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The extension of photonic technologies such as lidar and free-space optical communications from the traditional visible and near-infrared wavelengths to longer wavelengths can improve performance in adverse environments such as haze, fog, smoke, or strong solar background. Non-mechanical beam steerers will be a critical component of the low size, weight, and power modules needed for the portable or unmanned systems deployed in these environments. In this work, we demonstrate the first 2D optical phased array for non-mechanical beam steering in the mid-infrared spectral region. We combine a total internal-reflection mirror emitter with a non-redundant array of 30 elements to carry out 2D beam steering at a single wavelength of 4.6 $\mu$m. The experiment yielded 600 resolvable far-field points, with 2400 points over a $28^\circ \times 28^\circ$ field of view calculated theoretically. Moreover, the device was fabricated in a passive InGaAs/InP platform, contributing another advance in the ongoing development of quantum cascade laser-based photonic integration., Comment: Main document: 16 pages, 11 figures; Supplement: 3 pages, 2 figures

In recent decades, the demand for computational power has surged, particularly with the rapid expansion of artificial intelligence (AI). As we navigate the post-Moore's law era, the limitations of traditional electrical digital computing, including process bottlenecks and power consumption issues, are propelling the search for alternative computing paradigms. Among various emerging technologies, integrated photonics stands out as a promising solution for next-generation high-performance computing, thanks to the inherent advantages of light, such as low latency, high bandwidth, and unique multiplexing techniques. Furthermore, the progress in photonic integrated circuits (PICs), which are equipped with abundant photoelectronic components, positions photonic-electronic integrated circuits as a viable solution for high-performance computing and hardware AI accelerators. In this review, we survey recent advancements in both PIC-based digital and analog computing for AI, exploring the principal benefits and obstacles of implementation. Additionally, we propose a comprehensive analysis of photonic AI from the perspectives of hardware implementation, accelerator architecture, and software-hardware co-design. In the end, acknowledging the existing challenges, we underscore potential strategies for overcoming these issues and offer insights into the future drivers for optical computing.

The optical neural network (ONN) is a promising hardware platform for next-generation neuromorphic computing due to its high parallelism, low latency, and low energy consumption. However, previous integrated photonic tensor cores (PTCs) consume numerous single-operand optical modulators for signal and weight encoding, leading to large area costs and high propagation loss to implement large tensor operations. This work proposes a scalable and efficient optical dot-product engine based on customized multi-operand photonic devices, namely multi-operand optical neurons (MOON). We experimentally demonstrate the utility of a MOON using a multi-operand-Mach-Zehnder-interferometer (MOMZI) in image recognition tasks. Specifically, our MOMZI-based ONN achieves a measured accuracy of 85.89% in the street view house number (SVHN) recognition dataset with 4-bit voltage control precision. Furthermore, our performance analysis reveals that a 128x128 MOMZI-based PTCs outperform their counterparts based on single-operand MZIs by one to two order-of-magnitudes in propagation loss, optical delay, and total device footprint, with comparable matrix expressivity., Comment: 19 pages, 10 figures

The wide adoption and significant computing resource of attention-based transformers, e.g., Vision Transformers and large language models (LLM), have driven the demand for efficient hardware accelerators. There is a growing interest in exploring photonics as an alternative technology to digital electronics due to its high energy efficiency and ultra-fast processing speed. Photonic accelerators have shown promising results for CNNs, which mainly rely on weight-static linear operations. However, they encounter issues when efficiently supporting Transformer architectures, questioning the applicability of photonics to advanced ML tasks. The primary hurdle lies in their inefficiency in handling unique workloads in Transformers, i.e., dynamic and full-range tensor multiplication. In this work, we propose Lightening-Transformer, the first light-empowered, high-performance, and energy-efficient photonic Transformer accelerator. To overcome prior designs' fundamental limitations, we introduce a novel dynamically-operated photonic tensor core, DPTC, a crossbar array of interference-based optical vector dot-product engines supporting highly parallel, dynamic, and full-range matrix multiplication. Furthermore, we design a dedicated accelerator that integrates our novel photonic computing cores with photonic interconnects for inter-core data broadcast, fully unleashing the power of optics. Comprehensive evaluations show that ours achieves >2.6x energy and >12x latency reductions compared to prior photonic accelerators and delivers the lowest energy cost and 2 to 3 orders of magnitude lower energy-delay product compared to electronic Transformer accelerators, all while maintaining digital-comparable accuracy. Our work highlights the immense potential of photonics for advanced ML workloads, such as Transformer-backboned LLM. Our work is available at https://github.com/zhuhanqing/Lightening-Transformer., Comment: Published as a conference paper in HPCA 2024. Recieved the Reproducibility Badges at IEEE. Our implementation is available at https://github.com/zhuhanqing/Lightening-Transformer

