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Neural Computing and Applications 2024年第21期36卷 13373-13373页

作者： Massaoudi, Ayman Echouchene, Fraj Ben Ayed, Mossaad Berguiga, Abdelwahed Harchay, Ahlem Al-Ghamdi, Sara Belmabrouk, Hafedh Department of Computer Science College of Science and Arts in Gurayat Jouf University Sakakah Saudi Arabia Olive Research Center Jouf University Sakakah Saudi Arabia Laboratory of Electronics and Microelectronics Faculty of Science of Monastir University of Monastir Monastir Tunisia Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia Department of Industrial Electronics ENISo University of Sousse Sousse Tunisia Department of Computer Science College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia Department of Physics College of Science Majmaah University Al Majma’ah Saudi Arabia

Roadmap for phase change materials in photonics and beyond (vol 26, 107946, 2023)

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Iscience 2023年第12期26卷 107946页

作者： Prabhathan, Patinharekandy Sreekanth, Kandammathe Valiyaveedu Teng, Jinghua Ko, Joo Hwan Yoo, Young Jin Jeong, Hyeon-Ho Lee, Yubin Zhang, Shoujun Cao, Tun Popescu, Cosmin-Constantin Mills, Brian Gu, Tian Fang, Zhuoran Chen, Rui Tong, Hao Wang, Yi He, Qiang Lu, Yitao Liu, Zhiyuan Yu, Han Mandal, Avik Cui, Yihao Ansari, Abbas Sheikh Bhingardive, Viraj Kang, Myungkoo Lai, Choon Kong Merklein, Moritz Mueller, Maximilian J. Song, Young Min Tian, Zhen Hu, Juejun Losurdo, Maria Majumdar, Arka Miao, Xiangshui Chen, Xiao Gholipour, Behrad Richardson, Kathleen A. Eggleton, Benjamin J. Sharda, Kanudha Wuttig, Matthias Singh, Ranjan Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore 637371 Singapore Centre for Disruptive Photonic Technologies The Photonic Institute 50 Nanyang Avenue Singapore 639798 Singapore Institute of Materials Research and Engineering (IMRE) Agency for Science Technology and Research (A∗STAR) 2 Fusionopolis Way Innovis #08-03 Singapore 138634 Republic of Singapore School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju 61005 Republic of Korea School of Materials Science and Engineering Gwangju Institute of Science and Technology Gwangju 61005 Republic of Korea DELL Center for Terahertz Waves and College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Optoelectronic Information Technology (Ministry of Education of China) Tianjin University Tianjin 300072 China DELL School of Optoelectronic Engineering and Instrumentation Science Dalian University of Technology Dalian 116024 China Department of Materials Science &amp Engineering Massachusetts Institute of Technology Cambridge MA USA Materials Research Laboratory Massachusetts Institute of Technology Cambridge MA USA Department of Electrical &amp Computer Engineering University of Washington Washington Seattle USA Wuhan National Research Center for Optoelectronics School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan China Institute of Advanced Materials Beijing Normal University Beijing 100875 China Nanoscale Optics Lab ECE Department University of Alberta Edmonton Canada CREOL College of Optics and Photonics University of Central Florida Orlando FL USA Institute of Photonics and Optical Science (IPOS) School of Physics The University of Sydney New South Wales NSW 2006 Australia The University of Sydney Nano Institute (Sydney Nano) The University of Sydney New South Wales NSW 2006 Australia Insti

Phase Change Materials (PCMs) have demonstrated tremendous potential as a platform for achieving diverse functionalities in active and reconfigurable micro-nanophotonic devices across the electromagnetic spectrum, ranging from terahertz to visible frequencies. This comprehensive roadmap reviews the material and device aspects of PCMs, and their diverse applications in active and reconfigurable micro-nanophotonic devices across the electromagnetic spectrum. It discusses various device configurations and optimization techniques, including deep learning-based metasurface design. The integration of PCMs with Photonic Integrated Circuits and advanced electric-driven PCMs are explored. PCMs hold great promise for multifunctional device development, including applications in non-volatile memory, optical data storage, photonics, energy harvesting, biomedical technology, neuromorphic computing, thermal management, and flexible electronics.

