2,163 research outputs found

    Back action of graphene charge detectors on graphene and carbon nanotube quantum dots

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    We report on devices based on graphene charge detectors (CDs) capacitively coupled to graphene and carbon nanotube quantum dots (QDs). We focus on back action effects of the CD on the probed QD. A strong influence of the bias voltage applied to the CD on the current through the QD is observed. Depending on the charge state of the QD the current through the QD can either strongly increase or completely reverse as a response to the applied voltage on the CD. To describe the observed behavior we employ two simple models based on single electron transport in QDs with asymmetrically broadened energy distributions of the source and the drain leads. The models successfully explain the back action effects. The extracted distribution broadening shows a linear dependency on the bias voltage applied to the CD. We discuss possible mechanisms mediating the energy transfer between the CD and QD and give an explanation for the origin of the observed asymmetry.Comment: 6 pages, 4 figure

    Programmable photonics : an opportunity for an accessible large-volume PIC ecosystem

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    We look at the opportunities presented by the new concepts of generic programmable photonic integrated circuits (PIC) to deploy photonics on a larger scale. Programmable PICs consist of waveguide meshes of tunable couplers and phase shifters that can be reconfigured in software to define diverse functions and arbitrary connectivity between the input and output ports. Off-the-shelf programmable PICs can dramatically shorten the development time and deployment costs of new photonic products, as they bypass the design-fabrication cycle of a custom PIC. These chips, which actually consist of an entire technology stack of photonics, electronics packaging and software, can potentially be manufactured cheaper and in larger volumes than application-specific PICs. We look into the technology requirements of these generic programmable PICs and discuss the economy of scale. Finally, we make a qualitative analysis of the possible application spaces where generic programmable PICs can play an enabling role, especially to companies who do not have an in-depth background in PIC technology

    Search for a Metallic Dangling-Bond Wire on nn-doped H-passivated Semiconductor Surfaces

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    We have theoretically investigated the electronic properties of neutral and nn-doped dangling bond (DB) quasi-one-dimensional structures (lines) in the Si(001):H and Ge(001):H substrates with the aim of identifying atomic-scale interconnects exhibiting metallic conduction for use in on-surface circuitry. Whether neutral or doped, DB lines are prone to suffer geometrical distortions or have magnetic ground-states that render them semiconducting. However, from our study we have identified one exception -- a dimer row fully stripped of hydrogen passivation. Such a DB-dimer line shows an electronic band structure which is remarkably insensitive to the doping level and, thus, it is possible to manipulate the position of the Fermi level, moving it away from the gap. Transport calculations demonstrate that the metallic conduction in the DB-dimer line can survive thermally induced disorder, but is more sensitive to imperfect patterning. In conclusion, the DB-dimer line shows remarkable stability to doping and could serve as a one-dimensional metallic conductor on nn-doped samples.Comment: 8 pages, 5 figure

    Roadmap on semiconductor-cell biointerfaces.

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    This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world

    Ancient and historical systems

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    21st Century Nanostructured Materials

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    Nanostructured materials (NMs) are attracting interest as low-dimensional materials in the high-tech era of the 21st century. Recently, nanomaterials have experienced breakthroughs in synthesis and industrial and biomedical applications. This book presents recent achievements related to NMs such as graphene, carbon nanotubes, plasmonic materials, metal nanowires, metal oxides, nanoparticles, metamaterials, nanofibers, and nanocomposites, along with their physical and chemical aspects. Additionally, the book discusses the potential uses of these nanomaterials in photodetectors, transistors, quantum technology, chemical sensors, energy storage, silk fibroin, composites, drug delivery, tissue engineering, and sustainable agriculture and environmental applications

