NASA Tech Briefs, December 2008

Topics covered include: Crew Activity Analyzer; Distributing Data to Hand-Held Devices in a Wireless Network; Reducing Surface Clutter in Cloud Profiling Radar Data; MODIS Atmospheric Data Handler; Multibeam Altimeter Navigation Update Using Faceted Shape Model; Spaceborne Hybrid-FPGA System for Processing FTIR Data; FPGA Coprocessor for Accelerated Classification of Images; SiC JFET Transistor Circuit Model for Extreme Temperature Range; TDR Using Autocorrelation and Varying-Duration Pulses; Update on Development of SiC Multi-Chip Power Modules; Radio Ranging System for Guidance of Approaching Spacecraft; Electromagnetically Clean Solar Arrays; Improved Short-Circuit Protection for Power Cells in Series; Electromagnetically Clean Solar Arrays; Logic Gates Made of N-Channel JFETs and Epitaxial Resistors; Improved Short-Circuit Protection for Power Cells in Series; Communication Limits Due to Photon-Detector Jitter; System for Removing Pollutants from Incinerator Exhaust; Sealing and External Sterilization of a Sample Container; Converting EOS Data from HDF-EOS to netCDF; HDF-EOS 2 and HDF-EOS 5 Compatibility Library; HDF-EOS Web Server; HDF-EOS 5 Validator; XML DTD and Schemas for HDF-EOS; Converting from XML to HDF-EOS; Simulating Attitudes and Trajectories of Multiple Spacecraft; Specialized Color Function for Display of Signed Data; Delivering Alert Messages to Members of a Work Force; Delivering Images for Mars Rover Science Planning; Oxide Fiber Cathode Materials for Rechargeable Lithium Cells; Electrocatalytic Reduction of Carbon Dioxide to Methane; Heterogeneous Superconducting Low-Noise Sensing Coils; Progress toward Making Epoxy/Carbon-Nanotube Composites; Predicting Properties of Unidirectional-Nanofiber Composites; Deployable Crew Quarters; Nonventing, Regenerable, Lightweight Heat Absorber; Miniature High-Force, Long-Stroke SMA Linear Actuators; "Bootstrap" Configuration for Multistage Pulse-Tube Coolers; Reducing Liquid Loss during Ullage Venting in Microgravity; Ka-Band Transponder for Deep-Space Radio Science; Replication of Space-Shuttle Computers in FPGAs and ASICs; Demisable Reaction-Wheel Assembly; Spatial and Temporal Low-Dimensional Models for Fluid Flow; Advanced Land Imager Assessment System; Range Imaging without Moving Parts

NASA SBIR abstracts of 1991 phase 1 projects

The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

Real-time analysis of video signals

Many practical and experimental systems employing image processing techniques have been built by other workers for various applications. Most of these systems are computer-based and very few operate in a real time environment. The objective of this work is to build a microprocessor-based system for video image processing. The system is used in conjunction with an on-line TV camera and processing is carried out in real time. The enormous storage requirement of digitized TV signals and the real time constraint suggest that some simplification of the data must take place prior to any viable processing. Data reduction is attained through the representation of objects by their edges, an approach often adopted for feature extraction in pattern recognition systems. A new technique for edge detection by applying comparison criteria to differentials at adjacent pixels of the video image is developed and implemented as a preprocessing hardware unit. A circuit for the generation of the co-ordinates of edge points is constructed to free the processing computer of this task, allowing it more time for on-line analysis of video signals. Besides the edge detector and co-ordinate generator the hardware built consists of a microprocessor system based on a Texas Instruments T.US 9900 device, a first-in-first-out buffer store and interface circuitry to a TV camera and display devices. All hardware modules and their power supplies are assembled in one unit to provide a standalone instrument. The problem chosen for investigation is analysis of motion in a visual scene. Aspects of motion studied concern the tracking of moving objects with simple geometric shapes and description of their motion. More emphasis is paid to the analysis of human eye movements and measurement of its point-of-regard which has many practical applications in the fields of physiology and psychology. This study provides a basis for the design of a processing unit attached to an oculometer to replace bulky minicomputer-based eye motion analysis systems. Programs are written for storage, analysis and display of results in real time

