization of integrated metatronic devices and circuits.