    Programmable photonic circuits

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    [EN] The growing maturity of integrated photonic technology makes it possible to build increasingly large and complex photonic circuits on the surface of a chip. Today, most of these circuits are designed for a specific application, but the increase in complexity has introduced a generation of photonic circuits that can be programmed using software for a wide variety of functions through a mesh of on-chip waveguides, tunable beam couplers and optical phase shifters. Here we discuss the state of this emerging technology, including recent developments in photonic building blocks and circuit architectures, as well as electronic control and programming strategies. We cover possible applications in linear matrix operations, quantum information processing and microwave photonics, and examine how these generic chips can accelerate the development of future photonic circuits by providing a higher-level platform for prototyping novel optical functionalities without the need for custom chip fabricationBogaerts, W.; Pérez-López, D.; Capmany Francoy, J.; Miller, DAB.; Poon, J.; Englund, D.; Morichetti, F.... (2020). Programmable photonic circuits. Nature. 586(7828):207-216. https://doi.org/10.1038/s41586-020-2764-0S2072165867828Chen, X. et al. The emergence of silicon photonics as a flexible technology platform. Proc. IEEE 106, 2101–2116 (2018).Smit, M., Williams, K. & van der Tol, J. Past, present, and future of InP-based photonic integration. APL Photonics 4, 050901 (2019).Capmany, J. & Perez, D. Programmable Integrated Photonics (Oxford Univ. Press, 2020). The first book on the subject of programmable photonics gives a detailed overview of the fundamental principles, architectures and potential applications.Marpaung, D., Yao, J. & Capmany, J. Integrated microwave photonics. Nat. Photon. 13, 80–90 (2019).Zhuang, L., Roeloffzen, C. G. H., Hoekman, M., Boller, K. & Lowery, A. J. Programmable photonic signal processor chip for radiofrequency applications. Optica 2, 854–859 (2015).Shen, Y. et al. Deep learning with coherent nanophotonic circuits. Nat. Photon. 11, 441–446 (2017).Harris, N. C. et al. Linear programmable nanophotonic processors. Optica 5, 1623–1631 (2018). One of the largest-scale demonstrations of a programmable photonic circuit, using a silicon photonics forward-only mesh that maps 26 input modes onto 26 output modes, for use in deep learning and quantum information processing.Miller, D. A. B. Self-configuring universal linear optical component. Photon. Res. 1, 1–15 (2013). This foundational paper in the field of programmable photonics is the first to bring together waveguide meshes with self-configuration algorithms that require no active computation, including the concept of the self-aligning beam coupler.Carolan, J. et al. Universal linear optics. Science 349, 711–716 (2015).Harris, N. C. et al. Large-scale quantum photonic circuits in silicon. Nanophotonics 5, 456–468 (2016).Notaros, J. et al. Programmable dispersion on a photonic integrated circuit for classical and quantum applications. Opt. Express 25, 21275–21285 (2017).Clements, W. R., Humphreys, P. C., Metcalf, B. J., Kolthammer, W. S. & Walmsley, I. A. An optimal design for universal multiport interferometers. Optica 12, 1460–1465 (2016).Perez-Lopez, D. Programmable integrated silicon photonics waveguide meshes: optimized designs and control algorithms. IEEE J. Sel. Top. Quantum Electron. 26, 8301312 (2020).Ribeiro, A., Ruocco, A., Vanacker, L. & Bogaerts, W. Demonstration of a 4×4-port universal linear circuit. Optica 3, 1348–1357 (2016).Harris, N. C. et al. Quantum transport simulations in a programmable nanophotonic processor. Nat. Photon. 