Vision Sensors and Edge Detection

Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing

A STUDY OF MACHINE VISION IN THE AUTOMOTIVE INDUSTRY

With the growth of industrial automation, it has become increasingly important to validate the quality of every manufactured part during production. Until now, human visual inspection aided with hard tooling or machines have been the primary means to this end, but the speed of today's production lines, the complexity of production equipment and the highest standards of quality to which parts must adhere frequently, make the traditional methods of industrial inspection and control impractical, if not impossible. Subsequently, new solutions have been developed for the monitoring and control of industrial processes, in real­time. One such technology is the area of machine vision. After many years of research and development, computerised vision systems are now leaving the laboratory and are being used successfully in the factory environment. They are both robust and competitively priced as a sensing technique which has now opened up a whole new sector for automation. Machine vision systems are becoming an important integral part of the automotive manufacturing process, with applications ranging from inspection, classification, robot guidance, assembly verification through to process monitoring and control. Although the number of systems in current use is still relatively small, there can be no doubt, given the issues at stake, that the automotive industry will once again lead the way with the implementation of machine vision just as it has done robotic technology. The thesis considered the issue of machine vision and in particular, its deployment within the automotive industry. The thesis has presented work on machine vision for the prospective end-user and not the designer of such systems. It will provide sufficient background about the subject, to separate machine vision promises from reality and permit intelligent decisions regarding machine vision applications to be made. The initial part of the dissertation focussed on the strategic issues affecting the selection of machine vision at the planning stage, such as a listing of the factors to justify investment, the capability of the technology and type of problems that are associated with this relatively new but complex science. Though it is widely accepted that no two industrial machine vision systems are identical, knowledge of the basic fundamentals which underpin the structure of the technology in its application is presented. This work covered a structured description detailing typical hardware components such as camera technology, lighting systems, etc... which form an integral part of an industrial system and discussions regarding the criteria for selection are presented. To complement this work, a further section is specifically devoted to the bewildering array of vision software analysis techniques which are currently available today. A detailed description of the various techniques that are applied to images in order to make use of and understand the data contained within them are discussed and explored. Applications for machine vision fall into two main categories namely robotic guidance and inspection. Obviously within each category there are many further sub­groups. Within this context the latter part of the thesis reviews with a well structured description of several industrial case studies derived from the automotive industry, which illustrate that machine vision is capable of providing real time solutions to manufacturing based problems. In conclusion, despite the limited availability of industrially based machine vision systems, the success of implementation is not always guaranteed, as the technology imposes both technical limitations and introduce new human engineering considerations. By understanding the application and the implications of the technical requirements on both the "staging" and the "image-processing" power required of the machine vision system. The thesis has shown that the most significant elements of a successful application are indeed the lighting, optics, component design, etc... - the "Staging". From the case studies investigated, optimised "staging" has resulted in the need for less computing power in the machine vision system. Inevitably, greater computing power not only requires more time but is generally more expensive. The experience gained from the this project, has demonstrated that machine vision technology is a realistic alternative means of capturing data in real-time. Since the current limitations of the technology are well suited to the delivery process of the quality function within the manufacturing process

