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7th Asia Pacific conference on Optics Manufacture, APCOM 2021

作者： Yang, Qisheng Mou, Xing Wang, Yuhao Yan, Anzhi Yang, Yi Ren, Tian-Ling Tsinghua University Beijing100084 China

ISBN: (数字)9781510652095

ISBN: (纸本)9781510652088

The all-optical/optoelectronic hybrid intelligent computing with high speed and low power consumption characteristics has emerged as a promising solution for the bottleneck of Moore's Law. However, the low deployment flexibility and low integration limit the further development of optical computing systems, and it is urgent to match the new artificial intelligence theory with the physical characteristics of light itself. In this paper, we proposed a reconfigurable computing architecture based on planar optical waveguide, called wave network, which can be used for hardware development of optical switches, optical logic devices or neural networks. Inspired by the neuronal perceptron model, the elements of wave network are analyzed from the point of view of basic pixel units. Wave network has the processing capability of pulse input and time sequence input. To achieve low-power weight mapping, non-volatile materials with CMOS compatiblity characteristics are introduced above the waveguide (etc. phase change materials, multiferroics materials, and resistive switching materials). This hybrid structure provides a large-scale, low-cost, rapid development platform for the new photonic computing paradigm. And the simulation results show that the properties of the waveguide remain stable at different geometric scales and have the potential of scaling down. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Optical data processing

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Exploring Trends and Opportunities in Quantum-Enhanced Advanced photonic Illumination Technologies

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ADVANCED QUANTUM TECHNOLOGIES 2024年第3期7卷

作者： Taha, Bakr Ahmed Addie, Ali J. Haider, Adawiya J. Chaudhary, Vishal Apsari, Retna Kaushik, Ajeet Arsad, Norhana Univ Kebangsaan Malaysia Fac Engn & Built Environm UKM Dept Elect Elect & Syst Engn UKM Bangi 43600 Malaysia Minist Sci & Technol Ctr Adv Mat Directorate Mat Res Baghdad 10066 Iraq Univ Technol Baghdad Appl Sci Dept Laser Sci & Technol Branch Baghdad 10066 Iraq Univ Delhi Bhagini Nivedita Coll Phys Dept New Delhi 110045 India Univ Airlangga Fac Adv Technol & Multidiscipline Surabaya 60115 Indonesia Florida Polytech Univ Dept Environm Engn NanoBioTech Lab Lakeland FL 33805 USA

The development of quantum-enabled photonic technologies has opened new avenues for advanced illumination across diverse fields, including sensing, computing, materials, and integration. This review highlights how Quantum-enhanced sensing and imaging exploit nonclassical correlations to attain unprecedented accuracy in chaotic environments. As well as guaranteeing secure communications, quantum cryptography, protected by physical principles, ensures unbreakable cryptographic key exchange. As quantum computing speed increases exponentially, previously unimplementable uses for classical computers become feasible. On-chip integration enables the mass production of quantum photonic components for pervasive applications by facilitating miniaturization and scalability. A powerful and flexible platform is produced when classical and quantum systems are combined. Quantum spin liquids and other topological materials can maintain their quantum states while subject to decoherence. Despite challenges with decoherence, production, and commercialization, quantum photonics is an exciting new area of study that promises lighting techniques impossible with conventional optics. To realize this promise, researchers from several fields must work together to solve complex technical problems and decode fundamental physics. Finally, advances in quantum-enabled photonics have the potential to evolve quantum photonic devices and cutting-edge imaging methods and usher in a new age of lighting options based on quantum dots. photonic quantum technologies improve sensing, computing, and material illumination, providing precise sensing, safe encryption, and quick processing in chaotic conditions. Scalability and large manufacturing are possible with on-chip integration. A versatile platform is created by combining conventional and quantum technologies. Quantum spin liquids sustain quantum states despite decoherence, and interdisciplinary collaboration is essential for advancing quantum photonics

关键词： illumination engineering quantum communication quantum computing quantum photonics quantum sensing

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Atomistic materials and TCAD Device Modeling and Simulation of Ultrawide Bandgap (UWBG) materials and UWBG Heterointerfaces

Atomistic Materials and TCAD Device Modeling and Simulation ...