11, 447–452 (2017).Mennea, P. L. et al. Modular linear optical circuits. Optica 5, 1087–1090 (2018).Taballione, C. et al. 8×8 programmable quantum photonic processor based on silicon nitride waveguides. In Frontiers in Optics, JTu3A.58 (Optical Society of America, 2018). A demonstration of an 8 × 8 forward-only programmable linear circuit in silicon nitride that benefits from the notably low optical losses of this material and is therefore attractive for linear quantum operations on single photons.Perez, D. et al. Silicon photonics rectangular universal interferometer. Laser Photonics Rev. 11, 1700219 (2017).Xie, Y. et al. Programmable optical processor chips: toward photonic RF filters with DSP-level flexibility and MHz-band selectivity. Nanophotonics 7, 421–454 (2017). A comprehensive overview of the various ways in which a programmable photonic circuit can be used to process microwave signals, and on how this type of circuit is transitioning from custom ASPICs to generic programmable PICs.Hall, T. J. & Hasan, M. Universal discrete Fourier optics RF photonic integrated circuit architecture. Opt. Express 24, 7600–7610 (2016).Dyakonov, I. V. et al. Reconfigurable photonics on a glass chip. Phys. Rev. Appl. 10, 044048 (2018).Shokraneh, F., Geoffroy-Gagnon, S., Nezami, M. S. & Liboiron-Ladouceur, O. A single layer neural network implemented by a 4×4 MZI-based optical processor. IEEE Photonics J. 11, 4501612 (2019).Lu, L., Zhou, L. & Chen, J. Programmable SCOW mesh silicon photonic processor for linear unitary operator. Micromachines 10, 646 (2019).Qiang, X. et al. Large-scale silicon quantum photonics implementing arbitrary two-qubit processing. Nat. Photon. 12, 534–539 (2018).Wang, J. et al. Multidimensional quantum entanglement with large-scale integrated optics. Science 360, 285–291 (2018).Schaeff, C., Polster, R., Huber, M., Ramelow, S. & Zeilinger, A. Experimental access to higher-dimensional entangled quantum systems using integrated optics. Optica 2, 523–529 (2015).Shadbolt, P. J. et al. Generating, manipulating and measuring entanglement and mixture with a reconfigurable photonic circuit. Nat. Photon. 6, 45–49 (2012).Miller, D. A. B. Waves, modes, communications, and optics: a tutorial. Adv. Opt. Photonics 11, 679 (2019).Miller, D. A. B. Self-aligning universal beam coupler. Opt. Express 21, 6360–6370 (2013).Miller, D. A. B. Perfect optics with imperfect components. Optica 2, 747–750 (2015).Annoni, A. et al. Unscrambling light—automatically undoing strong mixing between modes. Light Sci. Appl. 6, e17110 (2017). Early demonstration of a forward-only programmable mesh used to unmix different modes in a waveguide, implementing integrated transparent detectors that measure the light intensity in the waveguide without inducing additional optical loss.Pai, S. et al. Parallel programming of an arbitrary feedforward photonic network. IEEE J. Sel. Top. Quantum Electron. 25, 6100813 (2020).Reck, M., Zeilinger, A., Bernstein, H. J. & Bertani, P. Experimental realization of any discrete unitary operator. Phys. Rev. Lett. 73, 58–61 (1994).Wang, M., Alves, A. R., Xing, Y. & Bogaerts, W. Tolerant, broadband tunable 2×2 coupler circuit. Opt. Express 28, 5555–5566 (2020).Pérez-López, D., Gutierrez, A. M., Sánchez, E., DasMahapatra, P. & Capmany, J. Integrated photonic tunable basic units using dual-drive directional couplers. Opt. Express 27, 38071 (2019).Choutagunta, K., Roberts, I., Miller, D. A. B. & Kahn, J. M. Adapting Mach–Zehnder mesh equalizers in direct-detection mode-division-multiplexed links. J. Light. Technol. 38, 723–735 (2020).Miller, D. A. B. Analyzing and generating multimode optical fields using self-configuring networks. Optica 7, 794–801 (2020).Morizur, J.-F. et al. Programmable unitary spatial mode manipulation. J. Opt. Soc. Am. A 27, 2524 (2010).Labroille, G. et al. Efficient and mode selective spatial mode multiplexer based on multi-plane light conversion. Opt. Express 22, 15599–15607 (2014).Tanomura, R., Tang, R., Ghosh, S., Tanemura, T. & Nakano, T. Robust integrated optical unitary converter using multiport directional couplers. J. Light. Technol. 