Principles, fundamentals, and applications of programmable integrated photonics

[EN] Programmable integrated photonics is an emerging new paradigm that aims at designing common integrated optical hardware resource configurations, capable of implementing an unconstrained variety of functionalities by suitable programming, following a parallel but not identical path to that of integrated electronics in the past two decades of the last century. Programmable integrated photonics is raising considerable interest, as it is driven by the surge of a considerable number of new applications in the fields of telecommunications, quantum information processing, sensing, and neurophotonics, calling for flexible, reconfigurable, low-cost, compact, and low-power-consuming devices that can cooperate with integrated electronic devices to overcome the limitation expected by the demise of Moore¿s Law. Integrated photonic devices exploiting full programmability are expected to scale from application-specific photonic chips (featuring a relatively low number of functionalities) up to very complex application-agnostic complex subsystems much in the same way as field programmable gate arrays and microprocessors operate in electronics. Two main differences need to be considered. First, as opposed to integrated electronics, programmable integrated photonics will carry analog operations over the signals to be processed. Second, the scale of integration density will be several orders of magnitude smaller due to the physical limitations imposed by the wavelength ratio of electrons and light wave photons. The success of programmable integrated photonics will depend on leveraging the properties of integrated photonic devices and, in particular, on research into suitable interconnection hardware architectures that can offer a very high spatial regularity as well as the possibility of independently setting (with a very low power consumption) the interconnection state of each connecting element. Integrated multiport interferometers and waveguide meshes provide regular and periodic geometries, formed by replicating unit elements and cells, respectively. In the case of waveguide meshes, the cells can take the form of a square, hexagon, or triangle, among other configurations. Each side of the cell is formed by two integrated waveguides connected by means of a Mach¿Zehnder interferometer or a tunable directional coupler that can be operated by means of an output control signal as a crossbar switch or as a variable coupler with independent power division ratio and phase shift. In this paper, we provide the basic foundations and principles behind the construction of these complex programmable circuits. We also review some practical aspects that limit the programming and scalability of programmable integrated photonics and provide an overview of some of the most salient applications demonstrated so far.European Research Council; Conselleria d'Educació, Investigació, Cultura i Esport; Ministerio de Ciencia, Innovación y Universidades; European Cooperation in Science and Technology; Horizon 2020 Framework Programme.Pérez-López, D.; Gasulla Mestre, I.; Dasmahapatra, P.; Capmany Francoy, J. (2020). Principles, fundamentals, and applications of programmable integrated photonics. Advances in Optics and Photonics. 12(3):709-786. https://doi.org/10.1364/AOP.387155709786123Lyke, J. C., Christodoulou, C. G., Vera, G. A., & Edwards, A. H. (2015). An Introduction to Reconfigurable Systems. Proceedings of the IEEE, 103(3), 291-317. doi:10.1109/jproc.2015.2397832Kaeslin, H. (2008). Digital Integrated Circuit Design. doi:10.1017/cbo9780511805172Trimberger, S. M. (2015). Three Ages of FPGAs: A Retrospective on the First Thirty Years of FPGA Technology. Proceedings of the IEEE, 103(3), 318-331. doi:10.1109/jproc.2015.2392104Mitola, J. (1995). The software radio architecture. IEEE Communications Magazine, 33(5), 26-38. doi:10.1109/35.393001Nunes, B. A. A., Mendonca, M., Nguyen, X.