关键词： physics applied physics Materials application

Localized Virtual Purification

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arXiv 2023年

作者： Hakoshima, Hideaki Endo, Suguru Yamamoto, Kaoru Matsuzaki, Yuichiro Yoshioka, Nobuyuki Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Osaka Toyonaka560-8531 Japan Center for Quantum Information and Quantum Biology Osaka University 1-2 Machikaneyama Osaka Toyonaka560-0043 Japan NTT Computer and Data Science Laboratories NTT Corporation Musashino180-8585 Japan JST PRESTO 4-1-8 Honcho Saitama Kawaguchi332-0012 Japan Department of Electrical Electronic and Communication Engineering Faculty of Science and Engineering Chuo University Bunkyo-ku 1-13-27 Kasuga Tokyo112-8551 Japan Department of Applied Physics University of Tokyo Bunkyo-ku 7-3-1 Hongo Tokyo113-8656 Japan Saitama Wako-shi351-0198 Japan

Analog and digital quantum simulators can efficiently simulate quantum many-body systems that appear in natural phenomena. However, experimental limitations of near-term devices still make it challenging to perform the entire process of quantum simulation. The purification-based quantum simulation methods can alleviate the limitations in experiments such as the cooling temperature and noise from the environment, while this method has the drawback that it requires global entangled measurement with a prohibitively large number of measurements that scales exponentially with the system size. In this Letter, we propose that we can overcome these problems by restricting the entangled measurements to the vicinity of the local observables to be measured, when the locality of the system can be exploited. We provide theoretical guarantees that the global purification operation can be replaced with local operations under some conditions, in particular for the task of cooling and error mitigation. We furthermore give a numerical verification that the localized purification is valid even when conditions are not satisfied. Our method bridges the fundamental concept of locality with quantum simulators, and therefore expected to open a path to unexplored quantum many-body phenomena. Copyright © 2023, The Authors. All rights reserved.

关键词： Purification

One-Phase Temporal Fuzzy Utility Mining

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One-Phase Temporal Fuzzy Utility Mining

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Tzung-Pei Hong Cheng-Yu Lin Wei-Ming Huang Shu-Min Li Shyue-Liang Wang Jerry Chun-Wei Lin Department of Computer Science and Information Engineering National University of Kaohsiung Taiwan Department of Computer Science and Engineering National Sun Yat-sen University Taiwan Department of Computing Mathematics and Physics Western Norway University of Applied Science Norway

ISBN: (数字)9781728169323

ISBN: (纸本)9781728169330

Temporal utility mining is complicated than utility mining due to the time consideration. The former discusses the situation that different items may have different profit values and on-shelf time periods. In this paper, we handle the problem of temporal fuzzy utility mining, which simultaneously considers the temporal factor, purchased quantities, item profits and linguistic terms from a transaction database. In the past, we proposed a two-phase tree-based approach to solve this problem. In this paper, we further design a tree structure with less memory to store all the required information and with faster execution speed than the previous one. The experimental results show that the proposed method can get good performance on the execution efficiency and consumed memory size.

关键词： Itemsets Data mining computer science Upper bound Linguistics Memory management Fuzzy sets

Bulk-plasmon-mediated free-electron radiation beyond the conventional formation time

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arXiv 2022年

作者： Tay, Fuyang Lin, Xiao Shi, Xihang Chen, Hongsheng Kaminer, Ido Zhang, Baile Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJUHangzhou Global Science and Technology Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX77005 United States International Joint Innovation Center The Electromagnetics Academy Zhejiang University Zhejiang University Haining314400 China Department of Electrical Engineering Technion-Israel Institute of Technology Haifa32000 Israel Jinhua Institute of Zhejiang University Zhejiang University Jinhua321099 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University 637371 Singapore

Free-electron radiation is a fundamental photon emission process that is induced by fast-moving electrons interacting with optical media. Historically, it has been understood that, just like any other photon emission process, free-electron radiation must be constrained within a finite time interval known as the "formation time", whose concept is applicable to both Cherenkov radiation and transition radiation, the two basic mechanisms describing radiation from a bulk medium and from an interface, respectively. Here we reveal an alternative mechanism of free-electron radiation far beyond the previously defined formation time. It occurs when a fast electron crosses the interface between vacuum and a plasmonic medium supporting bulk plasmons. While emitted continuously from the crossing point on the interface — thus consistent with the features of transition radiation — the extra radiation beyond the conventional formation time is supported by a long tail of bulk plasmons following the electron’s trajectory deep into the plasmonic medium. Such a plasmonic tail mixes surface and bulk effects, and provides a sustained channel for electron-interface interaction. These results also settle the historical debate in Ferrell radiation, regarding whether it is a surface or bulk effect, from transition radiation or plasmonic oscillation. Copyright © 2022, The Authors. All rights reserved.

