arXiv subjects

Mario Miscuglio

Publications and source records attributed to Mario Miscuglio.

32 records · Page 2Linked to original sources

arXiv2019

OE-CAM: A Hybrid Opto-Electronic Content Addressable Memory

A content addressable memory (CAM) is a type of memory that implements a parallel search engine at its core. A CAM takes as an input a value and outputs the address where this value is stored in case of a match. CAMs are used in a wide range of applications including networking, cashing, neuromorphic associative memories, multimedia, and data analytics. Here, we introduce a novel opto-electronic CAM (OE-CAM) utilizing the integrated silicon photonic platform. In our approach, we explore the performance of an experimental OE-CAM and verify the efficiency of the device at 25Gbit/s while maintaining the bit integrity under noise conditions. We show that OE-CAM enables a) two orders of magnitude faster search functionality resulting in b) a five orders of magnitude lower power-delay-product compared to CAMs implementations based on other emerging technologies. This remarkable performance potential is achieved by utilizing i) a high parallelism of wavelength-division-multiplexing in the optical domain, combined with ii) 10s of GHz-fast opto-electronic components, packaged in iii) integrated photonics for 10-100s ps-short communication delays. We further verify the upper optical input power limit of this OE-CAM to be given by parasitic nonlinearities inside the silicon waveguides, and the minimal detectable optical power at the back-end photoreceivers responsivity given channel noise. Such energy-efficient and short-delay OE-CAMs could become a key component of functional photonic-augmented ASICS, co-processors, or smart sensors.

physics.app-ph↗

arXiv2019

Artificial Synapse with Mnemonic Functionality using GSST-based Photonic Integrated Memory

Machine-learning tasks performed by neural networks demonstrated useful capabilities for producing reliable, and repeatable intelligent decisions. Integrated photonics, leveraging both component miniaturization and the wave-nature of the signals, can potentially outperform electronics architectures when performing inference tasks. However, the missing photon-photon force challenges non-volatile photonic device-functionality required for efficient neural networks. Here we present a novel concept and optimization of multi-level discrete-state non-volatile photonic memory based on an ultra-compact (<4um) hybrid phase change material GSST-silicon Mach Zehnder modulator, with low insertion losses (3dB), to serve as node in a photonic neural network. An optimized electro-thermal switching mechanism, induced by Joule heating through tungsten contacts, is engineered. This operation allows to change the phase of the GSST film thus providing weight updating functionality to the network. We show that a 5 V pulse-train (<1 us, 20 pulses) applied to a serpentine contact produces crystallization and a single pulse of longer duration (2 us) amorphization, used to set the analog synaptic weights of a neuron. Emulating an opportunely trained 100x100 fully connected multilayered perceptron neural network with this weighting functionality embedded as photonic memory, shows up to 93% inference accuracy and robustness towards noise when performing predictions of unseen data

physics.app-ph↗

arXiv2019

Electronic Bottleneck Suppression in Next-generation Networks with Integrated Photonic Digital-to-analog Converters

Digital-to-analog converters (DAC) are indispensable functional units in signal processing instrumentation and wide-band telecommunication links for both civil and military applications. Since photonic systems are capable of high data throughput and low latency, an increasingly found system limitation stems from the required domain-crossing such as digital-to-analog, and electronic-to-optical. A photonic DAC implementation, in contrast, enables a seamless signal conversion with respect to both energy efficiency and short signal delay, often require bulky discrete optical components and electric-optic transformation hence introducing inefficiencies. Here, we introduce a novel coherent parallel photonic DAC concept along with an experimental demonstration capable of performing this digital-to-analog conversion without optic-electric-optic domain crossing. This design hence guarantees a linear intensity weighting among bits operating at high sampling rates, yet at a reduced footprint and power consumption compared to other photonic alternatives. Importantly, this photonic DAC could create seamless interfaces of next-generation data processing hardware for data-centers, task-specific compute accelerators such as neuromorphic engines, and network edge processing applications.

eess.SP↗

arXiv2019

A Winograd-based Integrated Photonics Accelerator for Convolutional Neural Networks