-N., Obraczka, K., & Turletti, T. (2014). A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks. IEEE Communications Surveys & Tutorials, 16(3), 1617-1634. doi:10.1109/surv.2014.012214.00180Papagianni, C., Leivadeas, A., Papavassiliou, S., Maglaris, V., Cervello-Pastor, C., & Monje, A. (2013). On the optimal allocation of virtual resources in cloud computing networks. IEEE Transactions on Computers, 62(6), 1060-1071. doi:10.1109/tc.2013.31Peruzzo, A., Laing, A., Politi, A., Rudolph, T., & O’Brien, J. L. (2011). Multimode quantum interference of photons in multiport integrated devices. Nature Communications, 2(1). doi:10.1038/ncomms1228Metcalf, B. J., Thomas-Peter, N., Spring, J. B., Kundys, D., Broome, M. A., Humphreys, P. C., … Walmsley, I. A. (2013). Multiphoton quantum interference in a multiport integrated photonic device. Nature Communications, 4(1). doi:10.1038/ncomms2349Miller, D. A. B. (2013). Self-aligning universal beam coupler. Optics Express, 21(5), 6360. doi:10.1364/oe.21.006360Miller, D. A. B. (2013). Self-configuring universal linear optical component [Invited]. Photonics Research, 1(1), 1. doi:10.1364/prj.1.000001Carolan, J., Harrold, C., Sparrow, C., Martín-López, E., Russell, N. J., Silverstone, J. W., … Laing, A. (2015). Universal linear optics. Science, 349(6249), 711-716. doi:10.1126/science.aab3642Harris, N. C., Steinbrecher, G. R., Prabhu, M., Lahini, Y., Mower, J., Bunandar, D., … Englund, D. (2017). Quantum transport simulations in a programmable nanophotonic processor. Nature Photonics, 11(7), 447-452. doi:10.1038/nphoton.2017.95Birth of the programmable optical chip. (2015). Nature Photonics, 10(1), 1-1. doi:10.1038/nphoton.2015.265Zhuang, L., Roeloffzen, C. G. H., Hoekman, M., Boller, K.-J., & Lowery, A. J. (2015). Programmable photonic signal processor chip for radiofrequency applications. Optica, 2(10), 854. doi:10.1364/optica.2.000854Pérez, D., Gasulla, I., Capmany, J., & Soref, R. A. (2016). Reconfigurable lattice mesh designs for programmable photonic processors. Optics Express, 24(11), 12093. doi:10.1364/oe.24.012093Capmany, J., Gasulla, I., & Pérez, D. (2015). The programmable processor. Nature Photonics, 10(1), 6-8. doi:10.1038/nphoton.2015.254Pérez, D., Gasulla, I., Crudgington, L., Thomson, D. J., Khokhar, A. Z., Li, K., … Capmany, J. (2017). Multipurpose silicon photonics signal processor core. Nature Communications, 8(1). doi:10.1038/s41467-017-00714-1Clements, W. R., Humphreys, P. C., Metcalf, B. J., Kolthammer, W. S., & Walsmley, I. A. (2016). Optimal design for universal multiport interferometers. Optica, 3(12), 1460. doi:10.1364/optica.3.001460Perez, D., Gasulla, I., Fraile, F. J., Crudgington, L., Thomson, D. J., Khokhar, A. Z., … Capmany, J. (2017). Silicon Photonics Rectangular Universal Interferometer. Laser & Photonics Reviews, 11(6), 1700219. doi:10.1002/lpor.201700219Shen, Y., Harris, N. C., Skirlo, S., Prabhu, M., Baehr-Jones, T., Hochberg, M., … Soljačić, M. (2017). Deep learning with coherent nanophotonic circuits. Nature Photonics, 11(7), 441-446. doi:10.1038/nphoton.2017.93Ribeiro, A., Ruocco, A., Vanacker, L., & Bogaerts, W. (2016). Demonstration of a 4 × 4-port universal linear circuit. Optica, 3(12), 1348. doi:10.1364/optica.3.001348Annoni, A., Guglielmi, E., Carminati, M., Ferrari, G., Sampietro, M., Miller, D. A., … Morichetti, F. (2017). Unscrambling light—automatically undoing strong mixing between modes. Light: Science & Applications, 6(12), e17110-e17110. doi:10.1038/lsa.2017.110Perez, D., Gasulla, I., & Capmany, J. (2018). Toward Programmable Microwave Photonics Processors. Journal of Lightwave Technology, 36(2), 519-532. doi:10.1109/jlt.2017.2778741Chen, L., Hall, E., Theogarajan, L., & Bowers, J. (2011). Photonic Switching for Data Center Applications. IEEE Photonics Journal, 3(5), 834-844. doi:10.1109/jphot.2011.2166994Miller, D. A. B. (2017). Meshing optics with applications. Nature Photonics, 11(7), 403-404. doi:10.1038/nphoton.2017.104Thomas-Peter, N., Langford, N. K., Datta, A., Zhang, L., Smith, B. J., Spring, J. B., … Walmsley, I. A. (2011). Integrated photonic sensing. New Journal of Physics, 13(5), 055024. doi:10.1088/1367-2630/13/5/055024Smit, M., Leijtens, X., Ambrosius, H., Bente, E., van der Tol, J., Smalbrugge, B., … van Veldhoven, R. (2014). An introduction to InP-based generic integration technology. Semiconductor Science and Technology, 29(8), 083001. doi:10.1088/0268-1242/29/8/083001Coldren, L. A., Nicholes, S. C., Johansson, L., Ristic, S., Guzzon, R. S., Norberg, E. J., & Krishnamachari, U. (2011). High Performance InP-Based Photonic ICs—A Tutorial. Journal of Lightwave Technology, 29(4), 554-570. doi:10.1109/jlt.2010.2100807Kish, F., Nagarajan, R., Welch, D., Evans, P., Rossi, J., Pleumeekers, J., … Joyner, C. (2013). From