Designing Resilient Manufacturing Systems In the Presence of Change

Economic and technical changes force manufacturers to redesign and enhance their operational systems. The implications of such changes within a complex system such as manufacturing and the supply chain can be very challenging. In particular, where the number of system elements and their connections result in a high level of complexity, the potential effects of a change can be expensive concerning the delivery time and cost targets, as a change to one part or element of a design requires additional changes throughout the system. Companies need to understand the characteristics of their manufacturing systems that make them resilient to change. Considered from a system perspective, the structures of the system, and its elements and connections, contribute greatly to the characteristics and behavior of the system and hence potential resilience. A change prediction method can help to analyse the change properties and improve complex systems by focusing on the underlying structural elements and dependencies. This thesis proposes a novel system change method that can enable the review of the current manufacturing system and understand how to design a more robust or adaptable system that addresses resilience. This method is a combination of matrix-based approaches and methods to assess the interaction between elements of the product and its manufacturing process in order to understand the risk of changes propagating through the system. Risk assessment across layers of a system can give valuable insight into how an element change interacts within the system. The goal of this thesis is to contribute to gaining a fundamental understanding of manufacturing systems resilience by developing a method to evaluate capabilities of changes, performance robustness or adaptability, and achieving high resilience.Universal Oil Products (a Honeywell Company); Laing O’Rourk

Trading Off between Flexibility and Product Platform Constraints for Effective Technology Introduction

Developing product platforms is an established method of reducing internal variety costs while delivering variety to customers. \ua0A critical aspect of a platform, that is expected to be used and extended for many years, is the ability to introduce new technologies and solutions effectively. Since these technological integration endeavours may challenge platform constraints, it is necessary to be able to assess the trade-off between their expected value and cost of realisation. New technologies can be integrated more easily into products derived from product platforms if they are flexible. However, introducing flexibility early can be wasteful, both in terms of resources used for the development of the platforms and the suboptimal design of products derived from the platform. In this study, a review of the existing literature is conducted and several case studies in the automotive sector are performed. Both technical and organizational factors are found to limit platform flexibility. This research supports the idea that the flexibility to integrate technology into existing platforms is a valuable property. Consequently, it is important to foster the ability to more objectively assess the value of proposed technology changes in organisations relying on product and production platforms.Finally, this thesis proposes a model-based methodology to trade off the flexibility of a product platform with the lifetime value it can deliver to its stakeholders. The methodology utilizes technology roadmaps, architectural modelling, value-driven design, and model-based simulations to establish the bandwidth of a product platform. As such, the constraints that the platform introduces for future derived products are balanced against valuable flexibility, which is defined as the flexibility of the platform to allow for more alternative designs, including using new technologies, of higher value in future products. The findings of this thesis have implications for the research of product platforms and their development, as well as for practitioners making decisions about product platforms with consideration to the uncertainty around the ways they will be used and upgraded in the future

SPEM 2.0 extension for pervasive information systems

Pervasive computing is a research field of computing technology that aims to achieve a new computing paradigm. In this paradigm, the physical environment has a high degree of pervasiveness and availability of computers and other information technology (IT) devices, usually with communication capabilities. Pervasive Information Systems (PIS), composed by these kinds of devices, bring issues that challenge software development for them. Model-Driven Development (MDD), strongly focusing and relying on models, has the potential to allow: the use of concepts closer to the domain and the reduction of semantic gaps; higher automation and lower dependency to technological changes; higher capture of expert knowledge and reuse; an overall increased productivity. Along with the focus and use of models, software development processes are fundamental to efficient development efforts of successful software systems. For the description of processes, Software & Systems Process Engineering Meta-Model Specification (SPEM) is the current standard specification published by the Object Management Group (OMG). This paper presents an extension to SPEM (version 2.0) Base Plug-In Profile that includes stereotypes needed to support a suitable structural process organization for MDD approaches aiming to develop software for PIS. A case study is provided to evaluate the applicability of the extension

Maintaining Requirements Using Web Usage Data

AbstractThe use of the World Wide Web has had a huge growth and there is a greater variety of web applications with an increasing importance in society and in supporting the development to all kinds of business. Often, most of websites are providing support services that must be maintained and improved over time. This maintenance and upgrade can be difficult because frequently the requirements are no longer actual and/or often not even exist documented. Websites are increasingly monitoring usage data, and this type of information is increasingly abundant. Analyzing the usage of the websites can help identify improvements and help to maintain the website and its software requirements. This paper presents REQAnalytics, a recommender system that collects the information about the usage of a website, processes it and generates recommendations to the requirements specification of the website. This research work also presents an experimental evaluation of a case study based on an online newspaper website. The results showed that REQAnalytics can produce reports in a language closer to the business, identify most and less used functionalities, requirements that can be split in two or more requirements and give support to the maintenance of requirements of the website being analyzed

Engineering Resilient Collective Adaptive Systems by Self-Stabilisation

Collective adaptive systems are an emerging class of networked computational systems, particularly suited in application domains such as smart cities, complex sensor networks, and the Internet of Things. These systems tend to feature large scale, heterogeneity of communication model (including opportunistic peer-to-peer wireless interaction), and require inherent self-adaptiveness properties to address unforeseen changes in operating conditions. In this context, it is extremely difficult (if not seemingly intractable) to engineer reusable pieces of distributed behaviour so as to make them provably correct and smoothly composable. Building on the field calculus, a computational model (and associated toolchain) capturing the notion of aggregate network-level computation, we address this problem with an engineering methodology coupling formal theory and computer simulation. On the one hand, functional properties are addressed by identifying the largest-to-date field calculus fragment generating self-stabilising behaviour, guaranteed to eventually attain a correct and stable final state despite any transient perturbation in state or topology, and including highly reusable building blocks for information spreading, aggregation, and time evolution. On the other hand, dynamical properties are addressed by simulation, empirically evaluating the different performances that can be obtained by switching between implementations of building blocks with provably equivalent functional properties. Overall, our methodology sheds light on how to identify core building blocks of collective behaviour, and how to select implementations that improve system performance while leaving overall system function and resiliency properties unchanged.Comment: To appear on ACM Transactions on Modeling and Computer Simulatio

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

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