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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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Wetzel’s sector covers unit arcs

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arXiv 2019年

作者： Panraksa, Chatchawan Wichiramala, Wacharin Mathematics Program Science Division Mahidol University International College 999 Phutthamonthon 4 Road NakhonpathomSalaya73170 Thailand Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University 254 Phayathai Road BangkokPathumwan10330 Thailand

We settle J. Wetzel’s 1970’s conjecture and show that a 30◦ circular sector of unit radius can accommodate every planar arc of unit length. Leo Moser asked in 1966 for the smallest (convex) region in the plane that can accommodate each arc of unit length. With area π/12, this sector is the smallest such set presently known. Moser’s question has prompted a multitude of papers on related problems over the past 50 years, most remaining *** Codes 52A38, 51N05, 51M99 Copyright © 2019, The Authors. All rights reserved.

关键词： Set theory

Control the Water wheel with the Internet of Things 1

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Control the Water wheel with the Internet of Things

1st International Conference of SNIKOM 2018, ICoSNIKOM 2018

作者： Azmi, Zulfian Zarlis, Muhammad Mawengkang, Herman Efendi, Syahril Computer Science Universitas Sumatera Utara Indonesia Program Pasca Sarjana Doktoral Ilmu Komputer Universitas Sumatera Utara Padang Bulan USU Medan Indonesia Department of Mathematics Universitas Sumatera Utara Indonesia Sarjana Doktoral Ilmu Komputer Universitas Sumatera Utara Padang Bulan USU Medan Indonesia

The waterwheel is a component of the spinning water that energizes the rotating axis. Waterwheel is a means to convert water energy into mechanical energy in the form of torque on the shaft of the mill. One of the functions of water is to improve water quality. But the use of waterwheels manually is inefficient, because the mill works continuously even though the water quality is good. So it takes intelligent algorithm to be able to produce waterwheels that can benefit the local community for the needs of high protein foods. By adjusting some variables in determining water quality to improve the water quality of shrimp habitat, consisting of: water pH, water temperature, disoolved oxygen and salinity. And in uncertainty input from existing parameters can form a probability distribution that determines water quality and the movement of the mill. The sensor reading results into a reference microcontroller in sending PWM signals on the boost converter as DC motor drivers to run waterwheels slowly or quickly based on inputs. And with the Internet of Things (IoT) technology will make it easier to control, more practical, effective and efficient. © Published under licence by IOP Publishing Ltd.

关键词： Water quality

The Diffuse Ionized Gas of the Large Magellanic Cloud

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arXiv 2023年

作者： Smart, B.M. Haffner, L.M. Barger, K.A. Ciampa, D.A. Hill, A.S. Krishnarao, D. Madsen, G.J. Department of Astronomy University of Washington SeattleWA98195 United States Department of Physics Astronomy and Mathematics University of Hertfordshire HatfieldAL10 9AB United Kingdom Department of Astronomy University of Wisconsin-Madison MadisonWI53706 United States Department of Physical Sciences Embry-Riddle Aeronautical University Daytona BeachFL32114-3900 United States Department of Physics & Astronomy Texas Christian University Fort WorthTX76129 United States Department of Computer Science Math Physics and Statistics University of British Columbia Okanagan Campus KelownaBCV1V 1V7 Canada Space Science Institute BoulderCO80301 United States Dominion Radio Astrophysical Observatory Herzberg Program in Astronomy and Astrophysics National Research Council Canada PentictonBC Canada NSF Astronomy and Astrophysics Postdoctoral Fellow Johns Hopkins University BaltimoreMD21218 United States Department of Physics Colorado College Colorado SpringsCO United States Space Telescope Science Institute BaltimoreMD21218 United States Institute of Astronomy University of Cambridge Madingley Road CambridgeCB3 0HA United Kingdom

The Large Magellanic Cloud (LMC) has an extensive Hα emission halo that traces an extended, warm ionized component of its interstellar medium. Using the Wisconsin Hα Mapper (WHAM) telescope, we present the first kinematic Hα survey of an extensive region around the LMC, from ( b) = (264◦. 5, −45◦. 5) to (295◦. 5, −19◦. 5), covering +150 ≤ vLSR ≤ +390 km s−1. We find that ionized hydrogen exists throughout the galaxy and extends several degrees beyond detected neutral hydrogen emission (log (NH i/cm−2 ) ≈ 18.3) as traced by 21-cm in current surveys. Using the column density structure of the neutral gas and stellar line-of-sight depths as a guide, we estimate the upper limit mass of the ionized component of the LMC to be roughly Mionized ≈ (0.6−1.8)×109 M☉, which is comparable to the total neutral atomic gas mass in the same region (Mneutral ≈ 0.75 − 0.85 × 109 M☉). Considering only the atomic phases, we find Mionized/Mionized+neutral, to be 46%–68% throughout the LMC and its extended halo. Additionally, we find an ionized gas cloud that extends off of the LMC at ( b) ≈ (285◦, −28◦) into a region previously identified as the Leading Arm complex. This gas is moving at a similar line-of-sight velocity as the LMC and has Mionized/Mionized+neutral = 13%–51%. This study, combined with previous studies of the SMC and extended structures of the Magellanic Clouds, continues to suggest that warm, ionized gas is as massive and dynamically-important as the neutral gas in the Magellanic System. © 2023, CC BY.

关键词： Galaxies

The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

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arXiv 2023年

作者： Ma, Jun Xie, Ronald Ayyadhury, Shamini Ge, Cheng Gupta, Anubha Gupta, Ritu Gu, Song Zhang, Yao Lee, Gihun Kim, Joonkee Lou, Wei Li, Haofeng Upschulte, Eric Dickscheid, Timo de Almeida, José Guilherme Wang, Yixin Han, Lin Yang, Xin Labagnara, Marco Gligorovski, Vojislav Scheder, Maxime Rahi, Sahand Jamal Kempster, Carly Pollitt, Alice Espinosa, Leon Mignot, Tâm Middeke, Jan Moritz Eckardt, Jan-Niklas Li, Wangkai Li, Zhaoyang Cai, Xiaochen Bai, Bizhe Greenwald, Noah F. Van Valen, David Weisbart, Erin Cimini, Beth A. Cheung, Trevor Brück, Oscar Bader, Gary D. Wang, Bo Peter Munk Cardiac Centre University Health Network TorontoON Canada Department of Laboratory Medicine and Pathobiology University of Toronto TorontoON Canada Vector Institute TorontoON Canada Department of Molecular Genetics University of Toronto TorontoON Canada Donnelly Centre University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada School of Medicine and Pharmacy Ocean University of China Qingdao China New Delhi India Laboratory Oncology Dr. BRA-IRCH All India Institute of Medical Sciences New Delhi India Department of Image Reconstruction Nanjing Anke Medical Technology Co. Ltd. Nanjing China Shanghai Artificial Intelligence Laboratory Shanghai China Graduate School of AI KAIST Seoul Korea Republic of Shenzhen Research Institute of Big Data Shenzhen China Shenzhen China Helmholtz AI Research Center Jülich Jülich Germany Faculty of Mathematics and Natural Sciences Institute of Computer Science Heinrich Heine University Düsseldorf Düsseldorf Germany Hinxton United Kingdom Champalimaud Foundation - Centre for the Unknown Lisbon Portugal Department of Bioengineering Stanford University Palo AltoCA United States Tandon School of Engineering New York University New YorkNY United States School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Lausanne Switzerland School of Biological Sciences University of Reading Reading United Kingdom Laboratoire de Chimie Bactérienne CNRS Université Aix Marseille UMR Institut de Microbiologie de la Méditerranée Marseille France Department of Internal Medicine I University Hospital Dresden Technical University Dresden Dresden Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany Department of Automation University of Science and Technology of China Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei Chi

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging. © 2023, CC BY-NC-ND.

关键词： Deep learning

UNTANGLING HIGH-ORDER MESHES BASED ON SIGNED ANGLES 28

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UNTANGLING HIGH-ORDER MESHES BASED ON SIGNED ANGLES

28th International Meshing Roundtable, IMR 2019

作者： Stees, Mike Dotzel, Myra Shontz, Suzanne M. Department of Electrical Engineering and Computer Science Information and Telecommunication Technology Center University of Kansas 1520 W. 15th Street LawrenceKS66045 United States Department of Electrical Engineering and Computer Science Department of Mathematics Information and Telecommunication Technology Center University of Kansas 1520 W. 15th Street LawrenceKS66045 United States Department of Electrical Engineering and Computer Science Bioengineering Program Information and Telecommunication Technology Center University of Kansas 1520 W. 15th Street LawrenceKS66045 United States

ISBN: (纸本)9781733489003

One challenge in the generation of high-order meshes is that mesh tangling can occur as a consequence of moving the new boundary nodes to the true curved boundary. In this paper, we propose a new optimization-based method that uses signed angles to untangle invalid second- and third-order triangular meshes. Our proposed method consists of two passes. In the first pass, we loop over each high-order interior edge node and minimize an objective function based on the signed angles of the pair of triangles that share the node. In the second pass, we loop over face nodes and move them to the mean of the high-order nodes of the triangle to which the face node belongs. We present several numerical examples in two dimensions with second- and third-order elements that demonstrate the capabilities of our method for untangling invalid meshes. © 2019 Proceedings of the 28th International Meshing Roundtable, IMR 2019. All rights reserved.