Neural Networks (NNs) have become the mainstream technology in the artificial intelligence (AI) renaissance over the past decade. Among different types of neural networks, convolutional neural networks (CNNs) have been widely adopted as they have achieved leading results in many fields such as computer vision and speech recognition. This success in part is due to the widespread availability of capable underlying hardware platforms. Applications have always been a driving factor for design of such hardware architectures. Hardware specialization can expose us to novel architectural solutions, which can outperform general purpose computers for tasks at hand. Although different applications demand for different performance measures, they all share speed and energy efficiency as high priorities. Meanwhile, photonics processing has seen a resurgence due to its inherited high speed and low power nature. Here, we investigate the potential of using photonics in CNNs by proposing a CNN accelerator design based on Winograd filtering algorithm. Our evaluation results show that while a photonic accelerator can compete with current-state-of-the-art electronic platforms in terms of both speed and power, it has the potential to improve the energy efficiency by up to three orders of magnitude.

cs.ET↗

arXiv2019

A Lateral MOS-Capacitor Enabled ITO Mach-Zehnder Modulator for Beam Steering

Here, we experimentally demonstrate an Indium Tin Oxide (ITO) Mach-Zehnder interferometer heterogeneously integrated in silicon photonics. The phase shifter section is realized in a novel lateral MOS configuration, which, due to favorable electrostatic overlap, leads to efficient modulation (VπL = 63 Vum). This is achieved by (i) selecting a strong index changing material (ITO) and (ii) improving the field overlap as verified by the electrostatic field lines. Furthermore, we show that this platform serves as a building block in an endfire silicon photonics optical phased array (OPA) with a half-wavelength pitch within the waveguides with anticipated performance, including narrow main beam lobe (<3°) and >10 dB suppression of the side lobes, while electrostatically steering the emission profile up to plus/minus 80°, and if further engineered, can lead not only towards nanosecond-fast beam steering capabilities in LiDAR systems but also in holographic display, free-space optical communications, and optical switches.

physics.app-ph↗

arXiv2019

Roadmap on Material-Function Mapping for Photonic-Electronic Hybrid Neural Networks

Driven by machine-learning tasks neural networks have demonstrated useful capabilities as nonlinear hypothesis classifiers. The underlying technologies performing the dot product multiplication, the summation, and the nonlinear thresholding on the input data in electronics, however, are limited by the same capacitive challenges known from electronic integrated circuits. The optical domain, in contrast, provides low delay interconnectivity suitable for such node distributed non Von Neumann architectures relying on dense node to node communication. Thus, once the neural network's weights are set, the delay of the network is just given by the time of flight of the photon, which is in the picosecond range for photonic integrated circuits. However, the functionality of memory for storing the trained weights does not exists in optics, thus demanding a fresh look to explore synergies between photonics and electronics in neural networks. Here we provide a roadmap to pave the way for emerging hybridized photonic electronic neural networks by taking a detailed look into a single node's perceptron, discussing how it can be realized in hybrid photonic electronic heterogeneous technologies. We show that a set of materials exist that exploit synergies with respect to a number of constrains including electronic contacts, memory functionality, electrooptic modulation, optical nonlinearity, and device packaging. We find that the material ITO, in particular, could provide a viable path for both the perceptron weights and the nonlinear activation function, while simultaneously being a foundry process near material. We finally identify a number of challenges that, if solved, could accelerate the adoption of such heterogeneous integration strategies of emerging memory materials into integrated photonics platforms for real time responsive neural networks.

physics.app-ph↗

arXiv2019

ITO-based Electro-absorption Modulator for Photonic Neural Activation Function

Recently integrated optics has become an intriguing platform for implementing machine learning algorithms and inparticular neural networks. Integrated photonic circuits can straightforwardly perform vector-matrix multiplicationswith high efficiency and low power consumption by using weighting mechanism through linear optics. Although,this can not be said for the activation function which requires either nonlinear optics or an electro-optic module withan appropriate dynamic range. Even though all-optical nonlinear optics is potentially faster, its current integrationis challenging and is rather inefficient. Here we demonstrate an electro-absorption modulator based on an IndiumTin Oxide layer, whose dynamic range is used as nonlinear activation function of a photonic neuron. The nonlinearactivation mechanism is based on a photodiode, which integrates the weighed products, and whose photovoltage drivesthe elecro-absorption modulator. The synapse and neuron circuit is then constructed to execute a 200-node MNISTclassification neural network used for benchmarking the nonlinear activation function and compared with an equivalentelectronic module.

