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Integrated lithium niobate photonic computing circuit based on efficient and high-speed electro-optic conversion

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arXiv 2024年

作者： Hu, Yaowen Song, Yunxiang Zhu, Xinrui Guo, Xiangwen Lu, Shengyuan Zhang, Qihang He, Lingyan Franken, C.A.A. Powell, Keith Warner, Hana Assumpcao, Daniel Renaud, Dylan Wang, Ying Magalhães, Letícia Rosborough, Victoria Shams-Ansari, Amirhassan Li, Xudong Cheng, Rebecca Luke, Kevin Yang, Kiyoul Barbastathis, George Zhang, Mian Zhu, Di Johansson, Leif Beling, Andreas Sinclair, Neil Loncar, Marko John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States State Key Laboratory for Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics School of Physics Peking University Beijing100871 China Quantum Science and Engineering Harvard University CambridgeMA02138 United States Department of Electrical and Computing Engineering University of Virginia CharlottesvilleVA22903 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States HyperLight Corporation 501 Massachusetts Ave CambridgeMA02139 United States Laser Physics and Nonlinear Optics Group Department of Science and Technology MESA+ Institute of Nanotechnology University of Twente Enschede Netherlands Freedom Photonics 41 Aero Camino GoletaCA United States Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering National University of Singapore Singapore117575 Singapore Singapore138634 Singapore

The surge in artificial intelligence applications, encompassing machine vision, autonomous driving, remote sensing, and process simulation, relies on efficient and large-scale data processing. This requires highly scalable computation with high speed and low energy consumption, calling for innovative solutions to overcome the limitations of electronic systems1–9. Integrated photonics may play a pivotal role in addressing this challenge, leveraging the intrinsic properties of photons, such as natural parallelism, high bandwidth, and low latency10–15. While current photonic computing approaches show promise, they are critically limited by the speed and energy consumption of mapping information from the electronic to optical domain (i.e., electro-optic conversion)1–3,6–8,16 . Here we show a photonic computing accelerator utilizing a system-level thin-film lithium niobate circuit which overcomes this limitation. Leveraging the strong electro-optic (Pockels) effect and the scalability of this platform, we demonstrate photonic computation at speeds up to 1.36 TOPS while consuming 0.057 pJ/OP. Our system features more than 100 thin-film lithium niobate high-performance components working synergistically, surpassing state-of-the-art systems on this platform. We further demonstrate binary-classification, handwritten-digit classification, and image classification with remarkable accuracy, showcasing our system’s capability of executing real algorithms. Finally, we investigate the opportunities offered by combining our system with a hybrid-integrated distributed feedback laser source and a heterogeneous-integrated modified uni-traveling carrier photodiode. Our results illustrate the promise of thin-film lithium niobate as a computational platform, addressing current bottlenecks in both electronic and photonic computation. Its unique properties of high-performance electro-optic weight encoding and conversion, wafer-scale scalability, and compatibility with integrated lasers and

关键词： Distributed feedback lasers

Personal data access control through distributed authorization

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arXiv 2021年

作者： Zichichi, Mirko Ferretti, Stefano D’Angelo, Gabriele Rodríguez-Doncel, Víctor Ontology Engineering Group Universidad Politécnica de Madrid Spain Department of Pure and Applied Sciences University of Urbino Carlo Bo Italy Department of Computer Science and Engineering University of Bologna Italy

This paper presents an architecture of a Personal Information Management System, in which individuals can define the access to their personal data by means of smart contracts. These smart contracts, running on the Ethereum blockchain, implement access control lists and grant immutability, traceability and verifiability of the references to personal data, which is stored itself in a (possibly distributed) file system. A distributed authorization mechanism is devised, where trust from multiple network nodes is necessary to grant the access to the data. To this aim, two possible alternatives are described: a Secret Sharing scheme and Threshold Proxy Re-Encryption scheme. The performance of these alternatives is experimentally compared in terms of execution time. Threshold Proxy Re-Encryption appears to be faster in different scenarios, in particular when increasing message size, number of nodes and the threshold value, i.e. number of nodes needed to grant the data disclosure. Copyright © 2021, The Authors. All rights reserved.

关键词： Smart contract

THE DOUBLE DIHEDRAL DUNKL TOTAL ANGULAR MOMENTUM ALGEBRA

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arXiv 2023年

作者： de Martino, Marcelo Langlois-Rémillard, Alexis Oste, Roy Clifford Research Group Department of Electronics and Information Systems Faculty of Engineering and Architecture Ghent University Krijgslaan 281–S8 Gent9000 Belgium Department of Applied Mathematics Computer Science and Statistics Faculty of Sciences Ghent University Krijgslaan 281–S9 Gent9000 Belgium ScaDS.AI Leipzig University Leipzig04105 Germany

The Dunkl deformation of the Dirac operator is part of a realisation of an orthosymplectic Lie superalgebra inside the tensor product of a rational Cherednik algebra and a Clifford algebra. The Dunkl total angular momentum algebra (TAMA) occurs as the supercentraliser, or dual partner, of this Lie superalgebra. In this paper, we consider the case when the reflection group associated with the Dunkl operators is a product of two dihedral groups acting on a four-dimensional Euclidean space. We introduce a subalgebra of the total angular momentum algebra that admits a triangular decomposition and, in analogy to the celebrated theory of semisimple Lie algebras, we use this triangular subalgebra to give precise necessary conditions that a finite-dimensional irreducible representation must obey, in terms of weights. Furthermore, we construct a basis for representations of the TAMA with explicit actions. Examples of these modules occur in the kernel of the Dunkl–Dirac operator in the context of deformations of Howe dual pairs. © 2023, CC BY.