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IEEE Nanotechnology materials and devices conference (NMDC)

作者： Ugonna Ohiri Xiangyi Tony Guo Northrop Grumman Systems Corporation (NGSC) Linthicum MD USA

ISBN: (数字)9798331541439

ISBN: (纸本)9798331541446

Ultrawide bandgap (UWBG) materials (e.g., diamond, gallium oxide, boron nitride, and aluminum nitride) possess exquisite materials, electronic, and thermal properties. Atomistic materials and TCAD device modeling and simulations are prime accelerators for understanding the exquisite capabilities of UWBG materials, which can therefore guide future experimental UWBG device design. In this study, we explore several electronic properties of UWBG materials and heterointerfaces (i.e., UWBG semiconductor - UWBG semiconductor heterointerfaces and UWBG semiconductor - metal heterointerfaces) using Density Functional Theory (DFT) first-principle approaches in Synopsys Quantum ATK. TCAD device simulations were also performed using Synopsys Sentaurus TCAD, where Transfer Length Method (TLM) currentvoltage (I-V) simulations were performed to extract specific contact resistivity values, which could assist in downselecting materials needed to form compatible Schottky and/or Ohmic contacts for future UWBG-based devices. All UWBG atomistic materials and TCAD device simulations were performed using multi-level parallelization on high-performance computing workstations (> 16 cores) provided by NGSC. Comprehensively, these atomistic materials and TCAD device simulation results show promise for developing the next generation of high-performance UWBG devices and systems for emerging Department of Defense (DoD) applications (e.g., RF, power electronics, and high-temperature environments).

关键词： Performance evaluation Radio frequency Schottky diodes photonic band gap Computational modeling Simulation Discrete Fourier transforms Workstations US Department of Defense Next generation networking

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Ultrafast photodetectors at Terahertz frequencies based on 2D materials: technological developments and applications in optical communications

Ultrafast photodetectors at Terahertz frequencies based on 2...

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International conference on Transparent Optical Networks

作者： Miriam Serena Vitiello NEST National Research Council CNR-NANO and Scuola Normale Superiore Piazza San Silvestro Pisa Italy

ISBN: (数字)9798350377323

ISBN: (纸本)9798350377330

Bi-dimensional nano-materials and related heterostructures are establishing themselves as intriguing material systems for the development of electronic, photonic and plasmonic quantum devices with properties that can be engineered "from scratch". Their peculiar band-structure and electron transport characteristics, which can be easily manipulated via layer thickness control, indeed suggest they could also form the basis for a new generation of high-performance devices operating in the Terahertz frequency range ($1-10 \mathrm{THz}$) of the electromagnetic spectrum. This talk will review our latest achievements in the developments of high speed photodetectors at THz frequencies ($2-5 \mathrm{THz}$), and will discuss concrete perspectives for applications in optical communications.

关键词： Terahertz communications Photodetectors Optical fiber networks Thickness control Reviews Plasmons photonics

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Smart Citizen in a Smart Building in Society 5.0 24

Smart Citizen in a Smart Building in Society 5.0

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24th International conference on Control systems and Computer Science, CSCS 2023

作者： Rosu, Razvan Universitatea Politehnica Bucuresti Automation and Computers Systems Engineering Bucharest Romania

ISBN: (纸本)9798350313390

The relationship between humans and technology is constantly evolving, and we are currently witnessing three major trends that will significantly impact how we build and inhabit communities. Firstly, the energy cost will continuously decrease towards zero through better harvesting and storing energy from renewable sources. Secondly, the cost of acquiring data from citizens will decrease towards zero through the voluntary installation of IoT devices and cyberphysical systems and due to participatory data-sharing tendencies. Lastly, the cost of computation, through improving materials involved, distributed and quantum computing, and communication through 6G and tactile/senses internet, will decrease to zero. As a result, we must pay closer attention to how we build our society in a way that utilizes these abundant resources effectively. In this paper, we explore the potential of smart buildings equipped with cyber-physical systems as a means of building a new community fabric that enables individuals to live a smart life in Society 5.0. We propose an ontology that exemplifies interaction scenarios between smart building inhabitants, smart building control systems, and the city's marketplace. Furthermore, we discuss how the virtualization of individuals' residencies using Building Information Modelling (BIM) and the Internet of Things (IoT) can provide a better understanding of their needs and preferences. Virtualization can help building inhabitants experiment with different configurations and test out new ideas while also facilitating the process of finding solutions in the city's marketplace. Our proposed system can serve as a foundation for advancing research in connecting needs and reality in smart buildings to the marketplace, with potential applications in anonymized data sharing and community-level solutions. © 2023 IEEE.