关键词： Plasmonics

Training of Physical Neural Networks

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arXiv 2024年

作者： Momeni, Ali Rahmani, Babak Scellier, Benjamin Wright, Logan G. McMahon, Peter L. Wanjura, Clara C. Li, Yuhang Skalli, Anas Berloff, Natalia G. Onodera, Tatsuhiro Oguz, Ilker Morichetti, Francesco del Hougne, Philipp Le Gallo, Manuel Sebastian, Abu Mirhoseini, Azalia Zhang, Cheng Marković, Danijela Brunner, Daniel Moser, Christophe Gigan, Sylvain Marquardt, Florian Ozcan, Aydogan Grollier, Julie Liu, Andrea J. Psaltis, Demetri Alù, Andrea Fleury, Romain Lausanne Switzerland Microsoft Research 198 Cambridge Science Park CambridgeCB4 0AB United Kingdom Rain AI San Francisco United States Department of Applied Physics Yale University CT United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Max Planck Institute for the Science of Light Staudtstraße 2 Erlangen91058 Germany Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States FEMTO-ST Institute Optics Department CNRS University Bourgogne Franche-Comté Besançon25030 Cedex France Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge United Kingdom NTT Physics and Informatics Laboratories NTT Research Inc. Sunnyvale United States Lausanne Switzerland Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Milan Italy Univ Rennes CNRS IETR UMR 6164 RennesF-35000 France IBM Research Europe– Zurich Rüschlikon8803 Switzerland Department of Computer Science Stanford University United States Google DeepMind 1600 Amphitheatre Parkway Mountain ViewCA94043 United States Unité Mixte de Physique CNRS/Thales CNRS Thales Université Paris-Saclay Palaiseau France Laboratoire Kastler Brossel Sorbonne Université École Normale Supérieure Collège de France CNRS UMR 8552 Paris France Laboratoire Albert Fert CNRS Thales UniversitéParis-Saclay Palaiseau91767 France Department of Physics and Astronomy University of Pennsylvania PhiladelphiaPA19104 United States Lausanne Switzerland Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research area with small-scale laboratory demonstrations, they are arguably one of the most underappreciated important opportunities in modern artificial intelligence (AI). Could we train AI models 1000x larger than current ones? Could we do this and also have them perform inference locally and privately on edge devices, such as smartphones or sensors? Research over the past few years has shown that the answer to all these questions is likely "textityes, with enough research": PNNs could one day radically change what is possible and practical for AI systems. To do this will however require rethinking both how AI models work, and how they are trained – primarily by considering the problems through the constraints of the underlying hardware physics. To train PNNs at large scale, many methods including backpropagation-based and backpropagation-free approaches are now being explored. These methods have various trade-offs, and so far no method has been shown to scale to the same scale and performance as the backpropagation algorithm widely used in deep learning today. However, this is rapidly changing, and a diverse ecosystem of training techniques provides clues for how PNNs may one day be utilized to create both more efficient realizations of current-scale AI models, and to enable unprecedented-scale models. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

Outcoupling Hyperbolic Modes from Aligned Carbon Nanotube Films

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Outcoupling Hyperbolic Modes from Aligned Carbon Nanotube Fi...

Conference on Lasers and Electro-Optics (CLEO)

作者： Bryant Jerome Ciril S. Prasad Jacques Doumani Oliver S. Dewey Andrey Baydin Matteo Pasquali Junichiro Kono Weilu Gao Alessandro Alabastri Gururaj V. Naik Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Chemical and Biomolecular Engineering Rice University Houston TX USA Smalley-Curl Institute Rice University Houston TX USA Department of Chemistry Rice University Houston TX USA Department of Materials Science and NanoEngineering Rice University Houston TX USA Department of Physics and Astronomy Rice University Houston TX USA Department of Electrical and Computer Engineering University of Utah Salt Lake City UT USA

Aligned carbon nanotube films make an excellent hyperbolic material plat-form in the infrared. Here, we experimentally demonstrate the presence of high-k modes in aligned carbon nanotube films and outcouple them to fr... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Films Carbon nanotubes Lasers and electrooptics Laser modes High-k dielectric materials Gratings Laser applications

Dynamics of the competition between two languages

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SeMA Journal 2020年第4期77卷 351-373页

作者： Tchendjeu, A. E. Tchahou Bowong, S. Tchitnga, R. Fotsin, H.B. Department of Computer Engineering National Higher Polytechnic Institute University of Bamenda PO Box 39 Bambili Cameroon Laboratory of Condensed Matters Electronics and Signal Processing (LAMACETS) Department of Physics Faculty of Science University of Dschang PO Box 63 Dschang Cameroon Research Group on Experimental and Applied Physics for Sustainable Development (EAPhySuD) Department of Physics Faculty of Science University of Dschang PO Box 63 Dschang Cameroon Laboratory of Applied Mathematics Department of Mathematics and Computer Science Faculty of Science University of Douala PO Box 24157 Douala Cameroon UMI 209 IRD/UPMC UMMISCO Bondy France LIRIMA Project Team GRIMCAPE Yaounde Cameroon The African Center of Excellence in Information and Communication Technologies (CETIC) University of Yaounde 1 Yaounde Cameroon Institute of Surface Chemistry and Catalysis University of Ulm Albert-Einstein-Allee 47 Ulm 89081 Germany