Photonic computing shows promise for transformative advancements in machine learning (ML) acceleration, offering ultra-fast speed, massive parallelism, and high energy efficiency. However, current photonic tensor core (PTC) designs based on standard optical components hinder scalability and compute density due to their large spatial footprint. To address this, we propose an ultra-compact PTC using customized programmable multi-operand multimode interference (MOMMI) devices, named M3ICRO. The programmable MOMMI leverages the intrinsic light propagation principle, providing a single-device programmable matrix unit beyond the conventional computing paradigm of one multiply-accumulate (MAC) operation per device. To overcome the optimization difficulty of customized devices that often requires time-consuming simulation, we apply ML for optics to predict the device behavior and enable a differentiable optimization flow. We thoroughly investigate the reconfigurability and matrix expressivity of our customized PTC, and introduce a novel block unfolding method to fully exploit the computing capabilities of a complex-valued PTC for near-universal real-valued linear transformations. Extensive evaluations demonstrate that M3ICRO achieves a 3.4-9.6x smaller footprint, 1.6-4.4x higher speed, 10.6-42x higher compute density, 3.7-12x higher system throughput, and superior noise robustness compared to state-of-the-art coherent PTC designs, while maintaining close-to-digital task accuracy across various ML benchmarks. Our code is open-sourced at https://github.com/JeremieMelo/M3ICRO-MOMMI., Comment: 12 pages. Accepted to APL Machine Learning 2023

In the context of continued spread of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 and the emergence of new variants, the demand for rapid, accurate, and frequent detection is increasing. Besides, the new predominant strain, Omicron variant, manifests more similar clinical features to those of other common respiratory infections. The concurrent detection of multiple potential pathogens helps distinguish SARS-CoV-2 infection from other diseases with overlapping symptoms, which is significant for patients to receive tailored treatment and containing the outbreak. Here, we report a lab-on-a-chip biosensing platform for SARS-CoV-2 detection based on subwavelength grating micro-ring resonator. The sensing surface is functionalized by specific antibody against SARS-CoV-2 spike protein, which could produce redshifts of resonant peaks by antigen-antibody combination, thus achieving quantitative detection. Additionally, the sensor chip is integrated with a microfluidic chip with an anti-backflow Y-shaped structure that enables the concurrent detection of two analytes. In this study, we realized the detection and differentiation of COVID-19 and influenza A H1N1. Experimental results show that the limit of detection of our device reaches 100 fg/mL (1.31 fM) within 15 min detecting time, and cross-reactivity tests manifest the specificity of the optical diagnostic assay. Further, the integrated packaging and streamlined workflow facilitate its use for clinical applications. Thus, the biosensing platform offers a promising solution to achieve ultrasensitive, selective, multiplexed, and quantitative point-of-care detection of COVID-19.

Optical computing is an emerging technology for next-generation efficient artificial intelligence (AI) due to its ultra-high speed and efficiency. Electromagnetic field simulation is critical to the design, optimization, and validation of photonic devices and circuits. However, costly numerical simulation significantly hinders the scalability and turn-around time in the photonic circuit design loop. Recently, physics-informed neural networks have been proposed to predict the optical field solution of a single instance of a partial differential equation (PDE) with predefined parameters. Their complicated PDE formulation and lack of efficient parametrization mechanisms limit their flexibility and generalization in practical simulation scenarios. In this work, for the first time, a physics-agnostic neural operator-based framework, dubbed NeurOLight, is proposed to learn a family of frequency-domain Maxwell PDEs for ultra-fast parametric photonic device simulation. We balance the efficiency and generalization of NeurOLight via several novel techniques. Specifically, we discretize different devices into a unified domain, represent parametric PDEs with a compact wave prior, and encode the incident light via masked source modeling. We design our model with parameter-efficient cross-shaped NeurOLight blocks and adopt superposition-based augmentation for data-efficient learning. With these synergistic approaches, NeurOLight generalizes to a large space of unseen simulation settings, demonstrates 2-orders-of-magnitude faster simulation speed than numerical solvers, and outperforms prior neural network models by ~54% lower prediction error with ~44% fewer parameters. Our code is available at https://github.com/JeremieMelo/NeurOLight., Comment: 13 pages. Accepted to NeurIPS 2022

A micro-ring-resonator (MRR) optical biosensor based on the evanescent field sensing mechanism has been extensively studied due to its high sensitivity and compact device size. However, a suitable on-chip integrated spectrometer device has to be demonstrated for the lab-on-a-chip applications, which can read the resonance wavelength shift from MRR biosensors based on minuscule changes in refractive index. In this paper, we demonstrated the design and experimental results of the near-infrared lab-on-a-chip optical biosensor platform that monolithically integrates the MRR and the on-chip spectrometer on the silicon-on-insulator (SOI) wafer, which can eliminate the external optical spectrum analyzer for scanning the wavelength spectrum. The symmetric add-drop MRR biosensor is designed to have a free spectral range (FSR) of ~19 nm, and a bulk sensitivity of ~73 nm/RIU; then the drop-port output resonance peaks are reconstructed from the integrated spatial-heterodyne Fourier transform spectrometer (SHFTS) with the spectral resolution of ~3.1 nm and bandwidth of ~50 nm, which results in the limit of detection of 0.042 RIU. The MRR output spectrum with air- and water-claddings are measured and reconstructed from the MRR-SHFTS integrated device experimentally to validate the wavelength shifting measurement., Comment: 23 pages, 9 figures including supplementary