关键词： Cyber Physical System

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Optical Power Injection Approaches in photonic Integrated Circuits

Optical Power Injection Approaches in Photonic Integrated Ci...

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Optics and photonics conference (SBFoton IOPC), SBFoton International

作者： Gilliard N. Malheiros-Silveira Faculdade de Engenharia Elétrica e de Computação (FEEC) Universidade Estadual de Campinas (UNICAMP) Campinas SP Brazil

ISBN: (数字)9798350388176

ISBN: (纸本)9798350388183

Silicon photonics is a predominant and revolutionary platform in integrated photonics that enables the realization of a multitude of components and systems that cover several applications related to computing, communication, and sensing. Regardless of the device/system that can be implemented through this platform, an issue of academic and industrial interest lies in the injection of optical power/signal into photonic Integrated Circuits (PICs). This manuscript provides a brief review of some approaches used to power the PIC. First, we will address the issues and solutions related to the coupling of a signal from a laser to a PIC. Finally, we will address the approaches for heterogeneous integration between the light source and the PIC, where III-V-on-silicon technologies will be highlighted.

关键词： Integrated optics Reviews Semiconductor lasers photonic integrated circuits Multichip modules Silicon photonics Optical coupling Optical sensors III-V semiconductor materials Light sources

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Twin Metamaterials: Inversion Symmetry, Reverse Magnetism, and Interface States

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Physical Review Applied 2023年第5期19卷 054081-054081页

作者： Xiaodong Sun Xinyu Zhao Jingguang Chen Fang Guan Xinhua Hu Department of Materials Science and Key Laboratory of Micro- and Nano-Photonic Structures (Ministry of Education) Fudan University Shanghai 200433 China State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai 201210 China

Artificial magnetism can be realized with metamaterials in high frequencies, which are important for many applications. However, such metamaterials need to be constructed with metal or high-relative-permittivity dielectric and thus may exhibit absorption loss. Here, we theoretically propose and experimentally demonstrate a pair of magnetic metamaterials that have inversion symmetry and are generated from a parent photonic crystal with low-relative-permittivity dielectric (εr<4). Interestingly, one metamaterial is paramagnetic, the other is diamagnetic, and the product of their effective relative permeabilities is close to 1 (μe1>1, μe2<1, μe1μe2≈1) in a broad frequency range. As a result, fascinating effects, such as wide-angle and wide-frequency near-perfect transmission and interface states, are observed in the systems.

关键词： Dielectric properties Light propagation, transmission & absorption Metamaterials photonic crystals Surface & interfacial phenomena Diamagnets Paramagnets Inversion symmetry

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End-to-end deep learning with neuromorphic photonics 25

End-to-end deep learning with neuromorphic photonics

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conference on Integrated Optics - devices, materials, and Technologies XXV

作者： Dabos, G. Mourgias-Alexandris, G. Totovic, A. Kirtas, M. Passalis, N. Tefas, A. Pleros, N. Aristotle Univ Thessaloniki Dept Informat Thessaloniki Greece Aristotle Univ Thessaloniki Ctr Interdisciplinary Res & Innovat Thessaloniki Greece

ISBN: (纸本)9781510642140

Neuromorphic computing has emerged as a highly-promising compute alternative, migrating from von-Neuman architectures towards mimicking the human brain for sustaining computational power increases within a reduced power consumption envelope. Electronic neuromorphic chips like IBM's TrueNorth, Intel's Loihi and Mythic's AI platform reveal a tremendous performance improvement in terms of computational speed and density;at the same time, neuromorphic photonic layouts are constantly gaining ground in exploiting their large component portfolio for enabling GHz-bandwidth and low-energy neurons. Progressing in tight synergy with appropriate training techniques, this evolution has already started to translate into performance improvements in end-to-end applications, highlighting the practical perspectives of the new neural network hardware when effectively synergized with new training frameworks. Herein, we present a complete portfolio of neuromorphic photonic subsystems and architectures, highlighting their utilization in practical application scenario for time series classification and fiber transmission links. Our work extends along feed-forward and recurrent photonic NN models, demonstrating experimental results together with the required training methods for bridging the gap between software-deployed NNs and the photonic hardware. We report on the experimentally validated performance of a 10GHz photonic time series classification engine, presenting also preliminary results on how photonic neurons can replace DSP modules in end-to-end fiber transmission schemes. The perspectives of these layouts to yield energy and area efficiency benefits are discussed through a detailed energy and area breakdown of neuromorphic photonic technologies, highlighting a promising roadmap when plasmo-photonic hardware is adopted.