Visible Light-Emitting Diodes to Large-Scale III–V Photonic Integrated Circuits. Proceedings of the IEEE, 101(10), 2255-2270. doi:10.1109/jproc.2013.2275018Hochberg, M., & Baehr-Jones, T. (2010). Towards fabless silicon photonics. Nature Photonics, 4(8), 492-494. doi:10.1038/nphoton.2010.172Bogaerts, W., Fiers, M., & Dumon, P. (2014). Design Challenges in Silicon Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 20(4), 1-8. doi:10.1109/jstqe.2013.2295882Soref, R. (2006). The Past, Present, and Future of Silicon Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 12(6), 1678-1687. doi:10.1109/jstqe.2006.883151Chrostowski, L., & Hochberg, M. (2015). Silicon Photonics Design. doi:10.1017/cbo9781316084168Heck, M. J. R., Bauters, J. F., Davenport, M. L., Doylend, J. K., Jain, S., Kurczveil, G., … Bowers, J. E. (2013). Hybrid Silicon Photonic Integrated Circuit Technology. IEEE Journal of Selected Topics in Quantum Electronics, 19(4), 6100117-6100117. doi:10.1109/jstqe.2012.2235413Keyvaninia, S., Muneeb, M., Stanković, S., Van Veldhoven, P. J., Van Thourhout, D., & Roelkens, G. (2012). Ultra-thin DVS-BCB adhesive bonding of III-V wafers, dies and multiple dies to a patterned silicon-on-insulator substrate. Optical Materials Express, 3(1), 35. doi:10.1364/ome.3.000035Heideman, R., Hoekman, M., & Schreuder, E. (2012). TriPleX-Based Integrated Optical Ring Resonators for Lab-on-a-Chip and Environmental Detection. IEEE Journal of Selected Topics in Quantum Electronics, 18(5), 1583-1596. doi:10.1109/jstqe.2012.2188382Roeloffzen, C. G. H., Zhuang, L., Taddei, C., Leinse, A., Heideman, R. G., van Dijk, P. W. L., … Boller, K.-J. (2013). Silicon nitride microwave photonic circuits. Optics Express, 21(19), 22937. doi:10.1364/oe.21.022937Corbett, B., Loi, R., Zhou, W., Liu, D., & Ma, Z. (2017). Transfer print techniques for heterogeneous integration of photonic components. Progress in Quantum Electronics, 52, 1-17. doi:10.1016/j.pquantelec.2017.01.001Van der Tol, J. J. G. M., Jiao, Y., Shen, L., Millan-Mejia, A., Pogoretskii, V., van Engelen, J. P., & Smit, M. K. (2018). Indium Phosphide Integrated Photonics in Membranes. IEEE Journal of Selected Topics in Quantum Electronics, 24(1), 1-9. doi:10.1109/jstqe.2017.2772786Bachmann, M., Besse, P. A., & Melchior, H. (1994). General self-imaging properties in N × N multimode interference couplers including phase relations. Applied Optics, 33(18), 3905. doi:10.1364/ao.33.003905Soldano, L. B., & Pennings, E. C. M. (1995). Optical multi-mode interference devices based on self-imaging: principles and applications. Journal of Lightwave Technology, 13(4), 615-627. doi:10.1109/50.372474Madsen, C. K., & Zhao, J. H. (1999). Optical Filter Design and Analysis. Wiley Series in Microwave and Optical Engineering. doi:10.1002/0471213756Desurvire, E. (2009). Classical and Quantum Information Theory. doi:10.1017/cbo9780511803758Knill, E., Laflamme, R., & Milburn, G. J. (2001). A scheme for efficient quantum computation with linear optics. Nature, 409(6816), 46-52. doi:10.1038/35051009Capmany, J., & Pérez, D. (2020). Programmable Integrated Photonics. doi:10.1093/oso/9780198844402.001.0001Spagnolo, N., Vitelli, C., Bentivegna, M., Brod, D. J., Crespi, A., Flamini, F., … Sciarrino, F. (2014). Experimental validation of photonic boson sampling. Nature Photonics, 8(8), 615-620. doi:10.1038/nphoton.2014.135Mennea, P. L., Clements, W. R., Smith, D. H., Gates, J. C., Metcalf, B. J., Bannerman, R. H. S., … Smith, P. G. R. (2018). Modular linear optical circuits. Optica, 5(9), 1087. doi:10.1364/optica.5.001087Perez-Lopez, D., Sanchez, E., & Capmany, J. (2018). Programmable True Time Delay Lines Using Integrated Waveguide Meshes. Journal of Lightwave Technology, 36(19), 4591-4601. doi:10.1109/jlt.2018.2831008Pérez-López, D., Gutierrez, A. M., Sánchez, E., DasMahapatra, P., & Capmany, J. (2019). Integrated photonic tunable basic units using dual-drive directional couplers. Optics Express, 27(26), 38071. doi:10.1364/oe.27.038071Jinguji, K., & Kawachi, M. (1995). Synthesis of coherent two-port lattice-form optical delay-line circuit. Journal of Lightwave Technology, 13(1), 73-82. doi:10.1109/50.350643Mookherjea, S., & Yariv, A. (2002). Coupled resonator optical waveguides. IEEE Journal of Selected Topics in Quantum Electronics, 