Optical terabit transmitter and receiver based on passive polymer and InP technology for high-speed optical connectivity between datacenters

We demonstrate the hybrid integration of a multi-format tunable transmitter and a coherent optical receiver based on optical polymers and InP electronics and photonics for next generation metro and core optical networks. The transmitter comprises an array of two InP Mach-Zehnder modulators (MZMs) with 42 GHz bandwidth and two passive PolyBoards at the back- and front-end of the device. The back-end PolyBoard integrates an InP gain chip, a Bragg grating and a phase section on the polymer substrate capable of 22 nm wavelength tunability inside the C-band and optical waveguides that guide the light to the inputs of the two InP MZMs. The front-end PolyBoard provides the optical waveguides for combing the In-phase and Quadrature-phase modulated signals via an integrated thermo-optic phase shifter for applying the pi/2 phase-shift at the lower arm and a 3-dB optical coupler at the output. Two InP-double heterojunction bipolar transistor (InP-DHBT) 3-bit power digital-to-analog converters (DACs) are hybridly integrated at either side of the MZM array chip in order to drive the IQ transmitter with QPSK, 16-QAM and 64-QAM encoded signals. The coherent receiver is based on the other side on a PolyBoard, which integrates an InP gain chip and a monolithic Bragg grating for the formation of the local oscillator laser, and a monolithic 90° optical hybrid. This PolyBoard is further integrated with a 4-fold InP photodiode array chip with more than 80 GHz bandwidth and two high-speed InP-DHBT transimpedance amplifiers (TIAs) with automatic gain control. The transmitter and the receiver have been experimentally evaluated at 25Gbaud over 100 km for mQAM modulation showing bit-error-rate (BER) performance performance below FEC limit

Neuropsychosocial profiles of current and future adolescent alcohol misusers

A comprehensive account of the causes of alcohol misuse must accommodate individual differences in biology, psychology and environment, and must disentangle cause and effect. Animal models1 can demonstrate the effects of neurotoxic substances; however, they provide limited insight into the psycho-social and higher cognitive factors involved in the initiation of substance use and progression to misuse. One can search for pre-existing risk factors by testing for endophenotypic biomarkers2 in non-using relatives; however, these relatives may have personality or neural resilience factors that protect them from developing dependence3. A longitudinal study has potential to identify predictors of adolescent substance misuse, particularly if it can incorporate a wide range of potential causal factors, both proximal and distal, and their influence on numerous social, psychological and biological mechanisms4. Here we apply machine learning to a wide range of data from a large sample of adolescents (n = 692) to generate models of current and future adolescent alcohol misuse that incorporate brain structure and function, individual personality and cognitive differences, environmental factors (including gestational cigarette and alcohol exposure), life experiences, and candidate genes. These models were accurate and generalized to novel data, and point to life experiences, neurobiological differences and personality as important antecedents of binge drinking. By identifying the vulnerability factors underlying individual differences in alcohol misuse, these models shed light on the aetiology of alcohol misuse and suggest targets for prevention

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Broadband Packaging of Photodetectors for 100 Gb/s Ethernet Applications

The packing structure of functional modules is a major limitaion in achieving a desired performance for 100 Gb/s ethernet applications. This paper presents a methodology of developing advanced packaging of photodetectors (PDs) for high-speed data transmission applications by using 3-D electromagnetic (EM) simulations. A simplified model of the PD module is first used to analyze and optimize packaging structures and propose an optimal packaging design based on the simplified model. Although a PD module with improved performance proved the success of the optimal packaging design, the simplified model could not identify other important bandwidth limitation effects. Therefore, a full 3-D EM model of PD modules is developed to predict the optical-to-electrical response of the module, and with this model, it is possible to identify a critical mode mismatch effect as another important factor of limiting the bandwidth of PD modules. After eliminating the mode mismatch effect by improving the chip-conductor-backed coplanar waveguide transition, a final optimal packaging structure is implemented for the PD module with reduced attenuation up to 100 GHz and a broader 3-dB bandwidth of more than 90 GHz. Furthermore, the PD module exhibits excellent performance under the high-speed data-transmission experiment with 107 Gb/s data rate

Low-power/cost intra-datacentre architecture exploiting transmission and multiplexing in the interconnection fabric

We report a Datacentre system architecture and its performance, that is exploiting PON configurations in the interconnection fabric to play down the role of switching. Advanced transceiver technology is considered that is optimised for balancing performance with cost/power consumption

Gbit/s-operation of graphene electro-absorption modulators in a passive polymer waveguide platform for data and telecommunications

Graphene with its high carrier mobility as well as its tunable light absorption is an attractive active material for highspeed electro-absorption modulators (EAMs). Large-area CVD-grown graphene monolayers can be transferred onto arbitrary substrates to add active optoelectronic properties to intrinsically passive photonic integration platforms. In this work, we present graphene-based EAMs integrated in passive polymer waveguides. To facilitate modulation frequencies in the GHz range, a 50 Ω termination resistor as well as a DC blocking capacitor are integrated with graphene EAMs for the first time. Large signal data transmission experiments were carried out across the O, C and L optical communications bands. The fastest devices exhibit a 3-dB bandwidth of more than 4 GHz. Our analytical model of the modulation response for the graphene-based EAMs is in good agreement with the measurement results. It predicts that bandwidths greater than 50 GHz are possible with future device iterations. Owing to the absorption properties of the graphene layers, the devices are expected to be functional at smaller wavelengths of interest for optical interconnects and data-communications as well, offering a novel flexibility for the integration of high-speed functionalities in optoelectronic integrated circuits. Our work is the first step towards an Active Optical Printed Circuit Board, hiding the optics completely inside the board and thus removing entry barriers in manufacturing. We believe this will lead to the same success as observed in Active Optical Cables for short range optically wired connections

Photonic integrated devices and functions on hybrid polymer platform

Photonic devices and new functions based on HHI’s hybrid integration platform PolyBoard are presented providing lowloss thin-film-element-based light routing, an on-chip micro-optical bench and flexible chips comprising optical and electrical waveguides. The newly developed transfer and integration of graphene layers enables the fabrication of active optoelectronic devices in the intrinsically passive polymer waveguide networks with bandwidths in the GHz range. These novel functionalities in combination with the mature thermo-optic components of the PolyBoard platform such as tunable lasers, switches and variable attenuators pave the way towards new applications of photonic integrated circuits in communications and sensors

Hybrid Photonic Integration on a Polymer Platform

To fulfill the functionality demands from the fast developing optical networks, a hybrid integration approach allows for combining the advantages of various material platforms. We have established a polymer-based hybrid integration platform (polyboard), which provides flexible optical input/ouptut interfaces (I/Os) that allow robust coupling of indium phosphide (InP)-based active components, passive insertion of thin-film-based optical elements, and on-chip attachment of optical fibers. This work reviews the recent progress of our polyboard platform. On the fundamental level, multi-core waveguides and polymer/silicon nitride heterogeneous waveguides have been fabricated, broadening device design possibilities and enabling 3D photonic integration. Furthermore, 40-channel optical line terminals and compact, bi-directional optical network units have been developed as highly functional, low-cost devices for the wavelength division multiplexed passive optical network. On a larger scale, thermo-optic elements, thin-film elements and an InP gain chip have been integrated on the polyboard to realize a colorless, dual-polarization optical 90° hybrid as the frontend of a coherent receiver. For high-end applications, a wavelength tunable 100Gbaud transmitter module has been demonstrated, manifesting the joint contribution from the polyboard technology, high speed polymer electro-optic modulator, InP driver electronics and ceramic electronic interconnects