38, 60–66 (2020).Miller, D. A. B. Setting up meshes of interferometers – reversed local light interference method. Opt. Express 25, 29233 (2017).Li, H. W. et al. Calibration and high fidelity measurement of a quantum photonic chip. New J. Phys. 15, 063017 (2013).Cong, G. et al. Arbitrary reconfiguration of universal silicon photonic circuits by bacteria foraging algorithm to achieve reconfigurable photonic digital-to-analog conversion. Opt. Express 27, 24914 (2019).Pérez, D. et al. Multipurpose silicon photonics signal processor core. Nat. Commun. 8, 1–9 (2017). The first experimental demonstration of a recirculating waveguide mesh with seven unit cells that can be programmed to perform more than a hundred different functions.Pérez, D., Gasulla, I. & Capmany, J. Field-programmable photonic arrays. Opt. Express 26, 27265 (2018).Rahim, A., Spuesens, T., Baets, R. & Bogaerts, W. Open-access silicon photonics: current status and emerging initiatives. Proc. IEEE 106, 2313–2330 (2018).Munoz, P. et al. Foundry developments toward silicon nitride photonics from visible to the mid-infrared. IEEE J. Sel. Top. Quantum Electron. 25, 8200513 (2019).Teng, M. et al. Miniaturized silicon photonics devices for integrated optical signal processors. J. Light. Technol. 38, 6–17 (2020).Sacher, W. D. et al. Monolithically integrated multilayer silicon nitride-on-silicon waveguide platforms for 3-D photonic circuits and devices. Proc. IEEE 106, 2232–2245 (2018).Baudot, C. et al. Developments in 300mm silicon photonics using traditional CMOS fabrication methods and materials. In 2017 IEEE Int. Electron Devices Meeting, 765–768 (IEEE, 2017).Fahrenkopf, N. M. et al. The AIM photonics MPW: a highly accessible cutting edge technology for rapid prototyping of photonic integrated circuits. IEEE J. Sel. Top. Quantum Electron. 25, 8201406 (2019).Chiles, J. et al. Multi-planar amorphous silicon photonics with compact interplanar couplers, cross talk mitigation, and low crossing loss. APL Photonics 2, 116101 (2017).Van Campenhout, J., Green, W. M. J., Assefa, S. & Vlasov, Y. A. Integrated NiSi waveguide heaters for CMOS-compatible silicon thermo-optic devices. Opt. Lett. 35, 1013–1015 (2010).Masood, A. et al. Comparison of heater architectures for thermal control of silicon photonic circuits. In Proc. 10th Int. Conference on Group IV Photonics 83–84 (IEEE, 2013).Milanizadeh, M., Aguiar, D., Melloni, A. & Morichetti, F. Canceling thermal cross-talk effects in photonic integrated circuits. J. Light. Technol. 37, 1325–1332 (2019).Soref, R. A. & Bennett, B. R. Electrooptical effects in silicon. IEEE J. Quantum Electron. 23, 123–129 (1987).Reed, G. T., Mashanovich, G., Gardes, F. Y. & Thomson, D. J. Silicon optical modulators. Nat. Photon. 4, 518–526 (2010); corrigendum 4, 660 (2010).Memon, F. A. et al. Silicon oxycarbide platform for integrated photonics. J. Light. Technol. 38, 784–791 (2020).Jin, W., Polcawich, R. G., Morton, P. A. & Bowers, J. E. Piezoelectrically tuned silicon nitride ring resonator. Opt. Express 26, 3174–3187 (2018).Hosseini, N. et al. Stress-optic modulator in TriPleX platform using a piezoelectric lead zirconate titanate (PZT) thin film. Opt. Express 23, 14018 (2015).De Cort, W., Beeckman, J., Claes, T., Neyts, K. & Baets, R. Wide tuning of silicon-on-insulator ring resonators with a liquid crystal cladding. Opt. Lett. 36, 3876–3878 (2011).Xing, Y. et al. Digitally controlled phase shifter using an SOI slot waveguide with liquid crystal infiltration. IEEE Photonics Technol. Lett. 27, 1269–1272 (2015).Abel, S. et al. Large Pockels effect in micro- and nanostructured barium titanate integrated on silicon. Nat. Mater. 18, 42–47 (2019).Desiatov, B., Shams-Ansari, A., Zhang, M., Wang, C. & Lončar, M. Ultra-low-loss integrated visible photonics using thin-film lithium niobate. Optica 6, 380 (2019).Alexander, K. et al. Nanophotonic Pockels modulators on a silicon nitride platform. Nat. Commun. 9, 3444 (2018).Leuthold, J. et al. Silicon-organic hybrid electro-optical devices. IEEE J. Sel. Top. Quantum Electron. 