8(3), 448-456. doi:10.1109/jstqe.2002.1016347Heebner, J. E., Chak, P., Pereira, S., Sipe, J. E., & Boyd, R. W. (2004). Distributed and localized feedback in microresonator sequences for linear and nonlinear optics. Journal of the Optical Society of America B, 21(10), 1818. doi:10.1364/josab.21.001818Fandiño, J. S., Muñoz, P., Doménech, D., & Capmany, J. (2016). A monolithic integrated photonic microwave filter. Nature Photonics, 11(2), 124-129. doi:10.1038/nphoton.2016.233Miller, D. A. B. (2012). All linear optical devices are mode converters. Optics Express, 20(21), 23985. doi:10.1364/oe.20.023985Brown, S. D., Francis, R. J., Rose, J., & Vranesic, Z. G. (1992). Field-Programmable Gate Arrays. doi:10.1007/978-1-4615-3572-0Lee, E. K. F., & Gulak, P. G. (1992). Field programmable analogue array based on MOSFET transconductors. Electronics Letters, 28(1), 28-29. doi:10.1049/el:19920017Lee, E. K. F., & Gulak, P. G. (s. f.). A transconductor-based field-programmable analog array. Proceedings ISSCC ’95 - International Solid-State Circuits Conference. doi:10.1109/isscc.1995.535521Pérez, D., Gasulla, I., & Capmany, J. (2018). Field-programmable photonic arrays. Optics Express, 26(21), 27265. doi:10.1364/oe.26.027265Zheng, D., Doménech, J. D., Pan, W., Zou, X., Yan, L., & Pérez, D. (2019). Low-loss broadband 5  ×  5 non-blocking Si3N4 optical switch matrix. Optics Letters, 44(11), 2629. doi:10.1364/ol.44.002629Densmore, A., Janz, S., Ma, R., Schmid, J. H., Xu, D.-X., Delâge, A., … Cheben, P. (2009). Compact and low power thermo-optic switch using folded silicon waveguides. Optics Express, 17(13), 10457. doi:10.1364/oe.17.010457Song, M., Long, C. M., Wu, R., Seo, D., Leaird, D. E., & Weiner, A. M. (2011). Reconfigurable and Tunable Flat-Top Microwave Photonic Filters Utilizing Optical Frequency Combs. IEEE Photonics Technology Letters, 23(21), 1618-1620. doi:10.1109/lpt.2011.2165209Rudé, M., Pello, J., Simpson, R. E., Osmond, J., Roelkens, G., van der Tol, J. J. G. M., & Pruneri, V. (2013). Optical switching at 1.55 μm in silicon racetrack resonators using phase change materials. Applied Physics Letters, 103(14), 141119. doi:10.1063/1.4824714Zheng, J., Khanolkar, A., Xu, P., Colburn, S., Deshmukh, S., Myers, J., … Majumdar, A. (2018). GST-on-silicon hybrid nanophotonic integrated circuits: a non-volatile quasi-continuously reprogrammable platform. Optical Materials Express, 8(6), 1551. doi:10.1364/ome.8.001551Edinger, P., Errando-Herranz, C., & Gylfason, K. B. (2019). Low-Loss MEMS Phase Shifter for Large Scale Reconfigurable Silicon Photonics. 2019 IEEE 32nd International Conference on Micro Electro Mechanical Systems (MEMS). doi:10.1109/memsys.2019.8870616Carroll, L., Lee, J.-S., Scarcella, C., Gradkowski, K., Duperron, M., Lu, H., … O’Brien, P. (2016). Photonic Packaging: Transforming Silicon Photonic Integrated Circuits into Photonic Devices. Applied Sciences, 6(12), 426. doi:10.3390/app6120426Bahadori, M., Gazman, A., Janosik, N., Rumley, S., Zhu, Z., Polster, R., … Bergman, K. (2018). Thermal Rectification of Integrated Microheaters for Microring Resonators in Silicon Photonics Platform. Journal of Lightwave Technology, 36(3), 773-788. doi:10.1109/jlt.2017.2781131Cocorullo, G., Della Corte, F. G., Rendina, I., & Sarro, P. M. (1998). Thermo-optic effect exploitation in silicon microstructures. Sensors and Actuators A: Physical, 71(1-2), 19-26. doi:10.1016/s0924-4247(98)00168-xZecevic, N., Hofbauer, M., & Zimmermann, H. (2015). Integrated Pulsewidth Modulation Control for a Scalable Optical Switch Matrix. IEEE Photonics Journal, 7(6), 1-7. doi:10.1109/jphot.2015.2506153Seok, T. J., Quack, N., Han, S., & Wu, M. C. (2015). 50×50 Digital Silicon Photonic Switches with MEMS-Actuated Adiabatic Couplers. Optical Fiber Communication Conference. doi:10.1364/ofc.2015.m2b.4Zortman, W. A., Trotter, D. C., & Watts, M. R. (2010). Silicon photonics manufacturing. Optics Express, 18(23), 23598. doi:10.1364/oe.18.023598Mower, J., Harris, N. C., Steinbrecher, G. R., Lahini, Y., & Englund, D. (2015). High-fidelity quantum state evolution in imperfect photonic integrated circuits. Physical Review A, 92(3). doi:10.1103/physreva.92.032322Pérez, D., & Capmany, J. (2019). Scalable analysis for arbitrary photonic integrated waveguide meshes. Optica, 6(1), 19. doi:10.1364/optica.6.000019Oton, C. J., Manganelli, C., Bontempi, F., Fournier, M., Fowler, D., & Kopp, C. (2016). Silicon photonic waveguide metrology using Mach-Zehnder interferometers. Optics Express, 24(6), 6265. doi:10.1364/oe.24.006265Chen, X., & Bogaerts, W. (2019). A Graph-based Design and Programming Strategy for Reconfigurable Photonic Circuits. 