检索结果-内蒙古大学图书馆

Bayesian Inference analysis of jet quenching using inclusive jet and hadron suppression measurements

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Ehlers, R. Chen, Y. Mulligan, J. Ji, Y. Kumar, A. Mak, S. Jacobs, P.M. Majumder, A. Angerami, A. Arora, R. Bass, S.A. Datta, R. Du, L. Elfner, H. Fries, R.J. Gale, C. He, Y. Jacak, B.V. Jeon, S. Jonas, F. Kasper, L. Kordell II, M. Kunnawalkam-Elayavalli, R. Latessa, J. Lee, Y.-J. Lemmon, R. Luzum, M. Mankolli, A. Martin, C. Mehryar, H. Mengel, T. Nattrass, C. Norman, J. Parker, C. Paquet, J.-F. Putschke, J.H. Roch, H. Roland, G. Schenke, B. Schwiebert, L. Sengupta, A. Shen, C. Singh, M. Sirimanna, C. Soeder, D. Soltz, R.A. Soudi, I. Tachibana, Y. Velkovska, J. Vujanovic, G. Wang, X.-N. Wu, X. Zhao, W. Department of Physics University of California BerkeleyCA94270 United States Nuclear Science Division Lawrence Berkeley National Laboratory BerkeleyCA94270 United States Laboratory for Nuclear Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics and Astronomy Vanderbilt University NashvilleTN37235 United States Department of Statistical Science Duke University DurhamNC27708 United States Department of Physics University of Regina ReginaSKS4S 0A2 Canada Department of Physics McGill University MontréalQCH3A 2T8 Canada Department of Physics and Astronomy Wayne State University DetroitMI48201 United States Lawrence Livermore National Laboratory LivermoreCA94550 United States Department of Computer Science Wayne State University DetroitMI48202 United States Department of Physics Duke University DurhamNC27708 United States GSI Helmholtzzentrum für Schwerionenforschung Darmstadt64291 Germany Institute for Theoretical Physics Goethe University Frankfurt am Main60438 Germany Frankfurt Institute for Advanced Studies Frankfurt am Main60438 Germany Cyclotron Institute Texas A&M University College StationTX77843 United States Department of Physics and Astronomy Texas A&M University College StationTX77843 United States Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China Daresbury Laboratory Warrington Cheshire DaresburyWA44AD United Kingdom Instituto de Fisica Universidade de São Paulo C.P. 66318 SP São Paulo05315-970 Brazil Department of Physics and Astronomy University of Tennessee KnoxvilleTN37996 United States Oliver Lodge Laboratory University of Liverpool

The Jetscape Collaboration reports a new determination of the jet transport parameter q in the Quark-Gluon Plasma (QGP) using Bayesian Inference, incorporating all available inclusive hadron and jet yield suppression data measured in heavy-ion collisions at RHIC and the LHC. This multiobservable analysis extends the previously published Jetscape Bayesian Inference determination of q, which was based solely on a selection of inclusive hadron suppression data. Jetscape is a modular framework incorporating detailed dynamical models of QGP formation and evolution, and jet propagation and interaction in the QGP. Virtuality-dependent partonic energy loss in the QGP is modeled as a thermalized weakly-coupled plasma, with parameters determined from Bayesian calibration using soft-sector observables. This Bayesian calibration of q utilizes Active Learning, a machine-learning approach, for efficient exploitation of computing resources. The experimental data included in this analysis span a broad range in collision energy and centrality, and in transverse momentum. In order to explore the systematic dependence of the extracted parameter posterior distributions, several different calibrations are reported, based on combined jet and hadron data;on jet or hadron data separately;and on restricted kinematic or centrality ranges of the jet and hadron data. Tension is observed in comparison of these variations, providing new insights into the physics of jet transport in the QGP and its theoretical formulation. © 2024, CC BY.

关键词： Heavy ions

Adaptive unimodal cost volume filtering for deep stereo matching

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Zhang, Youmin Chen, Yimin Bai, Xiao Yu, Suihanjin Yu, Kun Li, Zhiwei Yang, Kuiyuan State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Jiangxi Research Institute Beihang University Beijing China DeepMotion

State-of-the-art deep learning based stereo matching approaches treat disparity estimation as a regression problem, where loss function is directly defined on true disparities and their estimated ones. However, disparity is just a byproduct of a matching process modeled by cost volume, while indirectly learning cost volume driven by disparity regression is prone to overfitting since the cost volume is under constrained. In this paper, we propose to directly add constraints to the cost volume by filtering cost volume with unimodal distribution peaked at true disparities. In addition, variances of the unimodal distributions for each pixel are estimated to explicitly model matching uncertainty under different contexts. The proposed architecture achieves state-of-the-art performance on Scene Flow and two KITTI stereo benchmarks. In particular, our method ranked the 1st place of KITTI 2012 evaluation and the 4th place of KITTI 2015 evaluation (recorded on 2019.8.20). The codes of AcfNet are available at: https://***/DeepMotionAIresearch/ DenseMatchingBenchmark. Copyright © 2019, The Authors. All rights reserved.

关键词： Uncertainty analysis

Correction to: A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility

学校读者我要写书评

暂无评论

Neuroinformatics 2022年第1期20卷 37-38页

作者： Mathew Birdsall Abrams Jan G Bjaalie Samir Das Gary F Egan Satrajit S Ghosh Wojtek J Goscinski Jeffrey S Grethe Jeanette Hellgren Kotaleski Eric Tatt Wei Ho David N Kennedy Linda J Lanyon Trygve B Leergaard Helen S Mayberg Luciano Milanesi Roman Mouček J B Poline Prasun K Roy Stephen C Strother Tong Boon Tang Paul Tiesinga Thomas Wachtler Daniel K Wójcik Maryann E Martone INCF Secretariat Karolinska Institutet Stockholm Sweden. mathew@***. Institute of Basic Medical Sciences University of Oslo Oslo Norway. McGill Centre for Integrative Neuroscience McGill University Montreal QC Canada. Monash Biomedical Imaging Monash University Clayton VIC Australia. McGovern Institute for Brain Research Massachusetts Institute of Technology Cambridge MA USA. Department of Otolaryngology - Head and Neck Surgery Harvard Medical School Boston Boston MA USA. Monash eResearch Centre Monash University Melbourne VIC Australia. Department of Neuroscience School of Medicine University of California San Diego La Jolla CA USA. KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden. Centre for Intelligent Signal and Imaging Research Institute of Health and Analytics Universiti Teknologi PETRONAS Perak Malaysia. Department of Psychiatry University of Massachusetts Medical School Worcester MA USA. Serendipitea.World Hasselby Sweden. Nash Family Center for Advanced Circuit Therapeutics Icahn School of Medicine New York NY USA. Institute of Biomedical Technologies National Research Council (CNR) Milan Italy. Department of Computer Science and Engineering Faculty of Applied Sciences University of West Bohemia Pilsen Czech Republic. Montreal Neurological Institute Faculty of Medicine and Health Sciences McGill University Montreal Canada. Computational Neuroscience & Neuroimaging Laboratory School of Bio-Medical Engineering Indian Institute of Technology (BHU) Varanasi UP India. Rotman Research Institute Baycrest Centre Department of Medical Biophysics University of Toronto Toronto ON Canada. Centre for Intelligent Signal and Imaging Research Institute of Health and Analytics Universiti Teknologi PETRONAS Bandar Seri Iskandar Malaysia. Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen Nijmegen Netherlands. Department of Biology II Ludwig-Maximilians-Univers

A Correction to this paper has been published: https://***/10.1007/s12021-021-09522-x

关键词：

Topology and Kinetic Pathways of Colloidosome Assembly and Disassembly

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Adkins, Raymond Robaszewski, Joanna Shin, Seungwoo Brauns, Fridtjof Jia, Leroy Khanra, Ayantika Sharma, Prerna Pelcovits, Robert Powers, Thomas R. Dogic, Zvonimir Department of Physics University of California Santa Barbara Santa BarbaraCA93106 United States Molecular Biophysics and Biochemistry Yale University New HavenCT06510 United States Environmental Laboratory US Army Engineer Research and Development Center ConcordMA01742 United States Kavli Institute for Theoretical Physics University of California Santa Barbara Santa BarbaraCA93106 United States Applied and Computational Mathematics Division National Institute of Standards and Technology GaithersburgMD20899 United States Department of Physics Indian Institute of Science Bangalore560012 India Department of Bioengineering Indian Institute of Science Bangalore560012 India Department of Physics Brown University ProvidenceRI02906 United States School of Engineering Brown University ProvidenceRI02906 United States

Liquid shells, such as lipid vesicles and soap bubbles, are ubiquitous throughout biology, engineered matter, and everyday life. Their creation and disintegration are defined by a singularity that separates a topologically distinct extended liquid film from a boundary-free closed shell. Such topology-changing processes are essential for cellular transport and drug delivery. However, their studies are challenging because of the rapid dynamics and small length scale of conventional lipid vesicles. We develop fluid colloidosomes, micron-sized analogs of lipid vesicles. We study their stability close to their disk-to-sphere topological transition. Intrinsic colloidal length and time scales slow down the dynamics to reveal vesicle conformations in real time during their assembly and disassembly. Remarkably, the lowest-energy pathway by which a closed vesicle transforms into a disk involves a topologically distinct cylinder-like intermediate. These results reveal universal aspects of topological changes in all liquid shells and a robust platform for the encapsulation, transport, and delivery of nanosized cargoes. © 2025, CC BY.

关键词： Controlled drug delivery

Quantum-centric Supercomputing for Materials science: A Perspective on Challenges and Future Directions

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Alexeev, Yuri Amsler, Maximilian Barroca, Marco Antonio Bassini, Sanzio Battelle, Torey Camps, Daan Casanova, David Choi, Young Jai Chong, Frederic T. Chung, Charles Codella, Christopher Córcoles, Antonio D. Cruise, James Di Meglio, Alberto Duran, Ivan Eckl, Thomas Economou, Sophia Eidenbenz, Stephan Elmegreen, Bruce Fare, Clyde Faro, Ismael Fernández, Cristina Sanz Ferreira, Rodrigo Neumann Barros Fuji, