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Emergent Dimer-Model Topological Order and Quasiparticle Excitations in Liquid Crystals: Combinatorial Vortex Lattices

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Physical Review X 2025年第2期15卷 021084-021084页

作者： Cuiling Meng Jin-Sheng Wu Žiga Kos Jörn Dunkel Cristiano Nisoli Ivan I. Smalyukh Department of Physics and Chemical Physics Program University of Colorado Boulder Colorado 80309 USA International Institute for Sustainability with Knotted Chiral Meta Matter (WPI-SKCM) Hiroshima University Higashihiroshima Hiroshima Japan Department of Mathematics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Faculty of Mathematics and Physics University of Ljubljana Ljubljana Slovenia Department of Condensed Matter Physics Jožef Stefan Institute Ljubljana Slovenia Theoretical Division Physics of Condensed Matter and Complex Systems and Center For Nonlinear Studies Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program University of Colorado Boulder Colorado 80309 USA Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado Boulder Colorado 80309 USA

Liquid crystals have proven to provide a versatile experimental and theoretical platform for studying topological objects such as vortices, skyrmions, and hopfions. In parallel, in hard condensed matter physics, the concept of topological phases and topological order has been introduced in the context of spin liquids to investigate emergent phenomena like quantum Hall effects and high-temperature superconductivity. Here, we bridge these two seemingly disparate perspectives on topology in physics. Combining experiments and simulations, we show how topological defects in liquid crystals can be used as versatile building blocks to create complex, highly degenerate topological phases, which we refer to as “combinatorial vortex lattices” (CVLs). CVLs exhibit extensive residual entropy and support locally stable quasiparticle excitations in the form of charge-conserving topological monopoles, which can act as mobile information carriers and be linked via Dirac strings. CVLs can be rewritten and reconfigured on demand, endowed with various symmetries, and modified through laser-induced topological surgery—an essential capability for information storage and retrieval. We demonstrate experimentally the realization, stability, and precise optical manipulation of CVLs, thus opening new avenues for understanding and technologically exploiting higher-hierarchy topology in liquid crystals and other ordered media.

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Observation of anti-parity-time-symmetry, phase transitions and exceptional points in an optical fibre

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arXiv 2020年

作者： Bergman, Arik Duggan, Robert Sharma, Kavita Tur, Moshe Zadok, Avi Alù, Andrea Faculty of Engineering Institute for Nano-Technology and Advanced Materials Bar-Ilan University Ramat-Gan5290002 Israel Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States School of Electrical Engineering Tel-Aviv University Tel-Aviv6997801 Israel Physics Program Graduate Center City University of New York New YorkNY10026 United States

The exotic physics emerging in non-Hermitian systems with balanced distributions of gain and loss has drawn a great deal of attention in recent years. These systems exhibit phase transitions and exceptional point singularities in their spectra, at which eigen-values and eigen-modes coalesce and the overall dimensionality is reduced. Among several peculiar phenomena observed at exceptional points, an especially intriguing property, with relevant practical potential, consists in the inherently enhanced sensitivity to small-scale perturbations. So far, however, these principles have been implemented at the expenses of precise fabrication and tuning requirements, involving tailored nano-structured devices with controlled distributions of optical gain and loss. In this work, anti-parity-time symmetric phase transitions and exceptional point singularities are demonstrated in a single strand of standard single-mode telecommunication fibre, using a setup consisting of entirely of off-the-shelf components. Two propagating signals are amplified and coupled through stimulated Brillouin scattering, which makes the process non-Hermitian and enables exquisite control over gain and loss. Singular response to small variations around the exceptional point and topological features arising around this singularity are experimentally demonstrated with large precision, enabling robustly enhanced spectral response to small-scale changes in the Brillouin frequency shift. Our findings open exciting opportunities for the exploration of non-Hermitian phenomena over a table-top setup, with straightforward extensions to higher-order Hamiltonians and applications in quantum optics, nanophotonics and sensing. Copyright © 2020, The Authors. All rights reserved.

关键词： Optical fibers

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

Back propagation neural network experiment on team matchmaking MOBA game 1

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Back propagation neural network experiment on team matchmaki...