Optical I/O plays a crucial role in the lifespan of lab-on-a-chip systems, from preliminary testing to operation in the target environment. However, due to the precise alignments required, efficient and reliable fiber-to-chip connections remain challenging, yielding inconsistent test results and unstable packaged performance. To overcome this issue, for use in single mode on-chip systems, we propose the incorporation of area-enlarged grating couplers working in conjunction with multimode fibers. This combination enables simpler, faster, and more reliable connections than the traditional small area grating coupler with single-mode fiber. In this work, we experimentally demonstrate a 3dB in-plane (X, Y) spatial tolerance of (10.2 {\mu}m, 17.3 {\mu}m) for the large area configuration, being at least (2.49, 3.33) times that of the small area one, and agreeing well with theoretical calculations. The simple concept is readily applicable to a range of photonic systems where cheaper more robust optical I/O is desired., Comment: 11 pages, 5 figures

Photonic tensor cores (PTCs) are essential building blocks for optical artificial intelligence (AI) accelerators based on programmable photonic integrated circuits. PTCs can achieve ultra-fast and efficient tensor operations for neural network (NN) acceleration. Current PTC designs are either manually constructed or based on matrix decomposition theory, which lacks the adaptability to meet various hardware constraints and device specifications. To our best knowledge, automatic PTC design methodology is still unexplored. It will be promising to move beyond the manual design paradigm and "nurture" photonic neurocomputing with AI and design automation. Therefore, in this work, for the first time, we propose a fully differentiable framework, dubbed ADEPT, that can efficiently search PTC designs adaptive to various circuit footprint constraints and foundry PDKs. Extensive experiments show superior flexibility and effectiveness of the proposed ADEPT framework to explore a large PTC design space. On various NN models and benchmarks, our searched PTC topology outperforms prior manually-designed structures with competitive matrix representability, 2-30x higher footprint compactness, and better noise robustness, demonstrating a new paradigm in photonic neural chip design. The code of ADEPT is available at https://github.com/JeremieMelo/ADEPT using the https://github.com/JeremieMelo/pytorch-onn (TorchONN) library., Comment: Accepted to ACM/IEEE Design Automation Conference (DAC), 2022

With the recent advances in optical phase change material (PCM), photonic in-memory neurocomputing has demonstrated its superiority in optical neural network (ONN) designs with near-zero static power consumption, time-of-light latency, and compact footprint. However, photonic tensor cores require massive hardware reuse to implement large matrix multiplication due to the limited single-core scale. The resultant large number of PCM writes leads to serious dynamic power and overwhelms the fragile PCM with limited write endurance. In this work, we propose a synergistic optimization framework, ELight, to minimize the overall write efforts for efficient and reliable optical in-memory neurocomputing. We first propose write-aware training to encourage the similarity among weight blocks, and combine it with a post-training optimization method to reduce programming efforts by eliminating redundant writes. Experiments show that ELight can achieve over 20X reduction in the total number of writes and dynamic power with comparable accuracy. With our ELight, photonic in-memory neurocomputing will step forward towards viable applications in machine learning with preserved accuracy, order-of-magnitude longer lifetime, and lower programming energy., Comment: 7 pages, 8 figures, accepted by ASPDAC 2022

The on-chip broadband optical spectrometers which cover the entire tissue transparency window ({\lambda}=650-1050 nm) with high resolution are highly demanded for the miniaturized bio-sensing and bio-imaging applications. Here, we propose a novel type of spatial heterodyne Fourier transform spectrometer (SHFTS) integrated with a sub-wavelength grating coupler (SWGC) for the dual-polarization bandpass sampling on the Si3N4 platform. Through tuning the coupling angles with different polarization, we experimentally demonstrated the unprecedented broadband spectrum retrieval results with the overall bandwidth coverage of 400 nm, bridging the wavelengths from 650 nm to 1050 nm, with the resolution of 2-5 nm. By applying the bandpass sampling theorem, we circumvented the intrinsic trade-off limitation between the bandwidth and resolution of SHFTS without having an outrageous number of Mach-Zehnder interferometer (MZI) arrays or adding additional active components. The bandpass sampling SHFTS is designed to have linearly unbalanced 32 MZIs with the maximum optical path length difference of 93 {\mu}m within an overall footprint size of 4.7 mm x 0.65 mm, and the coupling angles of SWGC are varied from 0{\deg} to 32{\deg} to cover the entire tissue transparency window., Comment: 48 Pages, 6 figures, 14 supportive figures

The optical neural network (ONN) is a promising hardware platform for next-generation neurocomputing due to its high parallelism, low latency, and low energy consumption. Previous ONN architectures are mainly designed for general matrix multiplication (GEMM), leading to unnecessarily large area cost and high control complexity. Here, we move beyond classical GEMM-based ONNs and propose an optical subspace neural network (OSNN) architecture, which trades the universality of weight representation for lower optical component usage, area cost, and energy consumption. We devise a butterfly-style photonic-electronic neural chip to implement our OSNN with up to 7x fewer trainable optical components compared to GEMM-based ONNs. Additionally, a hardware-aware training framework is provided to minimize the required device programming precision, lessen the chip area, and boost the noise robustness. We experimentally demonstrate the utility of our neural chip in practical image recognition tasks, showing that a measured accuracy of 94.16% can be achieved in hand-written digit recognition tasks with 3-bit weight programming precision., Comment: 17 pages,5 figures