This paper reports a new kind of mathematical model for language competition dynamics using compartmental epidemiological modeling approach. The model describes the competition between two languages, say the predominant one called language 1, and the less spoken language 2, both in the same community. We distinguish three groups of population building the concerned community: one majority speaking language 1, one minority speaking language 2 and a last minority speaking neither language 1 nor language 2. The study of the proposed model includes an analysis of the evolution of the number of speakers over time. This model predicts that language 2 can inevitably disappear if the threshold parameter R is less than one. We show that our model is well-posed mathematically and linguistically. We also show that the model has basically two linguistic equilibrium points. A monolingual equilibrium point that corresponds to the case where only one language is spoken: some individuals speak only the language 1 and some others do speak neither language 1, nor language 2. A bilingual equilibrium point which corresponds to the case where all the languages are spoken: some individuals speak both languages 1 and 2, some others speak only language 1, while a third group does speak only language 2, and the last group speaks none of the two languages. In this bilingual equilibrium point, both languages coexist. Depending on the threshold parameter, we demonstrate the stability of these equilibria. The model presents on one hand, a direct bifurcation phenomenon, in which we have a stable equilibrium point without bilingual speakers when the associated basic reproduction number is less than one. On the other hand, it presents a stable bilingual equilibrium point when the number of associated basic reproductions is greater than one. The analysis of the overall sensitivity of the model is performed and the impact of the system parameters on the basic reproduction number was performed using

关键词： Bilingualism Compartmental modeling Dynamical system Language competition Stability

Noise propagation in hybrid tensor networks

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arXiv 2023年

作者： Harada, Hiroyuki Suzuki, Yasunari Yang, Bo Tokunaga, Yuuki Endo, Suguru Department of Applied Physics and Physico-Informatics Keio University Hiyoshi 3-14-1 Kohoku Yokohama223-8522 Japan NTT Computer and Data Science Laboratories NTT Corporation 3-9-11 Midori-cho Musashino-shi Tokyo180-8585 Japan LIP6 Sorbonne Université 4 Place Jussieu Paris75005 France Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama332-0012 Japan

The hybrid tensor network (HTN) method is a general framework allowing for the construction of an effective wavefunction with the combination of classical tensors and quantum tensors, i.e., amplitudes of quantum states. In particular, hybrid tree tensor networks (HTTNs) are very useful for simulating larger systems beyond the available size of the quantum hardware. However, while the realistic quantum states in NISQ hardware are highly likely to be noisy, this framework is formulated for pure states. In this work, as well as discussing the relevant methods, i.e., Deep VQE and entanglement forging under the framework of HTTNs, we investigate the noisy HTN states by introducing the expansion operator for providing the description of the expansion of the size of simulated quantum systems and the noise propagation. This framework enables the general tree HTN states to be explicitly represented and their physicality to be discussed. We also show that the expectation value of a measured observable exponentially vanishes with the number of contracted quantum tensors. Our work will lead to providing the noise-resilient construction of HTN states. Copyright © 2023, The Authors. All rights reserved.

关键词： Tensors

Electron mobility of SnO2 from first principles

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arXiv 2024年

作者： Wang, Amanda Bushick, Kyle Pant, Nick Lee, Woncheol Zhang, Xiao Leveillee, Joshua Giustino, Feliciano Poncé, Samuel Kioupakis, Emmanouil Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical and Computer Engineering University of Michigan Ann ArborMI48109 United States Oden Institute for Computational Engineering and Sciences The University of Texas at Austin AustinTX78712 United States Department of Physics The University of Texas at Austin AustinTX78712 United States European Theoretical Spectroscopy Facility Institute of Condensed Matter and Nanosciences Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-NeuveB-1348 Belgium WEL Research Institute Avenue Pasteur 6 Wavre1300 Belgium

The transparent conducting oxide SnO2 is a wide bandgap semiconductor that is easily n-type doped and widely used in various electronic and optoelectronic applications. Experimental reports of the electron mobility of this material vary widely depending on the growth conditions and doping concentrations. In this work, we calculate the electron mobility of SnO2 from first principles to examine the temperature- and doping-concentration dependence, and to elucidate the scattering mechanisms that limit transport. We include both electron-phonon scattering and electron-ionized impurity scattering to accurately model scattering in a doped semiconductor. We find a strongly anisotropic mobility that favors transport in the direction parallel to the c-axis. At room temperature and intrinsic carrier concentrations, the low-energy polar-optical phonon modes dominate scattering, while ionized-impurity scattering dominates above 1018 cm-3 Copyright © 2024, The Authors. All rights reserved.

关键词： Electron mobility