关键词： Numerical methods

Counting Roots of a Polynomial in a Convex Compact Region by Means of Winding Number Calculation via Sampling

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arXiv 2019年

作者： Zaderman, Vitaly Zhao, Liang Ph.D. Program in Mathematics Graduate Center of the City University of New York New YorkNY10016 United States Department of Computer Science

In this paper, we propose a novel efficient algorithm for calculating winding numbers, aiming at counting the number of roots of a given polynomial in a convex region on the complex plane. This algorithm can be used for counting and exclusion tests in a subdivision algorithms for polynomial root-finding, and would be especially useful in application scenarios where high-precision polynomial coefficients are hard to obtain but we succeed with counting already by using polynomial evaluation with lower precision. We provide the pseudo code of the algorithm, proof of its correctness as well as estimation of its complexity. Copyright © 2019, The Authors. All rights reserved.

关键词： Winding

Implementation of Various Artificial Intelligence Approach for Prediction and Recommendation of Personality Disorder Patient

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Journal of Physics: Conference Series 2021年第1期1751卷

作者： H Sulistiani K Muludi A Syarif Doctoral Program of Mathematics and Natural Sciences Faculty University of Lampung Jl. Sumantri Brojonegoro No. 1 Bandar Lampung Indonesia. Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Jl. ZA. Pagaralam No. 9-11 Bandar Lampung Indonesia. Department of Computer Science Faculty of Mathematics and Science University of Lampung Jl. Sumantri Brojonegoro No. 1 Bandar Lampung Indonesia.

Personality disorder is known as chronic psychological disorders. It is a serious problem of the individual character and behavior that affect work, family and social life of a person. In many cases, the possibility of people do not realize that they have a personality disorder as a way of thinking and behaving seems natural to the patient, and the patient may blame others. To diagnose a personality disorder early, it is necessary to develop a system that is able to predict personality disorders and recommendation type of therapy patients should undergo. Artificial Intelligence is a technique that is very popular today. Various kinds of approaches and algorithms can be applied in the world of health, such as expert systems, neural networks and fuzzy logic. The aim of this study is to assess the artificial intelligence approach in predicting and recommending the type of therapy for patients with personality disorders.

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Ultra-Efficient Resistance Switching between Charge Ordered Phases in 1T-TaS2 with a Single Picosecond Electrical Pulse

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arXiv 2022年

作者： Venturini, Rok Mraz, Anže Vaskivskyi, Igor Vaskivskyi, Yevhenii Svetin, Damjan Mertelj, Tomaž Pavlovič, Leon Cheng, Jing Chen, Genyu Amarasinghe, Priyanthi Qadri, Syed B. Trivedi, Sudhir B. Sobolewski, Roman Mihailovic, Dragan Jožef Stefan Institute Jamova 39 LjubljanaSI-1000 Slovenia Faculty of Mathematics and Physics University of Ljubljana Jadranska 19 LjubljanaSI-1000 Slovenia Faculty for Electrical Engineering University of Ljubljana Tržaška 25 LjubljanaSI-1000 Slovenia CENN Nanocenter Jamova 39 LjubljanaSI-1000 Slovenia ELEP Electronics LjubljanaSI-1000 Slovenia Materials Science Program Laboratory for Laser Energetics University of Rochester New York14627 United States Brimrose Technology Corporation SparksMD21152 United States U.S. Naval Research Laboratory WashingtonDC United States Department of Electrical and Computer Engineering Department of Physics and Astronomy University of Rochester New York14627 United States

Progress in high-performance computing demands significant advances in memory technology. Among novel memory technologies that promise efficient device operation on a sub-ns timescale, resistance switching between charge ordered phases of 1T-TaS2 has shown to be potentially useful for development of high-speed, energy efficient non-volatile memory devices. Measurement of the electrical operation of such devices in the picosecond regime is technically challenging and hitherto still largely unexplored. Here we use an optoelectronic "laboratory-on-a-chip" experiment for measurements of ultrafast memory switching, enabling accurate measurement of electrical switching parameters with 100 fs temporal resolution. Photoexcitation and electro-optic sampling on a (Cd,Mn)Te substrate are used to generate and, subsequently, measure electrical pulse propagation, with intra-band excitation and sub-gap probing, respectively. We demonstrate high contrast non-volatile resistance switching from high to low resistance states of a 1T-TaS2 device using single sub-2ps electrical pulses. Using detailed modeling we find that the switching energy density per unit area is exceptionally small, EA = 9.4 fJ/µm2. The speed and energy efficiency of an electronic "write" process, place the 1T-TaS2 devices into a category of their own among new generation non-volatile memory devices. Copyright © 2022, The Authors. All rights reserved.

关键词： Switching