Silicon-photonics-based optical neural network (ONN) is a promising hardware platform that could represent a paradigm shift in efficient AI with its CMOS-compatibility, flexibility, ultra-low execution latency, and high energy efficiency. In-situ training on the online programmable photonic chips is appealing but still encounters challenging issues in on-chip implementability, scalability, and efficiency. In this work, we propose a closed-loop ONN on-chip learning framework L2ight to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated photonic circuit states under challenging physical constraints, then performs photonic core mapping via combined analytical solving and zeroth-order optimization. A subspace learning procedure with multi-level sparsity is integrated into L2ight to enable in-situ gradient evaluation and fast adaptation, unleashing the power of optics for real on-chip intelligence. Extensive experiments demonstrate our proposed L2ight outperforms prior ONN training protocols with 3-order-of-magnitude higher scalability and over 30X better efficiency, when benchmarked on various models and learning tasks. This synergistic framework is the first scalable on-chip learning solution that pushes this emerging field from intractable to scalable and further to efficient for next-generation self-learnable photonic neural chips. From a co-design perspective, L2ight also provides essential insights for hardware-restricted unitary subspace optimization and efficient sparse training. We open-source our framework at https://github.com/JeremieMelo/L2ight., Comment: 10 pages. Accepted to NeurIPS 2021

Deep neural networks (DNN) have shown superior performance in a variety of tasks. As they rapidly evolve, their escalating computation and memory demands make it challenging to deploy them on resource-constrained edge devices. Though extensive efficient accelerator designs, from traditional electronics to emerging photonics, have been successfully demonstrated, they are still bottlenecked by expensive memory accesses due to tremendous gaps between the bandwidth/power/latency of electrical memory and computing cores. Previous solutions fail to fully-leverage the ultra-fast computational speed of emerging DNN accelerators to break through the critical memory bound. In this work, we propose a general and unified framework to trade expensive memory transactions with ultra-fast on-chip computations, directly translating to performance improvement. We are the first to jointly explore the intrinsic correlations and bit-level redundancy within DNN kernels and propose a multi-level in situ generation mechanism with mixed-precision bases to achieve on-the-fly recovery of high-resolution parameters with minimum hardware overhead. Extensive experiments demonstrate that our proposed joint method can boost the memory efficiency by 10-20x with comparable accuracy over four state-of-the-art designs, when benchmarked on ResNet-18/DenseNet-121/MobileNetV2/V3 with various tasks., Comment: Accepted by International Conference on Computer Vision (ICCV) 2021

Optical neural networks (ONNs) have demonstrated record-breaking potential in high-performance neuromorphic computing due to their ultra-high execution speed and low energy consumption. However, current learning protocols fail to provide scalable and efficient solutions to photonic circuit optimization in practical applications. In this work, we propose a novel on-chip learning framework to release the full potential of ONNs for power-efficient in situ training. Instead of deploying implementation-costly back-propagation, we directly optimize the device configurations with computation budgets and power constraints. We are the first to model the ONN on-chip learning as a resource-constrained stochastic noisy zeroth-order optimization problem, and propose a novel mixed-training strategy with two-level sparsity and power-aware dynamic pruning to offer a scalable on-chip training solution in practical ONN deployment. Compared with previous methods, we are the first to optimize over 2,500 optical components on chip. We can achieve much better optimization stability, 3.7x-7.6x higher efficiency, and save >90% power under practical device variations and thermal crosstalk., Comment: 7 pages content, 2 pages of reference, 6 figures, 4 tables, accepted to Association for the Advancement of Artificial Intelligence (AAAI) 2021

The vertical-cavity surface-emitting lasers (VCSELs) have emerged as a vital approach for realizing energy efficient, high speed optical interconnects in the data center and supercomputers. As of today, VCSEL is the most suitable for mass production in terms of cost-effectiveness and reliability. However, there are still key challenges for higher speed modulation above 40 GHz. Here, a hexagonal transverse coupled cavity VCSEL adiabatically coupled through the center cavity is proposed. A 3-dB roll-off modulation bandwidth of 45 GHz is demonstrated, which is five times greater than a conventional VCSEL fabricated on the same epi-wafer structure. While a parity time (PT) symmetry approaches add loss to engineer the topological state of the laser system, here, a radical paradigm shift with gain introduces symmetry breaking. This idea, then enables a single mode operation with a side-mode suppression-ratio (SMSR) of > 30 decibels and signal-to-noise ratio (SNR) of > 45 decibels. The energy distribution inside the coupled cavity system is also redistributed to provide a coherent gain in a spatially separated system. Consequently, throughput power is three times higher than that of the conventional VCSEL., Comment: 14 pages, 4 figures

The sudden rise of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic early 2020 throughout the world has called into drastic action measures to do instant detection and reduce the spread rate. The common diagnostics testing methods has been only partially effective in satisfying the booming demand for fast detection methods to contain the further spread. However, the point-of-risk accurate diagnosis of this new emerging viral infection is paramount as simultaneous normal working operation and dealing with symptoms of SARS-CoV-2 can become the norm for years to come. Sensitive cost-effective biosensor with mass production capability is crucial throughout the world until a universal vaccination become available. Optical label-free biosensors can provide a non-invasive, extremely sensitive rapid detection technique up to ~1 fM concentration along with few minutes sensing. These biosensors can be manufactured on a mass-scale (billions) to detect the COVID-19 viral load in nasal, saliva, urinal, and serological samples even if the infected person is asymptotic. Methods investigated here are the most advanced available platforms for biosensing optical devices resulted from the integration of state-of-the-art designs and materials. These approaches are including but not limited to integrated optical devices, plasmonic resonance and also emerging nanomaterial biosensors. The lab-on-a-chip platforms examined here are suitable not only for SARS-CoV-2 spike protein detection but also other contagious virions such as influenza, and middle east respiratory syndrome (MERS)., Comment: 52 pages, 19 figures

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 VpL of 95 Vum, deploying an 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.