关键词： Angular momentum

HURWITZ SERIES RINGS SATISFYING A ZERO DIVISOR PROPERTY

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arXiv 2023年

作者： Mosallaei, Behrooz Afrouzmehr, Moein Abshari, Danial Farivar, Sepideh The Klipsch School of Electrical and Computer Engineering New Mexico State University Las CrucesNM88003 United States Department of Economics Applied Statistics and International Business New Mexico State University Las CrucesNM88003 United States Software and Information Systems Department University of North Carolina at Charlotte CharlotteNC28223 United States Department of Computer Science University of Nevada Las Vegas 4505 S. Maryland Parkway Las VegasNV89154-4030 United States

In this paper, we study zero divisors in the Hurwitz series rings and the Hurwitz polynomial rings over general non-commutative rings. We first construct Armendariz rings that are not Armendariz of the Hurwitz series type and find various properties of (the Hurwitz series) Armendariz rings. We show that for a semiprime Armendariz of the Hurwitz series type (so reduced) ring R with a.c.c. on annihilator ideals, HR (the Hurwitz series ring with coefficients over R) has finitely many minimal prime ideals, say B1, . . ., Bm such that B1 · . . . · Bm = 0 and Bi = HAi for some minimal prime ideal Ai of R for all i, where A1, . . ., Am are all minimal prime ideals of R. Additionally, we construct various types of (the Hurwitz series) Armendariz rings and demonstrate that the polynomial ring extension preserves the Armendarizness of the Hurwitz series as the Armendarizness. © 2023, CC0.

关键词： Algebra

MOVO: A dApp for DLT-based smart mobility

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arXiv 2021年

作者： Zichichi, Mirko Ferretti, Stefano D'Angelo, Gabriele Ontology Engineering Group Universidad Politécnica de Madrid Spain Department of Computer Science and Engineering University of Bologna Italy Department of Pure and Applied Sciences University of Urbino "Carlo Bo" Italy

Plenty of research on smart mobility is currently devoted to the inclusion of novel decentralized software architectures to these systems, due to the inherent advantages in terms of transparency, traceability, trustworthiness. MOVO is a decentralized application (dApp) for smart mobility. It includes: (i) a module for collecting data from vehicles and smartphones sensors;(ii) a component for interacting with Distributed Ledger Technologies (DLT) and Decentralized File Storages (DFS), for storing and validating sensor data;(iii) a module for "offline" interaction between devices. The dApp consists of an Android application intended for use inside a vehicle, which helps the user/driver collect contextually generated data (e.g. a driver's stress level, an electric vehicle's battery level), which can then be shared through the use of DLT (i.e., IOTA DLT and Ethereum smart contracts) and DFS (i.e., IPFS). The third module consists of an implementation of a communication channel that, via Wi-Fi Direct, allows two devices to exchange data and payment information with respect to DLT (i.e. cryptocurrency and token) assets. In this paper, we describe the main software components and provide an experimental evaluation that confirms the viability of the MOVO dApp in real mobility scenarios. Copyright © 2021, The Authors. All rights reserved.

关键词： Distributed ledger

Machine Learning Technique for Analyzing the Behavior of Fish in an Aquarium 1st

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Machine Learning Technique for Analyzing the Behavior of Fis...

1st International Conference on Modeling, Machine Learning and Astronomy, MMLA 2019

作者： Bhaskaran, Rishabh Baskaran, Rajesh Kanna Vijayalakshmi, C. Software Engineer -II Walmartlabs Bengaluru India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Statistics and Applied Mathematics Central University of Tamil Nadu Thiruvarur India

ISBN: (纸本)9789813364622

Over the years lots of marine biologists and scientists have made efforts to study the various problem related to the ocean and its animals. One such problem faced by the fisheries is the change in the physical and mental state of the fishes when they are affected by natural calamities, external agents, change in environment, epidemic outbreak or many such factors. Under such circumstances it’s probable that the fishes in the region may get affected and due to a small amount of bad fish the whole population could suffer which is a huge loss both biologically and economically. There are numerous research and studies back on the fact that fishes tend to change their behaviour in the situation of distress. The behavioural change is just in response to the distress caused to them either physically or psychologically. The motion of the fish over a period of time interval can help us learn about the behaviour it is showing. And a significant change in its pattern of motion can alarm us that there is some issue with the fish. The main idea is to identify and establish the relationship between the movements and behaviour of the fish. The video footage of a Tilapia Genus fish in a standard size aquarium set up with the help of surveillance cameras, tracked the motion of the fish in 2-D space is collected and the movement of the fish over a period of time is categorised. Based on the output the losses can be reduced. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Fish