19, 114–126 (2013).Errando-Herranz, C. et al. MEMS for photonic integrated circuits. IEEE J. Sel. Top. Quantum Electron. 26, 8200916 (2020).Quack, N. et al. MEMS-enabled silicon photonic integrated devices and circuits. IEEE J. Quantum Electron. 56, 8400210 (2020).Hoessbacher, C. et al. The plasmonic memristor: a latching optical switch. Optica 1, 198 (2014).Ríos, C. et al. Integrated all-photonic non-volatile multi-level memory. Nat. Photon. 9, 725–732 (2015).Wuttig, M., Bhaskaran, H. & Taubner, T. Phase-change materials for non-volatile photonic applications. Nat. Photon. 11, 465–476 (2017).Morichetti, F. et al. Non-invasive on-chip light observation by contactless waveguide conductivity monitoring. IEEE J. Sel. Top. Quantum Electron. 20, 292–301 (2014).Jayatilleka, H., Shoman, H., Chrostowski, L. & Shekhar, S. Photoconductive heaters enable control of large-scale silicon photonic ring resonator circuits. Optica 6, 84–91 (2019).Grillanda, S. et al. Non-invasive monitoring and control in silicon photonics using CMOS integrated electronics. Optica 1, 129 (2014).Annoni, A. et al. Automated routing and control of silicon photonic switch fabrics. IEEE J. Sel. Top. Quantum Electron. 22, 169–176 (2016).Dumais, P. et al. Silicon photonic switch subsystem with 900 monolithically integrated calibration photodiodes and 64-fiber package. J. Light. Technol. 36, 233–238 (2018).Chen, H., Luo, X. & Poon, A. W. Cavity-enhanced photocurrent generation by 1.55 μm wavelengths linear absorption in a p–i–n diode embedded silicon microring resonator. Appl. Phys. Lett. 95, 171111 (2009).Ribeiro, A. & Bogaerts, W. Digitally controlled multiplexed silicon photonics phase shifter using heaters with integrated diodes. Opt. Express 25, 29778 (2017).Zimmermann, L. et al. BiCMOS silicon photonics platform. In Optical Fiber Communication Conference Th4E-5 (Optical Society of America, 2015).Orcutt, J. S. et al. Nanophotonic integration in state-of-the-art CMOS foundries. Opt. Express 19, 2335–2346 (2011).Stojanović, V. et al. Monolithic silicon-photonic platforms in state-of-the-art CMOS SOI processes. Opt. Express 26, 13106 (2018).Carroll, L. et al. Photonic packaging: transforming silicon photonic integrated circuits into photonic devices. Appl. Sci. 6, 426 (2016).Patterson, D., De Sousa, I. & Archard, L.-M. The future of packaging with silicon photonics. Chip Scale Rev. 21, 1–10 (2017).Ribeiro, A., Declercq, S., Khan, U., Wang, M. & Van Iseghem, L. Column-row addressing of thermo-optic phase shifters for controlling large silicon photonic circuits. IEEE J. Sel. Top. Quantum Electron. 26, 6100708 (2020).Pantouvaki, M. et al. Active components for 50 Gb/s NRZ-OOK optical interconnects in a silicon photonics platform. J. Light. Technol. 35, 631–638 (2017).Chen, H. et al. 100-Gbps RZ data reception in 67-GHz Si-contacted germanium waveguide p-i-n photodetectors. J. Light. Technol. 35, 722–726 (2017).Pérez, D., Gasulla, I. & Capmany, J. Toward programmable microwave photonics processors. J. Light. Technol. 36, 519–532 (2018).Zoldak, M., Halmo, L., Turkiewicz, J. P., Schumann, S. & Henker, R. Packaging of ultra-high speed optical fiber data interconnects. In Opt. Fibers and Their Applications 2017 10325, 103250R (International Society for Optics and Photonics, 2017).Willner, A. E., Khaleghi, S., Chitgarha, M. R. & Yilmaz, O. F. All-optical signal processing. J. Light. Technol. 32, 660–680 (2014).Ramirez, J. M. et al. III–V-on-silicon integration: from hybrid devices to heterogeneous photonic integrated circuits. IEEE J. Sel. Top. Quantum Electron. 26, 6100213 (2020).Liu, A. Y. & Bowers, J. Photonic integration with epitaxial III–V on silicon. IEEE J. Sel. Top. Quantum Electron. 24, 6000412 (2018).Zhang, J. et al. Transfer-printing-based integration of a III–V-on-silicon distributed feedback laser. Opt. Express 26, 8821–8830 (2018).Thiessen, T. et al. Back-side-on-BOX heterogeneously integrated III–V-on-silicon O-band distributed feedback lasers. J. Light. Technol. 