Here, we demonstrate a spectrally broadband, GHz-fast Mach-Zehnder interferometeric modulator, exhibiting a miniscule VpL of 95 V-um, deploying a sub-wavelength short electrostatically tunable plasmonic phase-shifter, based on heterogeneously integrated ITO thin films into silicon photonics.

In a laser system non-Hermitian methods such as Parity-Time (PT) Symmetry and Supersymmetry (SUSY) have shown and demonstrated the ability to suppress unwanted lasing modes and, thus, achieved single mode lasing operation through the addition of lossy passive elements. While these approaches enable laser engineering versatility, they rely on the drawback of adding optical losses to a system tasked to produce single mode gain. Unlike PT and SUSY lasers, here we show an extra loss-free non-Hermitian laser engineering approach to realize single mode lasing operation for the first time. By selectively enhancing the fundamental modes quality factor, we obtain single mode operation with higher output power per cavity since all cavities in this system contribute to the laser output, in contrast to other non-Hermitian approaches. Furthermore, we show that this approach interestingly allows reducing the number of to-be-designed cavities in super-partner array as compared with, for example, the SUSY approach, thus leading to reduced design complexity upon coupled cavity scale up of laser arrays. In summary, the ability to engineer coupled laser systems where each laser cavity contributes to coherent light amplification opens up a new degree of laser-design freedom leading to increased device performance and simultaneous reduced design and fabrication complexity.

We investigate 1D aperiodic multilayer microstructures in order to achieve near total absorption in preselected wavelengths in a graphene monolayer. Our structures are designed by a genetic optimization algorithm coupled to a transfer matrix code. Coupled mode theory (CMT) analysis, in accordance with transfer matrix method (TMM) results, indicates the existence of a critical coupling in a graphene monolayer for perfect absorptions. Our findings show that the near-total-absorption peaks are highly tunable and can be controlled simultaneously or independently in wide range of wavelengths in the near-infrared and visible. Our proposed approach is metal free and does not require surface texturing or patterning, and can be applied for other two dimensional (2D) materials., Comment: 12 pages, 5 figures

In atomic multi-level systems, adiabatic elimination is a method used to minimize complicity of the system by eliminating irrelevant and strongly coupled levels by detuning them from one-another. Such a three-level system, for instance, can be mapped onto physical in form of a three-waveguide system. Actively detuning the coupling strength between the respective waveguide modes allows modulating light propagating through the device, as proposed here. The outer waveguides act as an effective two- photonic-mode system similar to ground- and excited states of a three-level atomic system, whilst the center waveguide is partially plasmonic. In adiabatic elimination regime, the amplitude of the middle waveguide oscillates much faster in comparison to the outer waveguides leading to a vanishing field build up. As a result, the middle waveguide becomes a dark state and hence a low insertion-loss of 8 decibel is expected to keep when achieving the modulation depth as high as 70 decibel despite the involvement of a plasmonic waveguide in the design presented here. The modulation mechanism relies on switching this waveguide system from a critical coupling regime to adiabatic elimination condition via electrostatically tuning the free-carrier concentration and hence the optical index of a thin ITO layer residing in the plasmonic center waveguide. This alters the effective coupling length and the phase mismatching condition thus modulation in each of outer waveguides. Our results show a modulator energy efficiency as low as 40 atto-joule per bit and an extinction ratio of 50 decibel. Given the minuscule footprint of the modulator, the resulting lumped-element limited RC delay is expected to exceed 200 giga hertz. This type of modulator paves the way for next-generation both energy-and speed conscience optical short-reach interconnects., Comment: 11 Pages,5 figures

Electromagnetic (EM) wave detection over a large spectrum has recently attracted significant amount of attention. Traditional electronic EM wave sensors use large metallic probes which distort the field to be measured and also have strict limitations on the detectable RF bandwidth. To address these problems, integrated photonic EM wave sensors have been developed to provide high sensitivity and broad bandwidth. Previously we demonstrated a compact, broadband, and sensitive integrated photonic EM wave sensor, consisting of an organic electro-optic (EO) polymer refilled silicon slot photonic crystal waveguide (PCW) modulator integrated with a gold bowtie antenna, to detect the X band of the electromagnetic spectrum. However, due to the relative large RC constant of the silicon PCW, such EM wave sensors can only work up to tens of GHz. In this work, we present a detailed design and discussion of a new generation of EM wave sensors based on EO polymer refilled plasmonic slot waveguides in conjunction with bowtie antennas to cover a wider electromagnetic spectrum from 1 GHz up to 10THz, including the range of microwave, millimeter wave and even terahertz waves. This antenna-coupled plasmonic-organic hybrid (POH) structure is designed to provide an ultra-small RC constant, a large overlap between plasmonic mode and RF field, and strong electric field enhancement, as well as negligible field perturbation. A taper is designed to bridge silicon strip waveguide to plasmonic slot waveguide. Simulation results show that our device can have an EM wave sensing ability up to 10 THz. To the best of our knowledge, this is the first POH device for photonic terahertz wave detection., Comment: 8 pages, 6 figures, SPIE Photonics West 2016, Paper No. 975614-975614-975618. arXiv admin note: text overlap with arXiv:1503.01904

The bowtie antenna is a topic of growing interest in recent years. In this paper, we design, fabricate, and characterize a modified gold bowtie antenna integrated on a transparent silica substrate. The bowtie antenna is designed with broad RF bandwidth to cover the X-band in the electromagnetic spectrum. We numerically investigate the antenna characteristics, specifically its resonant frequency and enhancement factor. Our designed bowtie antenna provides a strong broadband electric field enhancement in its feed gap. Taking advantage of the low-k silica substrate, high enhancement factor can be achieved without the unwanted reflection and scattering from the backside silicon handle which is the issue of using an SOI substrate. We simulate the dependence of resonance frequency on bowtie geometry, and verify the simulation results through experimental investigation, by fabricating different sets of bowtie antennas on silica substrates and then measuring their resonance frequencies. In addition, the far-field radiation pattern of the bowtie antenna is measured, and it shows dipole-like characteristics with large beam width. Such a broadband antenna will be useful for a myriad of applications, ranging from photonic electromagnetic wave sensing to wireless communications., Comment: arXiv admin note: substantial text overlap with arXiv:1503.01907

We design, fabricate, and experimentally demonstrate a compact thermo-optic gate switch comprising a 3.78 um-long coupled L0-type photonic crystalmicrocavities on a silicon-on-insulator substrate. A nanohole is inserted in the center of each individual L0 photonic crystalmicrocavity. Coupling between identical microcavities gives rise to bonding and anti-bonding states of the coupled photonic molecules. The coupled photonic crystalmicrocavities are numerically simulated and experimentally verified with a 6 nm-wide flat-bottom resonance in its transmission spectrum, which enables wider operational spectrum range than microring resonators. An integrated micro-heater is in direct contact with the silicon core to efficiently drive the device. The thermo-optic switch is measured with an optical extinction ratio of 20 dB, an on-off switching power of 18.2 mW, a thermo-optic tuning efficiency of 0.63 nm/mW, a rise time of 14.8 us, and a fall time of 18.5 us. The measured on-chip loss on the transmission band is as low as 1 dB.

In this paper, we design a dielectric-to-plasmonic slot waveguide mode converter based on the hybrid silicon-gold taper. The effects of mode matching, the effective index matching, and the metallic absorption loss on the conversion efficiency are studied. Consequently, a metallic taper-funnel coupler with an overall length of 1.7um is designed to achieve a very high conversion efficiency of 93.3% at 1550 nm. The configuration limitations for not allowing this mode converter to achieve a 100% conversion efficiency are also investigated. Such a high-efficiency converter can provide practical routes to realize ultracompact integrated circuits., Comment: 6 pages, 7 figures

The bowtie antenna is a topic of growing interest in recent years. In this paper, we design, fabricate, and characterize a modified gold bowtie antenna integrated on a transparent glass substrate. We numerically investigate the antenna characteristics, specifically its resonant frequency and enhancement factor. We simulate the dependence of resonance frequency on bowtie geometry, and verify the simulation results through experimental investigation, by fabricating different sets of bowtie antennas on glass substrates utilizing CMOS compatible processes and measuring their resonance frequencies. Our designed bowtie antenna provides a strong broadband electric field enhancement in its feed gap. The far-field radiation pattern of the bowtie antenna is measured, and it shows dipole-like characteristics with large beam width. Such a broadband antenna will be useful for a myriad of applications, ranging from wireless communications to electromagnetic wave detection., Comment: 8 pages, 7 figures, SPIE Photonics West Conference

Silicon-organic hybrid integrated devices have emerging applications ranging from high-speed optical interconnects to photonic electromagnetic-field sensors. Silicon slot photonic crystal waveguides (PCWs) filled with electro-optic (EO) polymers combine the slow-light effect in PCWs with the high polarizability of EO polymers, which promises the realization of high-performance optical modulators. In this paper, a broadband, power-efficient, low-dispersion, and compact optical modulator based on an EO polymer filled silicon slot PCW is presented. A small voltage-length product of V{\pi}*L=0.282Vmm is achieved, corresponding to an unprecedented record-high effective in-device EO coefficient (r33) of 1230pm/V. Assisted by a backside gate voltage, the modulation response up to 50GHz is observed, with a 3-dB bandwidth of 15GHz, and the estimated energy consumption is 94.4fJ/bit at 10Gbit/s. Furthermore, lattice-shifted PCWs are utilized to enhance the optical bandwidth by a factor of ~10X over other modulators based on non-band-engineered PCWs and ring-resonators., Comment: 12 pages, 4 figures, SPIE Photonics West Conference 2015

