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Application-level Benchmarking of Quantum Computers using Nonlocal Game Strategies

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arXiv 2023年

作者： Furches, Jim Chehade, Sarah Hamilton, Kathleen Wiebe, Nathan Marrero, Carlos Ortiz College of Computing Georgia Institute of Technology AtlantaGA30332 United States Physical Detection Systems and Deployment Division Pacific Northwest National Laboratory RichlandWA99354 United States Quantum Computational Science Group Oak Ridge National Laboratory Oak RidgeTN37830 United States Department of Computer Science University of Toronto ONM5S 1A1 Canada High Performance Computing Group Pacific Northwest National Laboratory RichlandWA99354 United States Canadian Institute for Advanced Research TorontoONM5G 1M1 Canada Department of Electrical & Computer Engineering North Carolina State University RaleighNC27607 United States

In a nonlocal game, two noncommunicating players cooperate to convince a referee that they possess a strategy that does not violate the rules of the game. Quantum strategies allow players to optimally win some games by performing joint measurements on a shared entangled state, but computing these strategies can be challenging. We present a variational quantum algorithm to compute quantum strategies for nonlocal games by encoding the rules of a nonlocal game into a Hamiltonian. We show how this algorithm can generate a short-depth optimal quantum strategy for a graph coloring game with a quantum advantage. This quantum strategy is then evaluated on fourteen different quantum hardware platforms to demonstrate its utility as a benchmark. Finally, we discuss potential sources of errors that can explain the observed decreased performance of the executed task and derive an expression for the number of samples required to accurately estimate the win rate in the presence of noise. Copyright © 2023, The Authors. All rights reserved.

关键词： Hamiltonians

A polyconvex transversely-isotropic invariant-based formulation for electro-mechanics: stability, minimisers and computational implementation

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arXiv 2022年

作者： Horák, Martin Gil, Antonio J. Ortigosa, Rogelio Kružík, Martin Faculty of Civil Engineering Czech Technical University Thákurova 7 Praha 6CZ-166 29 Czech Republic Zienkiewicz Centre for Computational Engineering Faculty of Science and Engineering Swansea University Bay Campus SA1 8EN United Kingdom Computational Mechanics and Scientific Computing Group Technical University of Cartagena Campus Muralla del Mar Cartagena Murcia30202 Spain Czech Academy of Sciences Institute of Information Theory and Automation Pod vodárenskou věží 4 Praha 8CZ-182 00 Czech Republic

The fabrication of evermore sophisticated miniaturised soft robotic components made up of Electro-Active Polymers (EAPs) is constantly demanding parallel development from the in-silico simulation point of view. The incorporation of crystallographic anisotropic micro-architectures, within an otherwise nearly uniform isotropic soft polymer matrix, has shown great potential in terms of advanced three-dimensional actuation (i.e. stretching, bending, twisting), especially at large strains, that is, beyond the onset of geometrical pull-in instabilities. To accommodate for this in-silico response, this paper presents a phenomenological invariant-based polyconvex transversely isotropic framework for the simulation of EAPs at large strains. This research expands previous work developed by Gil and Ortigosa for isotropic EAPs [40] with the help of the pioneering work by Schröeder and Neff [81] in the context of polyconvexity for materials endowed with crystallographic architectures in single physics mechanics. The paper also summarises key important results both in terms of the existence of minimisers and material stability. In addition, a series of numerical examples is presented in order to demonstrate the effect that the anisotropic orientation and the contrast of material properties, as well as the level of deformation and electric field, have upon the response of the EAP when subjected to large three-dimensional stretching, bending and torsion, including the possible development of wrinkling. Copyright © 2022, The Authors. All rights reserved.

