Photonic integration enabling new multiplexing concepts in optical board-to-board and rack-to-rack interconnects

New broadband applications are causing the datacenters to proliferate, raising the bar for higher interconnection speeds. So far, optical board-to-board and rack-to-rack interconnects relied primarily on low-cost commodity optical components assembled in a single package. Although this concept proved successful in the first generations of optical-interconnect modules, scalability is a daunting issue as signaling rates extend beyond 25 Gb/s. In this paper we present our work towards the development of two technology platforms for migration beyond Infiniband enhanced data rate (EDR), introducing new concepts in board-to-board and rack-to-rack interconnects. The first platform is developed in the framework of MIRAGE European project and relies on proven VCSEL technology, exploiting the inherent cost, yield, reliability and power consumption advantages of VCSELs. Wavelength multiplexing, PAM-4 modulation and multi-core fiber (MCF) multiplexing are introduced by combining VCSELs with integrated Si and glass photonics as well as BiCMOS electronics. An in-plane MCF-to-SOI interface is demonstrated, allowing coupling from the MCF cores to 340x400 nm Si waveguides. Development of a low-power VCSEL driver with integrated feed-forward equalizer is reported, allowing PAM-4 modulation of a bandwidth-limited VCSEL beyond 25 Gbaud. The second platform, developed within the frames of the European project PHOXTROT, considers the use of modulation formats of increased complexity in the context of optical interconnects. Powered by the evolution of DSP technology and towards an integration path between inter and intra datacenter traffic, this platform investigates optical interconnection system concepts capable to support 16QAM 40GBd data traffic, exploiting the advancements of silicon and polymer technologies

Training Passive Photonic Reservoirs with Integrated Optical Readout

As Moore's law comes to an end, neuromorphic approaches to computing are on the rise. One of these, passive photonic reservoir computing, is a strong candidate for computing at high bitrates (> 10 Gbps) and with low energy consumption. Currently though, both benefits are limited by the necessity to perform training and readout operations in the electrical domain. Thus, efforts are currently underway in the photonic community to design an integrated optical readout, which allows to perform all operations in the optical domain. In addition to the technological challenge of designing such a readout, new algorithms have to be designed in order to train it. Foremost, suitable algorithms need to be able to deal with the fact that the actual on-chip reservoir states are not directly observable. In this work, we investigate several options for such a training algorithm and propose a solution in which the complex states of the reservoir can be observed by appropriately setting the readout weights, while iterating over a predefined input sequence. We perform numerical simulations in order to compare our method with an ideal baseline requiring full observability as well as with an established black-box optimization approach (CMA-ES).Comment: Accepted for publication in IEEE Transactions on Neural Networks and Learning Systems (TNNLS-2017-P-8539.R1), copyright 2018 IEEE. This research was funded by the EU Horizon 2020 PHRESCO Grant (Grant No. 688579) and the BELSPO IAP P7-35 program Photonics@be. 11 pages, 9 figure

Singing synthesis with an evolved physical model

A two-dimensional physical model of the human vocal tract is described. Such a system promises increased realism and control in the synthesis. of both speech and singing. However, the parameters describing the shape of the vocal tract while in use are not easily obtained, even using medical imaging techniques, so instead a genetic algorithm (GA) is applied to the model to find an appropriate configuration. Realistic sounds are produced by this method. Analysis of these, and the reliability of the technique (convergence properties) is provided

A Study on Topology Optimization of Plasmonic Waveguide Devices Using Function Expansion Method and Evolutionary Approach

We propose a novel topology optimization method for plasmonic devices. Plasmonic devices that have a great potential to downsize various optical devices beyond the diffraction limit attract a lot of attention. In order to develop high-performance plasmonic devices, a novel design theory is expected to be established instead of the conventional theory for dielectric waveguide devices. In this paper, we employ the function expansion method to express a device structure in the design region and optimize the design variables by using several evolutionary approaches, which do not require the sensitivity analysis. The validity and usefulness of this approach are demonstrated through the design examples of optical diode and optical circulator

Synthesis of Artificial Magnetic Conductors Using Structure-Based Evolutionary Design

An evolutionary programming approach, the so-called structure based evolutionary design, is applied to the synthesis of planar periodic electronic band gap in order to obtain an artificial magnetic conductor surface. We show that this strategy, in conjunction with a flexible aperture-oriented approach, allows for obtaining new and effective structures. This almost unique ability is exploited to obtain an artificial magnetic conductor periodic surface with a bandwidth larger than the most popular surfaces known so far