Visualizing Quantum Circuit Probability estimating computational action for quantum program synthesis

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arXiv 2023年

作者： Bach, Bao Gia Kundu, Akash Acharya, Tamal Sarkar, Aritra Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Viet Nam Viet Nam Joint Doctoral School Silesian University of Technology Gliwice Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland Independent Researcher Bengaluru India Quantum Machine Learning Research group Quantum Computing Division QuTech Netherlands Quantum Intelligence Research team Department of Quantum & Computer Engineering Delft University of Technology Netherlands

This research applies concepts from algorithmic probability to Boolean and quantum combinatorial logic circuits. A tutorial-style introduction to states and various notions of the complexity of states are presented. Thereafter, the probability of states in the circuit model of computation is defined. Classical and quantum gate sets are compared to select some characteristic sets. The reachability and expressibility in a space-time-bounded setting for these gate sets are enumerated and visualized. These results are studied in terms of computational resources, universality and quantum behavior. The article suggests how applications like geometric quantum machine learning, novel quantum algorithm synthesis and quantum artificial general intelligence can benefit by studying circuit probabilities. © 2023, CC BY-NC-SA.

关键词： Machine learning

Recent Advancements in Solid State Transformer-based EV Fast Charging Stations

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Recent Advancements in Solid State Transformer-based EV Fast...

International Conference on Power Electronics and Drive Systems (PEDS)

作者： Ruvini De Seram Anindita Golder Sheldon S. Williamson Smart Transportation Electrification and Energy Research (STEER) Group Ontario Tech University Oshawa ON Canada Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech University Oshawa ON Canada Ontario Tech-Automotive Center of Excellence (ACE) Ontario Tech University Oshawa ON Canada Department of Electrical and Computer Engineering Faculty of Engineering and Applied Science Ontario Tech University Oshawa ON Canada

Growing deployments of ultra fast charging stations (XFCS) are putting a stress on the existing line-frequency transformer (LFT)-based medium voltage (MV) grid due to the high charging demands of exponentially growing electric vehicles (EV). The conventional LFT occupies a large space in the XFCS installation which introduces challenges in facilitating the XFCS infrastructure. As a result, solid-state transformer (SST)-based XFCS are being developed which can be directly connected to the MV grid and several advantages over LFT-based systems such as compactness, intelligence and availability of the DC link to connect renewable energy sources and storage system can be realized. As such, a detailed analysis of current developments in SST-based XFCS is presented and compared with one another in this paper. The challenges associated with the configurations are examined and direction for future research is identified.

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Smart Office Automation using Multi-Dimensional Attention Spiking Neural Network for Face Recognition in Internet of Things

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applied Soft Computing 2025年

作者： Harish Kumar Taluja Anuradha Taluja I Kala Balasubbareddy Mallala Department of Computer Science and Engineering HRIT Group of Institutions Ghaziabad Uttar Pradesh-201003 India Department of Computer Science Ajay Kumar Garg Engineering College Ghaziabad Uttar Pradesh-201015 India Department of Computer Science and Engineering PSG Institute of technology and Applied Research Coimbatore Tamil Nadu-641062 India Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Hyderabad Telangana-500075 India

In smart office automation, face recognition systems face accuracy constraints that are exacerbated by the difficulty of recognizing masked faces. Masked face recognition is a key research field in smart office automation, as it faces challenges in classification *** resolve these issues, pioneering research is needed to develop resilient solutions for accurately identifying individuals and enhancing the productivity of smart office setups. Therefore, in this paper, a Smart Office Automation using Multi-Dimensional Attention Spiking Neural Network for Face Recognition in the Internet of Things (SOA-MDASNN-FR-IoT) is proposed. Here, the input images are gathered fromLabelled Faces in the Wild (LFW) dataset. Then, the Multi Window Savitzky Golay Filter (MWSGF) is used for resizing and enhancing the collected images. Afterward, feature extraction is performed using the Multi-Synchro squeezing Transform (MSST) to extract facial features,like eyes, eyebrows, mouth, nose, and jaw. A Multi-Dimensional Attention Spiking Neural Network (MDASNN) is used to detect individual faces based on an IoT device, classified as either 'Door Closed' or 'Door Opened. Hence, the Secretary Bird Optimization Algorithm (SBOA) is proposed to enhance MDASNN that can effectively recognize the face. The proposed SOA-MDASNN-FR-IoT method provides 36.64%, 33.87 and 31.56% higher precision, 28.59%, 33.47% and 27.53% better accuracy compared with the existing *** proposed SOA-MDASNN-FR-IoTmodel considerably increases face recognition accuracy and efficiency in smart office automation, especially for masked faces, also outperforming other methods in performance measures.

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