physics.app-ph↗

arXiv2019

Coupling-enhanced Dual ITO Layer Electro-absorption Modulator in Silicon Photonics

Electro-optic signal modulation provides a key functionality in modern technology and information networks. Photonic integration has enabled not only miniaturizing photonic components, but also provided performance improvements due to co-design addressing both electrical and optical device rules. However, the millimeter-to-centimeter large footprint of many foundry-ready photonic electro-optic modulators significantly limits on-chip scaling density. To address these limitations, here we experimentally demonstrate a coupling-enhanced electro-absorption modulator by heterogeneously integrating a novel dual-gated indium-tin-oxide (ITO) phase-shifting tunable absorber placed at a silicon directional coupler region. Our experimental modulator shows a 2 dB extinction ratio for a just 4 um short device at 4 volt bias. Since no material nor optical resonances are deployed, this device shows spectrally broadband operation as demonstrated here across the entire C-band. In conclusion we demonstrate a modulator utilizing strong index-change from both real and imaginary part of active material enabling compact and high-performing modulators using semiconductor foundry-near materials.

physics.app-ph↗

arXiv2019

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 parameters of RF-sputtering, showing a holistic control of the quality of ITO thin films in the visible and particularly near-infrared spectral region. We further 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.

physics.app-ph↗

arXiv2018

Coupling-controlled Dual ITO Layer Electro-Optic Modulator in Silicon Photonics

Electro-optic signal modulation provides a key functionality in modern technology and information networks. Photonic integration has enabled not only miniaturizing photonic components, but also provided performance improvements due to co-design addressing both electrical and optical device rules. However the millimeter-to-centimeter large footprint of many foundry-ready photonic electro-optic modulators significantly limits scaling density. Furthermore, modulators bear a fundamental a frequency-response to energy-sensitive trade-off, a limitation that can be overcome with coupling-based modulators where the temporal response speed is decoupled from the optical cavity photo lifetime. Thus, the coupling effect to the resonator is modulated rather then tuning the index of the resonator itself. However, the weak electro-optic response of silicon limits such coupling modulator performance, since the micrometer-short overlap region of the waveguide-bus and a microring resonator is insufficient to induce signal modulation. To address these limitations, here we demonstrate a coupling-controlled electro-optic modulator by heterogeneously integrating a dual-gated indium-tin-oxide (ITO) phase shifter placed at the silicon microring-bus coupler region. Our experimental modulator shows about 4 dB extinction ratio on resonance, and a about 1.5 dB off resonance with a low insertion loss of 0.15 dB for a just 4 μm short device demonstrating a compact high 10:1 modulation-to-loss ratio. In conclusion we demonstrate a coupling modulator using strongly index-changeable materials enabling compact and high-performing modulators using semiconductor foundry-near materials.

physics.app-ph↗

arXiv2018

Compact Graphene Plasmonic Slot Photodetector on Silicon-on-insulator with High Responsivity

Graphene has extraordinary electro-optic properties and is therefore a promising candidate for monolithic photonic devices such as photodetectors. However, the integration of this atom-thin layer material with bulky photonic components usually results in a weak light-graphene interaction leading to large device lengths limiting electro-optic performance. In contrast, here we demonstrate a plasmonic slot graphene photodetector on silicon-on-insulator platform with high-responsivity given the 5 um-short device length. We observe that the maximum photocurrent, and hence the highest responsivity, scales inversely with the slot gap width. Using a dual-lithography step, we realize 15 nm narrow slots that show a 15-times higher responsivity per unit device-length compared to photonic graphene photodetectors. Furthermore, we reveal that the back-gated electrostatics is overshadowed by channel-doping contributions induced by the contacts of this ultra-short channel graphene photodetector. This leads to quasi charge neutrality, which explains both the previously-unseen offset between the maximum photovoltaic-based photocurrent relative to graphenes Dirac point and the observed non-ambipolar transport. Such micrometer compact and absorption-efficient photodetectors allow for short-carrier pathways in next-generation photonic components, while being an ideal testbed to study short-channel carrier physics in graphene optoelectronics.