关键词： Finite element method

Secure dual-functional radar-communication transmission: Exploiting interference for resilience against target eavesdropping

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arXiv 2021年

作者： Su, Nanchi Liu, Fan Wei, Zhongxiang Liu, Ya-Feng Masouros, Christos Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China College of Electronic and Information Engineering Tongji University Shanghai China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematicsand Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

We study security solutions for dual-functional radar communication (DFRC) systems, which detect the radar target and communicate with downlink cellular users in millimeter-wave (mmWave) wireless networks simultaneously. Uniquely for such scenarios, the radar target is regarded as a potential eavesdropper which might surveil the information sent from the base station (BS) to communication users (CUs), that is carried by the radar probing signal. Transmit waveform and receive beamforming are jointly designed to maximize the signalto- interference-plus-noise ratio (SINR) of the radar under the security and power budget constraints. We apply a Directional Modulation (DM) approach to exploit constructive interference (CI), where the known multiuser interference (MUI) can be exploited as a source of useful signal. Moreover, to further deteriorate the eavesdropping signal at the radar target, we utilize destructive interference (DI) by pushing the received symbols at the target towards the destructive region of the signal constellation. Our numerical results verify the effectiveness of the proposed design showing a secure transmission with enhanced performance against benchmark DFRC techniques. Copyright © 2021, The Authors. All rights reserved.

关键词： Budget control

Speech AI for All: Promoting Accessibility, Fairness, Inclusivity, and Equity

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Speech AI for All: Promoting Accessibility, Fairness, Inclus...

2025 CHI Conference on Human Factors in computing Systems, CHI EA 2025

作者： Wu, Shaomei Wenzel, Kimi Li, Jingjin Li, Qisheng Pradhan, Alisha Kushalnagar, Raja Lea, Colin Koenecke, Allison Vogler, Christian Hasegawa-Johnson, Mark Su, Norman Makoto Ratner, Nan Bernstein *** Mountain ViewCA United States Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States *** SeattleWA United States Department of Informatics Ying Wu College of Computing New Jersey Institute of Technology NewarkNJ United States Gallaudet University WashingtonDC United States Apple CupertinoCA United States Cornell University IthacaNY United States Technology Access Program Gallaudet University WashingtonDC United States The Grainger College of Engineering University of Illinois Urbana-Champaign Urbana-ChampaignIL United States Department of Computational Media University of California Santa Cruz Santa CruzCA United States Department of Hearing and Speech Sciences University of Maryland College Park College ParkMD United States Neuroscience and Cognitive Science University of Maryland College Park College ParkMD United States

ISBN: (纸本)9798400713958

Trained and optimized for typical and fluent speech, speech AI works poorly for people with speech diversities, often interrupting them and misinterpreting their speech. The increasing deployment of speech AI in automated phone menus, AI-conducted job interviews, and everyday devices poses tangible risks to people with speech diversities. To mitigate these risks, this workshop aims to build a multidisciplinary coalition and set the research agenda for fair and accessible speech AI. Bringing together a broad group of academics and practitioners with diverse perspectives, including HCI, AI, and other relevant fields such as disability studies, speech language pathology, and law, this workshop will establish a shared understanding of the technical challenges for fair and accessible speech AI, as well as its ramifications in design, user experience, policy, and society. In addition, the workshop will invite and highlight first-person accounts from people with speech diversities, facilitating direct dialogues and collaboration between speech AI developers and the impacted communities. The key outcomes of this workshop include a summary paper that synthesizes our learnings and outlines the roadmap for improving speech AI for people with speech diversities, as well as a community of scholars, practitioners, activists, and policy makers interested in driving progress in this domain. © 2025 Copyright held by the owner/author(s).