2019 IEEE Photonics Society Summer Topical Meeting Series (SUM). doi:10.1109/phosst.2019.8795068Zibar, D., Wymeersch, H., & Lyubomirsky, I. (2017). Machine learning under the spotlight. Nature Photonics, 11(12), 749-751. doi:10.1038/s41566-017-0058-3Lopez, D. P. (2020). Programmable Integrated Silicon Photonics Waveguide Meshes: Optimized Designs and Control Algorithms. IEEE Journal of Selected Topics in Quantum Electronics, 26(2), 1-12. doi:10.1109/jstqe.2019.2948048Harris, N. C., Bunandar, D., Pant, M., Steinbrecher, G. R., Mower, J., Prabhu, M., … Englund, D. (2016). Large-scale quantum photonic circuits in silicon. Nanophotonics, 5(3), 456-468. doi:10.1515/nanoph-2015-0146Spring, J. B., Metcalf, B. J., Humphreys, P. C., Kolthammer, W. S., Jin, X.-M., Barbieri, M., … Walmsley, I. A. (2012). Boson Sampling on a Photonic Chip. Science, 339(6121), 798-801. doi:10.1126/science.1231692O’Brien, J. L., Furusawa, A., & Vučković, J. (2009). Photonic quantum technologies. Nature Photonics, 3(12), 687-695. doi:10.1038/nphoton.2009.229Kok, P., Munro, W. J., Nemoto, K., Ralph, T. C., Dowling, J. P., & Milburn, G. J. (2007). Linear optical quantum computing with photonic qubits. Reviews of Modern Physics, 79(1), 135-174. doi:10.1103/revmodphys.79.135Politi, A., Cryan, M. J., Rarity, J. G., Yu, S., & O’Brien, J. L. (2008). Silica-on-Silicon Waveguide Quantum Circuits. Science, 320(5876), 646-649. doi:10.1126/science.1155441Politi, A., Matthews, J., Thompson, M. G., & O’Brien, J. L. (2009). Integrated Quantum Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 15(6), 1673-1684. doi:10.1109/jstqe.2009.2026060Thompson, M. G., Politi, A., Matthews, J. C. F., & O’Brien, J. L. (2011). Integrated waveguide circuits for optical quantum computing. IET Circuits, Devices & Systems, 5(2), 94. doi:10.1049/iet-cds.2010.0108Silverstone, J. W., Bonneau, D., O’Brien, J. L., & Thompson, M. G. (2016). Silicon Quantum Photonics. IEEE Journal of Selected Topics in Quantum Electronics, 22(6), 390-402. doi:10.1109/jstqe.2016.2573218Poot, M., Schuck, C., Ma, X., Guo, X., & Tang, H. X. (2016). Design and characterization of integrated components for SiN photonic quantum circuits. Optics Express, 24(7), 6843. doi:10.1364/oe.24.006843Saleh, M. F., Di Giuseppe, G., Saleh, B. E. A., & Teich, M. C. (2010). Modal and polarization qubits in Ti:LiNbO_3 photonic circuits for a universal quantum logic gate. Optics Express, 18(19), 20475. doi:10.1364/oe.18.020475Harris, N. C., Carolan, J., Bunandar, D., Prabhu, M., Hochberg, M., Baehr-Jones, T., … Englund, D. (2018). Linear programmable nanophotonic processors. Optica, 5(12), 1623. doi:10.1364/optica.5.001623Qiang, X., Zhou, X., Wang, J., Wilkes, C. M., Loke, T., O’Gara, S., … Matthews, J. C. F. (2018). Large-scale silicon quantum photonics implementing arbitrary two-qubit processing. Nature Photonics, 12(9), 534-539. doi:10.1038/s41566-018-0236-yLee, B. G., & Dupuis, N. (2019). Silicon Photonic Switch Fabrics: Technology and Architecture. Journal of Lightwave Technology, 37(1), 6-20. doi:10.1109/jlt.2018.2876828Cheng, Q., Rumley, S., Bahadori, M., & Bergman, K. (2018). Photonic switching in high performance datacenters [Invited]. Optics Express, 26(12), 16022. doi:10.1364/oe.26.016022Wonfor, A., Wang, H., Penty, R. V., & White, I. H. (2011). Large Port Count High-Speed Optical Switch Fabric for Use Within Datacenters [Invited]. Journal of Optical Communications and Networking, 3(8), A32. doi:10.1364/jocn.3.000a32Hamamoto, K., Anan, T., Komatsu, K., Sugimoto, M., & Mito, I. (1992). First 8×8 semiconductor optical matrix switches using GaAs/AlGaAs electro-optic guided-wave directional couplers. Electronics Letters, 28(5), 441. doi:10.1049/el:19920278Van Campenhout, J., Green, W. M., Assefa, S., & Vlasov, Y. A. (2009). Low-power, 2×2 silicon electro-optic switch with 110-nm bandwidth for broadband reconfigurable optical networks. Optics Express, 17(26), 24020. doi:10.1364/oe.17.024020Dupuis, N., Lee, B. G., Rylyakov, A. V., Kuchta, D. M., Baks, C. W., Orcutt, J. S., … Schow, C. L. (2015). D