38, 3000–3006 (2020).López, A., Perez, D., DasMahapatra, P. & Capmany, J. Auto-routing algorithm for field-programmable photonic gate arrays. Opt. Express 28, 737–752 (2020).Chen, X., Stroobant, P., Pickavet, M. & Bogaerts, W. Graph representations for programmable photonic circuits. J. Light. Technol. https://ieeexplore.ieee.org/document/9056549 (2020).Zand, I. & Bogaerts, W. Effects of coupling and phase imperfections in programmable photonic hexagonal waveguide meshes. Photon. Res. 8, 211–218 (2020).Bogaerts, W. & Rahim, A. Programmable photonics: an opportunity for an accessible large-volume PIC ecosystem. IEEE J. Sel. Top. Quantum Electron. 26, 1–17 (2020). A simple techno-economic analysis of how general-purpose programmable photonic circuits can reduce the cost of prototyping photonics applications.Dubrovsky, M., Ball, M. & Penkovsky, B. Optical proof of work. Preprint at https://arxiv.org/abs/1911.05193 (2019).Paquot, Y., Schroeder, J., Pelusi, M. D. & Eggleton, B. J. All-optical hash code generation and verification for low latency communications. Opt. Express 21, 23873 (2013).Wang, J., Sciarrino, F., Laing, A. & Thompson, M. G. Integrated photonic quantum technologies. Nat. Photon. 14, 273–284 (2019).Norberg, E. J., Guzzon, R. S., Parker, J. S., Johansson, L. A. & Coldren, L. A. Programmable photonic microwave filters monolithically integrated in InP-InGaAsP. J. Light. Technol. 29, 1611–1619 (2011).Wang, J. et al. Reconfigurable radio-frequency arbitrary waveforms synthesized in a silicon photonic chip. Nat. Commun. 6, 5957 (2015).Burla, M. et al. On-chip CMOS compatible reconfigurable optical delay line with separate carrier tuning for microwave photonic signal processing. Opt. Express 19, 21475 (2011).Liu, L. et al. Photonic measurement of microwave frequency using a silicon microdisk resonator. Opt. Commun. 335, 266–270 (2015).Perez-Lopez, D., Sanchez, E. & Capmany, J. Programmable true-time delay lines using integrated waveguide meshes. J. Light. Technol. 36, 4591–4601 2018.Novak, D. et al. Radio-over-fiber technologies for emerging wireless systems. IEEE J. Quantum Electron. 52, 0600311 (2016).Behroozpour, B., Sandborn, P. A. M., Wu, M. C. & Boser, B. E. Lidar system architectures and circuits. IEEE Commun. Mag. 55, 135–142 (2017).Heck, M. J. R. Highly integrated optical phased arrays: photonic integrated circuits for optical beam shaping and beam steering. Nanophotonics 6, 93–107 (2017).Van Acoleyen, K. Efficient light collection and direction-of-arrival estimation using a photonic integrated circuit. Photonics 24, 933–935 (2012).Miller, D. A. B. Establishing optimal wave communication channels automatically. J. Light. Technol. 31, 3987–3994 (2013).Luan, E., Shoman, H., Ratner, D. M., Cheung, K. C. & Chrostowski, L. Silicon photonic biosensors using label-free detection. Sensors 18, 3519 (2018).Subramanian, A. Z. et al. Silicon and silicon nitride photonic circuits for spectroscopic sensing on-a-chip. Photon. Res. 3, B47–B59 (2015).Li, Y. et al. Six-beam homodyne laser Doppler vibrometry based on silicon photonics technology. Opt. Express 26, 3638 (2018).Trimberger, S. M. Three ages of FPGAs: a retrospective on the first thirty years of FPGA technology. Proc. IEEE 103, 318–331 (2015).Mohomed, I. & Dutta, P. The age of DIY and dawn of the maker movement. Mob. Comput. Commun. Rev. 18, 41–43 (2015).Preskill, J. Quantum computing in the NISQ era and beyond. Quantum 7, 79 (2018).Arute, F. et al. Quantum supremacy using a programmable superconducting processor. Nature 574, 505–510 (2019).Biamonte, J. et al. Quantum machine learning. Nature 549, 195–202 (2017).Steinbrecher, G. R., Olson, J. P., Englund, D. & Carolan, J. Quantum optical neural networks. npj Quantum Inf. 5, 60 (2019).Miatto, F. M., Epping, M. & Lütkenhaus, N. Hamiltonians for one-way quantum repeaters. Quantum 2, 75 (2018)
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