1st international Conference on Information and Communications Technology, ICOIACT 2018

作者： Tanuar, Evawaty Abbas, Bahtiar Saleh Trisetyarso, Agung Kang, Chul-Ho Gaol, Ford Lumban Suparta, Wayan Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Electrical Engineering Sanata Dharma University Yogyakarta55282 Indonesia

ISBN: (纸本)9781538609545

Backpropagation is one of the famous method for learning, Implementing Backpropagation techniques in games is part of AI in game. This paper aim to analyzed the best team composition in a Moba Game type in learning using neural network. Mobile Legend: Bang Bang is one of MOBA game for mobile phone. In this experiment, the 2 hidden layers back-propagation neural network algorithm is used to analyze the Mobile Legend game. 5000 training steps was done to reach the stability. This also a way of learning to find the best composition in a team played. Research in area AI and game is very wide and open, a huge opportunity to be explore in future. The objective of this research is to produce the good combination of team which can be resulted in a greater winning chance. © 2018 IEEE.

关键词： Backpropagation

Biphenylene monolayer as a two-dimensional nonbenzenoid carbon allotrope: A first-principles study

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arXiv 2021年

作者： Bafekry, Asadolah Faraji, M. Fadlallah, M.M. Jappor, H.R. Karbasizadeh, S. Ghergherehchi, M. Gogova, D. Department of Radiation Application Shahid Beheshti University Tehran*** Iran Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Department of Physics Faculty of Science Benha University Benha13518 Egypt Department of Physics College of Education for Pure Sciences University of Babylon Hilla Iraq Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Physics University of Oslo P.O. Box 1048 Blindern Oslo Norway

In a very recent accomplishment, the two-dimensional form of Biphenylene network (BPN) has been successfully fabricated [Fan et al., science, 372, 852-856 (2021)]. Motivated by this exciting experimental result on 2D layered BPN structure, herein we perform detailed density functional theory-based first-principles calculations, for the first time, in order to gain insight into the structural, electronic and optical properties of this promising nanomaterial. Our theoretical results reveal the BPN structure is constructed from three rings of tetragon, hexagon and octagon, meanwhile the electron localization function shows very strong bonds between the C atoms in the structure. The dynamical stability of BPN is verified via the phonon band dispersion calculations. The mechanical properties reveal the brittle behavior of BPN monolayer. The Young's modulus has been computed as 0.1 TPa, which is smaller than the corresponding value of graphene, while the Poisson's ratio determined to be 0.26 is larger than that of graphene. The band structure is evaluated to show the electronic features of the material;determining the BPN monolayer as metallic with a band gap of zero. The optical properties (real and imaginary parts of the dielectric function, and the absorption spectrum) uncover BPN as an insulator along the zz direction, while owning metallic properties in xx and yy directions. We anticipate that our discoveries will pave the way to the successful implementation of this new 2D allotrope of carbon in advanced nanoelectronics. © 2021, CC BY.

关键词： Monolayers

Tunable nanophotonics enabled by chalcogenide phase-change materials

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arXiv 2020年

作者： Abdollahramezani, Sajjad Hemmatyar, Omid Taghinejad, Hossein Krasnok, Alex Kiarashinejad, Yashar Zandehshahvar, Mohammadreza Alù, Andrea Adibi, Ali School of Electrical and Computer Engineering Georgia Institute of Technology 778 Atlantic Drive NW AtlantaGA30332-0250 United States 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

Nanophotonics has garnered intensive attention due to its unique capabilities in molding the flow of light in the subwavelength regime. Metasurfaces (MSs) and photonic integrated circuits (PICs) enable the realization of mass-producible, cost-effective, and highly efficient flat optical components for imaging, sensing, and communications. In order to enable nanophotonics with multi-purpose functionalities, chalcogenide phase-change materials (PCMs) have been introduced as a promising platform for tunable and reconfigurable nanophotonic frameworks. Integration of non-volatile chalcogenide PCMs with unique properties such as drastic optical contrasts, fast switching speeds, and long-term stability grants substantial reconfiguration to the more conventional static nanophotonic platforms. In this review, we discuss state-of-the-art developments as well as emerging trends in tunable MSs and PICs using chalcogenide PCMs. We outline the unique material properties, structural transformation, electro-optic, and thermo-optic effects of well-established classes of chalcogenide PCMs. The emerging deep learning-based approaches for the optimization of reconfigurable MSs and the analysis of light-matter interactions are also discussed. The review is concluded by discussing existing challenges in the realization of adjustable nanophotonics and a perspective on the possible developments in this promising area. Copyright © 2020, The Authors. All rights reserved.

关键词： Phase change materials

THz Generation Control in Fe/X Spintronic Multilayers by chemical bonding at epitaxial Fe/GaAs(001) interfaces

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THz Generation Control in Fe/X Spintronic Multilayers by che...

Conference on Lasers and Electro-Optics (CLEO)

作者： Roman Adam Genyu Chen Daniel E. Bürgler Derang Cao Sarah Heidtfeld Debamitra Chakraborty Jing Cheng Ivan Komissarov Hilde Hardtdegen Martin Mikulics Claus M. Schneider Roman Sobolewski Research Centre Jülich Peter Grünberg Institute (PGI-6) Jülich Germany Materials Science Graduate Program University of Rochester Rochester New York USA Laboratory for Laser Energetics University of Rochester Rochester New York USA College of Physics Center for Marine Observation and Communications Qingdao University Qingdao China Department of Electrical and Computer Engineering University of Rochester Rochester New York USA Research Centre Jülich Ernst Ruska Centre for Microscopy and Spectroscopy with Electrons Jülich Germany Department of Physics University of California Davis Davis California USA

We report an additional degree of control of THz transients in Fe/X spintronic emitters grown on GaAs(001). We ascribe the field-independent enhancement of the THz amplitude to specific chemical bonding at the epitaxi... 详细信息

ISBN: (纸本)9781943580910

关键词： Electromagnetic radiation Free electron lasers Gallium arsenide Magnetic fields Terahertz generation Ultrafast lasers

Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

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arXiv 2022年

作者： Aubry, Jean-Francois Bates, Oscar Boehm, Christian Pauly, Kim Butts Christensen, Douglas Cueto, Carlos Gélat, Pierre Guasch, Lluis Jaros, Jiri Jing, Yun Jones, Rebecca Li, Ningrui Marty, Patrick Montanaro, Hazael Neufeld, Esra Pichardo, Samuel Pinton, Gianmarco Pulkkinen, Aki Stanziola, Antonio Thielscher, Axel Treeby, Bradley Van't Wout, Elwin Physics for Medicine Paris INSERM U1273 ESPCI Paris PSL University CNRS UMR 8063 France Department of Bioengineering Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Institute of Geophysics ETH Zürich Sonneggstrasse 5 Zürich8092 Switzerland Department of Radiology Stanford University StanfordCA United States Department of Biomedical Engineering Department of Electrical and Computer Engineering University of Utah United States Department of Surgical Biotechnology Division of Surgery and Interventional Science University College London LondonNW3 2PF United Kingdom Earth Science and Engineering Department Imperial College London London United Kingdom Centre of Excellence IT4Innovations Faculty of Information Technology Brno University of Technology Bozetechova 2 Brno612 00 Czech Republic Graduate Program in Acoustics The Pennsylvania State University University Park PA16802 United States Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill North Carolina State University NC United States Department of Electrical Engineering Stanford University StanfordCA United States Zurich Switzerland Laboratory for Acoustics / Noise control Empa Swiss Federal Laboratories for Materials Science and Technology Dubendorf Switzerland Zurich Switzerland Radiology and Clinical Neurosciences Departments Cumming School of Medicine University of Calgary Canada Department of Applied Physics University of Eastern Finland Kuopio70211 Finland Department of Medical Physics and Biomedical Engineering University College London Gower Street LondonWC1E 6BT United Kingdom Technical University of Denmark Denmark Danish Research Center for Magnetic Resonance Copenhagen University Hospital Hvidovre Denmark Institute for Mathematical and Computational Engineering School of Engineering and Faculty of Mathematics Pontificia Universidad Catolica de Chile Santiago Chile

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular-spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons. Copyright © 2022, The Authors. All rights reserved.

关键词： Bone

Broadband delay lines and nonreciprocal resonances in unidirectional waveguides

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Physical Review B 2019年第2期100卷 020303(R)-020303(R)页

作者： Sander A. Mann Dimitrios L. Sounas Andrea Alù Photonics Initiative Advanced Science Research Center City University of New York New York 10031 USA Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Department of Electrical and Computer Engineering Wayne State University Detroit Michigan 48202 USA Physics Program Graduate Center City University of New York New York 10016 USA Department of Electrical Engineering City College of The City University of New York New York 10031 USA

Slow-light waveguides play an important role in optical pulse delay lines, but are practically limited by disorder-induced attenuation. Topological edge states, unidirectional and robust against disorder, have been proposed as a way to address this issue. Here, we study the transmission phase and pulse propagation dynamics through unidirectional systems in the presence of strong discontinuities. We first investigate a magnetically biased slow-light channel, demonstrating broadband pulse delays in small footprints. We uncover a nonreciprocal etalonlike resonance, sustained by propagating forward and evanescent backward modes, affecting pulse propagation and delay. We then show the existence of these features in topologically protected edge states, highlighting their universality. These exotic resonances provide a new degree of freedom in unidirectional waveguides to engineer their response, and they may therefore prove highly useful in various nanophotonic applications.

关键词： Plasmonics Topological effects in photonic systems Topological insulators Topological materials Waveguides Lorentz symmetry