COBE's search for structure in the Big Bang

The launch of Cosmic Background Explorer (COBE) and the definition of Earth Observing System (EOS) are two of the major events at NASA-Goddard. The three experiments contained in COBE (Differential Microwave Radiometer (DMR), Far Infrared Absolute Spectrophotometer (FIRAS), and Diffuse Infrared Background Experiment (DIRBE)) are very important in measuring the big bang. DMR measures the isotropy of the cosmic background (direction of the radiation). FIRAS looks at the spectrum over the whole sky, searching for deviations, and DIRBE operates in the infrared part of the spectrum gathering evidence of the earliest galaxy formation. By special techniques, the radiation coming from the solar system will be distinguished from that of extragalactic origin. Unique graphics will be used to represent the temperature of the emitting material. A cosmic event will be modeled of such importance that it will affect cosmological theory for generations to come. EOS will monitor changes in the Earth's geophysics during a whole solar color cycle

VLSI Design

This book provides some recent advances in design nanometer VLSI chips. The selected topics try to present some open problems and challenges with important topics ranging from design tools, new post-silicon devices, GPU-based parallel computing, emerging 3D integration, and antenna design. The book consists of two parts, with chapters such as: VLSI design for multi-sensor smart systems on a chip, Three-dimensional integrated circuits design for thousand-core processors, Parallel symbolic analysis of large analog circuits on GPU platforms, Algorithms for CAD tools VLSI design, A multilevel memetic algorithm for large SAT-encoded problems, etc

Dynamically reconfigurable architecture for embedded computer vision systems

The objective of this research work is to design, develop and implement a new architecture which integrates on the same chip all the processing levels of a complete Computer Vision system, so that the execution is efficient without compromising the power consumption while keeping a reduced cost. For this purpose, an analysis and classification of different mathematical operations and algorithms commonly used in Computer Vision are carried out, as well as a in-depth review of the image processing capabilities of current-generation hardware devices. This permits to determine the requirements and the key aspects for an efficient architecture. A representative set of algorithms is employed as benchmark to evaluate the proposed architecture, which is implemented on an FPGA-based system-on-chip. Finally, the prototype is compared to other related approaches in order to determine its advantages and weaknesses