physics.app-ph↗

arXiv2018

Loss and Coupling Tuning via Heterogeneous Integration of MoS2 Layers in Silicon Photonics

Layered two-dimensional (2D) materials provide a wide range of unique properties as compared to their bulk counterpart, making them ideal for heterogeneous integration for on-chip interconnects. Hence, a detailed understanding of the loss and index change on Si integrated platform is a prerequisite for advances in opto-electronic devices impacting optical communication technology, signal processing, and possibly photonic-based computing. Here, we present an experimental guide to characterize transition metal dichalcogenides (TMDs), once monolithically integrated into the Silicon photonic platform at 1.55 um wavelength. We describe the passive tunable coupling effect of the resonator in terms of loss induced as a function of 2D material layer coverage length and thickness. Further, we demonstrate a TMD-ring based hybrid platform as a refractive index sensor where resonance shift has been mapped out as a function of flakes thickness which correlates well with our simulated data. These experimental findings on passive TMD-Si hybrid platform open up a new dimension by controlling the effective change in loss and index, which may lead to the potential application of 2D material based active on chip photonics.

physics.optics↗

arXiv2018

All-optical Nonlinear Activation Function for Photonic Neural Networks

With the recent successes of neural networks (NN) to perform machine-learning tasks, photonic-based NN designs may enable high throughput and low power neuromorphic compute paradigms since they bypass the parasitic charging of capacitive wires. Thus, engineering data-information processors capable of executing NN algorithms with high efficiency is of major importance for applications ranging from pattern recognition to classification. Our hypothesis is therefore, that if the time-limiting electro-optic conversion of current photonic NN designs could be postponed until the very end of the network, then the execution time of the photonic algorithm is simple the delay of the time-of-flight of photons through the NN, which is on the order of picoseconds for integrated photonics. Exploring such all-optical NN, in this work we discuss two independent approaches of implementing the optical perceptrons nonlinear activation function based on nanophotonic structures exhibiting i) induced transparency and ii) reverse saturated absorption. Our results show that the all-optical nonlinearity provides about 3 and 7 dB extinction ratio for the two systems considered, respectively, and classification accuracies of an exemplary MNIST task of 97% and near 100% are found, which rivals that of software based trained NNs, yet with ignored noise in the network. Together with a developed concept for an all-optical perceptron, these findings point to the possibility of realizing pure photonic NNs with potentially unmatched throughput and even energy consumption for next generation information processing hardware.

physics.app-ph↗

arXiv2018

Multiband Plasmonic Sierpinski Carpet Fractal Antennas

Deterministic fractal antennas are employed to realize multimodal plasmonic devices. Such structures show strongly enhanced localized electromagnetic fields typically in the infrared range with a hierarchical spatial distribution. Realization of engineered fractal antennas operating in the optical regime would enable nanoplasmonic platforms for applications, such as energy harvesting, light sensing, and bio/chemical detection. Here, we introduce a novel plasmonic multiband metamaterial based on the Sierpinski carpet (SC) space-filling fractal, having a tunable and polarization-independent optical response, which exhibits multiple resonances from the visible to mid-infrared range. We investigate gold SCs fabricated by electron-beam lithography on CaF$_{2}$ and Si/SiO$_{2}$ substrates. Furthermore, we demonstrate that such resonances originate from diffraction-mediated localized surface plasmons, which can be tailored in deterministic fashion by tuning the shape, size, and position of the fractal elements. Moreover, our findings illustrate that SCs with high order of complexity present a strong and hierarchically distributed electromagnetic near-field of the plasmonic modes. Therefore, engineered plasmonic SCs provide an efficient strategy for the realization of compact active devices with a strong and broadband spectral response in the visible/mid-infrared range. We take advantage of such a technology by carrying out surface enhanced Raman spectroscopy (SERS) on Brilliant Cresyl Blue molecules deposited onto plasmonic SCs. We achieve a broadband SERS enhancement factor up to $10^{4}$, thereby providing a proof-of-concept application for chemical diagnostics.

physics.optics↗