关键词： Neuromorphic photonics photonic integrated circuits neural networks optical computing artificial intelligence

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Effects of Process Parameters on $\mathrm{G}{\mathrm{a}}_2{\mathrm{O}}_3$ Fabricated by MBE, HVPE, and MOCVD

Effects of Process Parameters on $\mathrm{G}{\mathrm{a}}_2{\...

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Integrated Circuits, Communication, and computing systems (ICIC3S), International conference on

作者： Mukund Ayalasomayajula Vasanth Balakrishnan Mohit Ravi Khurana Prince Shiva Chaudhary Sourayan Basu Bal Dept. of Mat. Sci. and Engg Cornell University Ithaca USA Dept. of Data Science Worcester Polytechnique Institute Worcester USA Dept. of Matter Transport & Energy. Arizona State University Tempe USA

ISBN: (数字)9798350364088

ISBN: (纸本)9798350364095

This study investigates Ga2O3, a promising wide bandgap semiconductor, amid the semiconductor industry's quest for high-performance, cost-effective devices. Ga2O3's various polymorphs, notably $\beta$ -Ga2O3, showcase a wide bandgap, enabling UV transparency crucial for diverse applications. While $\beta$ -Ga2O3's fabrication via melt-growth techniques distinguishes it from other phases, its high electron mobility and controllable electrical conductivity position it as a potential GaN alternative, despite its lower thermal conductivity. This paper delves into deposition techniquesMBE, HVPE, and MOCVD-unveiling distinct approaches and challenges. MBE's ultra-high vacuum conditions encounter phase stability issues addressed through compound sources, while HVPE, known for high growth rates, adopts thermodynamically determined precursors for optimal growth. MOCVD, though slower, benefits from modified setups to enhance growth rates. Emphasizing Ga2O3's wide bandgap and exploring its deposition techniques, this study offers critical insights, propelling advancements in semiconductor technology for high-bandgap materials.

关键词： Temperature photonic band gap Molecular beam epitaxial growth Production Conductivity Thermal conductivity Wide band gap semiconductors

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Editorial: Neuromorphic computing: from emerging materials and devices to algorithms and implementation of neural networks inspired by brain neural mechanism

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FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2024年 18卷 1443758页

作者： Zhang, Guohe Xi An Jiao Tong Univ Sch Microelect Key Lab Micro Nano Elect & Syst Integrat Xian City Xian Peoples R China

One of the key challenges in computational neuroscience is the need for powerful simulation platforms to study complex neural network models. Traditional simulators often struggle to keep up with the complexity and scale of these models, leading to slow simulation times and limited insights. To address this challenge, Kauth et al. ( 2023) introduced the neuroAIx-Framework, a flexible and scalable approach to explore future neuroscience simulation systems. This framework leverages empirical modeling tools, virtual prototypes, and FPGA clusters to achieve significant acceleration, even for large-scale models. The FPGA cluster developed within this framework achieves a remarkable 20x acceleration compared to biological real-time, setting a new benchmark in the field. This breakthrough opens doors for researchers to study complex neural processes and explore new hypotheses at a scale previously *** Neural Networks (SNNs) have gained attention for their potential to achieve low-power and low-latency AI computations. Traditional neural network architectures, such as LSTM and CNN, are energy-intensive and not suitable for resource-constrained devices. SNNs, on the other hand, exhibit spike-based computations that closely resemble biological neural processing and offer significant energy savings. that the excitatory-inhibitory balance plays a crucial role in driving dynamics and performance, overriding attractor dynamics. The findings provide valuable insights for designing optimal RBN reservoirs and simplifying the reservoir design process. This understanding can lead to the development of more efficient and effective RC models that can be used for a wide range of applications, such as speech recognition, natural language processing, and signal *** articles discussed above showcase the diverse and exciting research happening in computational neuroscience. The future of the field holds several promising directions:1) Developing More Complex SNN A

关键词： spiking neural networks reservoir computing (RC) photonic hardware neuroAIx-Framework computational neuroscience

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