关键词： Speech enhancement

SHREC 2021: Classification in cryo-electron tomograms

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arXiv 2022年

作者： Gubins, Ilja Chaillet, Marten L. van der Schot, Gijs Trueba, M. Cristina Veltkamp, Remco C. Förster, Friedrich Wang, Xiao Kihara, Daisuke Moebel, Emmanuel Nguyen, Nguyen P. White, Tommi Bunyak, Filiz Papoulias, Giorgos Gerolymatos, Stavros Zacharaki, Evangelia I. Moustakas, Konstantinos Zeng, Xiangrui Liu, Sinuo Xu, Min Wang, Yaoyu Chen, Cheng Cui, Xuefeng Zhang, Fa Department of Information and Computing Sciences Utrecht University Netherlands Department of Chemistry Utrecht University Netherlands Department of Computer Science Purdue University United States Department of Biological Sciences Purdue University United States Inria Rennes Bretagne Atlantique France Department of Electrical Engineering and Computer Science University of Missouri United States Department of Biochemistry Electron Microscopy Core Facility University of Missouri United States Department of Electrical and Computer Engineering University of Patras Greece Computational Biology Department Carnegie Mellon University United States School of Computer Science and Technology Shandong University China Institute of Computing Technology Chinese Academy of Sciences China

Cryo-electron tomography (cryo-ET) is an imaging technique that allows three-dimensional visualization of macro-molecular assemblies under near-native conditions. Cryo-ET comes with a number of challenges, mainly low signal-to-noise and inability to obtain images from all angles. computational methods are key to analyze cryo-electron tomograms. To promote innovation in computational methods, we generate a novel simulated dataset to benchmark different methods of localization and classification of biological macromolecules in tomograms. Our publicly available dataset contains ten tomographic reconstructions of simulated cell-like volumes. Each volume contains twelve different types of complexes, varying in size, function and structure. In this paper, we have evaluated seven different methods of finding and classifying proteins. Seven research groups present results obtained with learning-based methods and trained on the simulated dataset, as well as a baseline template matching (TM), a traditional method widely used in cryo-ET research. We show that learning-based approaches can achieve notably better localization and classification performance than TM. We also experimentally confirm that there is a negative relationship between particle size and performance for all methods. © 2022, CC BY-NC-ND.

关键词： Classification (of information)

Robust Myco-Composites as a Platform for Versatile Hybrid-Living Structural Materials

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arXiv 2023年

作者： Shen, Sabrina C. Lee, Nicolas A. Lockett, William J. Acuil, Aliai D. Gazdus, Hannah B. Spitzer, Branden N. Buehler, Markus J. Massachusetts Institute of Technology 77 Massachusetts Ave. 1-165 CambridgeMA02139 United States Department of Materials Science and Engineering Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 United States School of Architecture and Planning Media Lab Massachusetts Institute of Technology 75 Amherst Street CambridgeMA02139 United States Massachusetts Institute of Technology 77 Massachusetts Ave. 10-183 CambridgeMA02139 United States Department of Media Culture and Communication New York University 239 Greene Street New YorkNY10003 United States Department of Civil and Environmental Engineering Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 United States Department of Mechanical Engineering Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 United States Center for Computational Science and Engineering Schwarzman College of Computing 77 Massachusetts Ave. CambridgeMA02139 United States

Fungal mycelium, a living network of filamentous threads, thrives on lignocellulosic waste and exhibits rapid growth, hydrophobicity, and intrinsic regeneration, offering a potential means to create next-generation sustainable and functional composites. However, existing hybrid-living mycelium composites (myco-composites) are tremendously constrained by conventional mold-based manufacturing processes, which are only compatible with simple geometries and coarse biomass substrates that enable gas exchange. Here we introduce a class of structural myco-composites manufactured with a novel platform that harnesses high-resolution biocomposite additive manufacturing and robust mycelium colonization with indirect inoculation. We leverage principles of hierarchical composite design and selective nutritional provision to create a robust myco-composite that is scalable, tunable, and compatible with complex geometries. To illustrate the versatility of this platform, we characterize the impact of mycelium colonization on mechanical and surface properties of the composite, finding that it yields the strongest mycelium composite reported to date, and demonstrate fabrication of unique foldable bio-welded containers and flexible mycelium textiles. This study bridges the gap between biocomposite and hybrid-living materials research, opening the door to advanced structural mycelium applications and demonstrating a novel platform for development of diverse hybrid-living materials. © 2023, CC BY-NC-ND.

关键词： Mycelium

Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models

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arXiv 2021年

作者： Guo, Ling Wu, Hao Zhou, Tao Department of Mathematics Shanghai Normal University Shanghai China School Odmathematical Sciences Tongji University Shanghai China LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

We introduce in this work the normalizing field flows (NFF) for learning random fields from scattered measurements. More precisely, we construct a bijective transformation (a normalizing flow characterizing by neural networks) between a Gaussian random field with the Karhunen-Loève (KL) expansion structure and the target stochastic field, where the KL expansion coefficients and the invertible networks are trained by maximizing the sum of the log-likelihood on scattered measurements. This NFF model can be used to solve data-driven forward, inverse, and mixed forward/inverse stochastic partial differential equations in a unified framework. We demonstrate the capability of the proposed NFF model for learning Non Gaussian processes and different types of stochastic partial differential equations. Copyright © 2021, The Authors. All rights reserved.

关键词： Uncertainty analysis

A New Global Divergence Free and Pressure-Robust HDG Method for Tangential Boundary Control of Stokes Equations

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arXiv 2022年

作者： Chen, Gang Gong, Wei Mateos, Mariano Singler, John R. Zhang, Yangwen School of Mathematics Sichuan University Chengdu China NCMIS LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Dpto. de Matemáticas Universidad de Oviedo Campus de Gijón Spain Department of Mathematics and Statistics Missouri University of Science and Technology RollaMO United States Department of Mathematical Science Carnegie Mellon University PittsburghPA United States

In [ESAIM: M2AN, 54(2020), 2229-2264], we proposed an HDG method to approximate the solution of a tangential boundary control problem for the Stokes equations and obtained an optimal convergence rate for the optimal control that reflects its global regularity. However, the error estimates depend on the pressure, and the velocity is not divergence free. The importance of pressure-robust numerical methods for fluids was addressed by John et al. [SIAM Review, 59(2017), 492-544]. In this work, we devise a new HDG method to approximate the solution of the Stokes tangential boundary control problem;the HDG method is also of independent interest for solving the Stokes equations. This scheme yields a H(div) conforming, globally divergence free, and pressure-robust solution. To the best of our knowledge, this is the first time such a numerical scheme has been obtained for an optimal boundary control problem for the Stokes equations. We also provide numerical experiments to show the performance of the new HDG method and the advantage over the non pressure-robust *** Codes 35Q35, 49M25, 65N30 Copyright © 2022, The Authors. All rights reserved.

关键词： Numerical methods

Enhancing customers' knowledge and decision making using augmented reality 28

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Enhancing customers' knowledge and decision making using aug...

28th International Conference on Computers in Education, ICCE 2020

作者： Boonrat, Wisanoo Vaidya, Vimita Baghaei, Nilufar Sharifzadeh, Hamid Ahmed, Ali Casey, John Department of Information Technology Otago Polytechnic Auckland Campus New Zealand School of Natural and Computational Sciences Massey University Auckland New Zealand School of Computing Unitec Institute of Technology New Zealand School of Engineering and Computer Science Victoria University of Wellington New Zealand

ISBN: (纸本)9789869721455

Augmented reality has seen massive success in recent years as it provides an opportunity for a seamless and rich user interaction with the real world. Recent studies have shown augmented and virtual reality can play a significant role in the future of retail. Innovations can help customers make good choices and can improve their confidence and satisfaction in their purchasing decisions. It also reduces the physical interaction between customers and store especially during lockdowns (i.e. during pandemics such as COVID-19). This paper presents ARiel, an augmented reality application for mobile commerce (m-commerce), enabling customers to turn catalogued items into 3D animated models. It was developed using Google's ARCore platform. Customers can try on products such as jewellery or watches using their mobile phones without being physically present in the retail shop. Data about their purchasing decisions are logged in a database. We describe the process of designing and implementing ARiel and the outcome of an evaluation using Nielsen's ten usability heuristics. We also outline our plan for future work. © ICCE 2020 - 28th International Conference on Computers in Education, Proceedings. All rights reserved.

关键词： Augmented reality