We design, fabricate and experimentally demonstrate a highly efficient adiabatic mode converter for coupling light into a silicon slot waveguide with a slot width as large as 320nm. This strip-to-slot mode converter is optimized to provide a measured insertion loss as low as 0.08dB. Our mode converter provides 0.1dB lower loss compared to a conventional V-shape mode converter. This mode converter is used to couple light into and out of a 320nm slot photonic crystal waveguide, and it is experimentally shown to improve the coupling efficiency up to 3.5dB compared to the V-shape mode converter, over the slow-light wavelength region., Comment: 13 pages, 7 figures, SPIE Photonics West Conference 2014

In this work, we design, fabricate and characterize a compact, broadband and highly sensitive integrated photonic electromagnetic field sensor based on a silicon-organic hybrid modulator driven by a bowtie antenna. The large electro-optic (EO) coefficient of organic polymer, the slow-light effects in the silicon slot photonic crystal waveguide (PCW), and the broadband field enhancement provided by the bowtie antenna, are all combined to enhance the interaction of microwaves and optical waves, enabling a high EO modulation efficiency and thus a high sensitivity. The modulator is experimentally demonstrated with a record-high effective in-device EO modulation efficiency of r33=1230pm/V. Modulation response up to 40GHz is measured, with a 3-dB bandwidth of 11GHz. The slot PCW has an interaction length of 300um, and the bowtie antenna has an area smaller than 1cm2. The bowtie antenna in the device is experimentally demonstrated to have a broadband characteristics with a central resonance frequency of 10GHz, as well as a large beam width which enables the detection of electromagnetic waves from a large range of incident angles. The sensor is experimentally demonstrated with a minimum detectable electromagnetic power density of 8.4mW/m2 at 8.4GHz, corresponding to a minimum detectable electric field of 2.5V/m and an ultra-high sensitivity of 0.000027V/m Hz^-1/2 ever demonstrated. To the best of our knowledge, this is the first silicon-organic hybrid device and also the first PCW device used for the photonic detection of electromagnetic waves. Finally, we propose some future work, including a Teraherz wave sensor based on antenna-coupled electro-optic polymer filled plasmonic slot waveguide, as well as a fully packaged and tailgated device., Comment: 20 pages, 16 figures

We design and demonstrate a compact, low-power, low-dispersion and broadband optical modulator based on electro-optic (EO) polymer refilled silicon slot photonic crystal waveguide (PCW). The EO polymer is engineered for large EO activity and near-infrared transparency. The half-wave switching-voltage is measured to be V{\pi}=0.97V over optical spectrum range of 8nm, corresponding to a record-high effective in-device r33 of 1190pm/V and V{\pi} L of 0.291Vmm in a push-pull configuration. Excluding the slow-light effect, we estimate the EO polymer is poled with an ultra-high efficiency of 89pm/V in the slot. In addition, to achieve high-speed modulation, silicon PCW is selectively doped to reduce RC time delay. The 3-dB RF bandwidth of the modulator is measured to be 11GHz, and a modulation response up to 40GHz is observed., Comment: 8 pages, 5 pages

We design, fabricate and experimentally demonstrate a highly efficient adiabatic mode converter for coupling light into a silicon slot waveguide with a slot width as large as 320nm. This strip-to-slot mode converter is optimized to provide a measured insertion loss as low as 0.08dB. Our mode converter provides 0.1dB lower loss compared to a conventional V-shape mode converter. This mode converter is used to couple light into and out of a 320nm slot photonic crystal waveguide, and it is experimentally shown to improve the coupling efficiency up to 3.5dB compared to the V-shape mode converter, over the slow-light wavelength region., Comment: 13 pages, 7 figures

In this paper, we present the design and experimental demonstration of a high dynamic range electric field sensor based on electro-optic (EO) polymer directional coupler waveguides that offers the strong and ultra-fast EO response of EO polymer. As compared to conventional photonic electric field sensors, our directional coupler waveguide design offers several advantages such as bias-free operation, highly linear measurement response up to 70dB, and a wide electric field detection range from 16.7V/m to 750kV/m at a frequency of 1GHz., Comment: 7 pages, 5 figures, conference. "EO-polymer waveguide based high dynamic range EM wave sensors", SPIE Photonics West, Proc. SPIE 8258, 82580Y, 2012. arXiv admin note: substantial text overlap with arXiv:1403.0138

Polymer based electro-optic modulators have shown great potentials in high frequency analog optical links. Existing commercial LiNibO3 Mach-Zehnder modulators have intrinsic drawbacks in linearity to provide high fidelity communication. In this paper, we present the design, fabrication and characterization of a traveling wave directional coupler modulator based on electro-optic polymer, which is able to provide high linearity, high speed, and low optical insertion loss. A silver ground electrode is used to reduce waveguide sidewall roughness due to the scattering of UV light in photolithography process in addition to suppressing the RF loss. A 1-to-2 multi-mode interference 3dB-splitter, a photobleached refractive index taper and a quasi-vertical taper are used to reduce the optical insertion loss of the device. The symmetric waveguide structure of the MMI-fed directional coupler is intrinsically bias-free, and the modulation is obtained at the 3-dB point regardless of the ambient temperature. By achieving low RF loss, characteristic impedance matching with 50{\Omega} load, and excellent velocity matching between the RF wave and the optical wave, a travelling wave electrode is designed to function up to 62.5GHz. Domain-inversion poling with push-pull configuration is applied using alternating pulses on a 2-section directional-coupler to achieve a spurious free dynamic range of 110dB/Hz2/3. The 3-dB electrical bandwidth of device is measured to be 10GHz., Comment: 11 pages, 12 figures, conference. "Improved performance of traveling wave directional coupler modulator based on electro-optic polymer," SPIE Photonics West, Proc. SPIE 8267, 82671B, 2012. arXiv admin note: text overlap with arXiv:1403.0134

The accelerating increase in information traffic demands the expansion of optical access network systems that require cost reduction of optical and photonic components. Low cost, ease of fabrication, and integration capabilities of low optical-loss polymers make them attractive for photonic applications. In addition to passive wave-guiding components, electro-optic (EO) polymers consisting of a polymeric matrix doped with organic nonlinear chromophores have enabled wide-RF-bandwidth and low-power optical modulators. Beside board level passive and active optical components, compact on-chip modulators (a few 100 micronmeters to a few millimeters) have been made possible by hybrid integration of EO polymers onto the silicon platform. This paper summarizes some of the recent progress in polymer based optical modulators and interconnects. A highly linear, broadband directional coupler modulator for use in analog optical links and compact, and low-power silicon/polymer hybrid slot photonic crystal waveguide modulators for on chip applications are presented. Recently, cost-effective roll-to-roll fabrication of electronic and photonic systems on flexible substrates has been gaining interest. A low-cost imprinted/ink-jet-printed Mach-Zehnder modulator and board-to-board optical interconnects using microlens integrated 45-degree mirror couplers compatible with the roll-to-roll fabrication platforms are also presented., Comment: 15 pages, 17 figures. arXiv admin note: text overlap with arXiv:1403.0134

In this paper, we present the design, fabrication and characterization of a traveling wave directional coupler modulator based on electro-optic polymer, which is able to provide both high linearity and broad bandwidth. The high linearity is realized by introducing domain-inversion technique in the two-domain directional coupler. A travelling wave electrode is designed to function with bandwidth-length product of 302GHz cm, by achieving low microwave loss, excellent impedance matching and velocity matching, as well as smooth electric field profile transformation. The 3-dB bandwidth of the device is measured to be 10GHz. The spurious free dynamic range of about 110dB Hz^(2/3) is measured over the modulation frequency range 2-8GHz. To the best of our knowledge, such high linearity is first measured at the frequency up to 8GHz. In addition, a 1-to-2 multi-mode interference 3dB-splitter, a photobleached refractive index taper and a quasi-vertical taper are used to reduce the optical insertion loss of the device., Comment: 18 pages, 12 figures

The present work demonstrates an electro-optic polymer based Mach-Zehnder (MZ) modulator fabricated utilizing advanced ultraviolet (UV) imprinting and aligned ink-jet printing technologies for patterning and layer deposition. The bottom electrode layer is designed and directly ink-jet printed on the substrate to form the patterned layer. The waveguide structure is formed into a bottom cladding polymer using a transparent flexible mold based UV imprinting method. All other layers can be ink-jet printed. The top electrode is aligned and printed over the Mach-Zehnder arm. The modulator demonstrates a V-pi of 8V at 3kHz. This technology shows great potential in minimizing the fabrication complexity and roll-to-roll compatibility for manufacturing low cost, light-weight, and conformal modulators at high throughput., Comment: 3 pages, 4 figures

We design a high dynamic range electric field sensor based on domain inverted electro-optic (E-O) polymer Y-fed directional coupler for electromagnetic wave detection. This electrode-less, all optical, wideband electrical field sensor is fabricated using standard processing for E-O polymer photonic devices. Experimental results demonstrate effective detection of electric field from 16.7V/m to 750KV/m at a frequency of 1GHz, and spurious free measurement range of 70dB., Comment: 6 pages, 5 figures

We present the design of a compact and highly sensitive electric field sensor based on a bowtie antenna-coupled slot photonic crystal waveguide (PCW). An electro-optic (EO) polymer with a large EO coefficient, r33=100pm/V, is used to refill the PCW slot and air holes. Bowtie-shaped electrodes are used as both poling electrodes and as receiving antenna. The slow-light effect in the PCW is used to increase the effective in-device r33>1000pm/V. The slot PCW is designed for low-dispersion slow light propagation, maximum poling efficiency as well as optical mode confinement inside the EO polymer. The antenna is designed for operation at 10GHz., Comment: 7 pages, 5 figures, conference. "Electric field sensor based on electro-optic polymer refilled silicon slot photonic crystal waveguide coupled with bowtie antenna," Proc. SPIE 8624, 862418 (2013)

We design and demonstrate a compact and low-power band-engineered electro-optic (EO) polymer refilled silicon slot photonic crystal waveguide (PCW) modulator. The EO polymer is engineered for large EO activity and near-infrared transparency. A PCW step coupler is used for optimum coupling to the slow-light mode of the band-engineered PCW. The half-wave switching-voltage is measured to be V{\pi}=0.97+-0.02V over optical spectrum range of 8nm, corresponding to the effective in-device r33 of 1190pm/V and V{\pi} L of 0.291+-0.006V mm in a push-pull configuration. Excluding the slow-light effect, we estimate the EO polymer is poled with an efficiency of 89pm/V in the slot., Comment: 4 pages, 4 figures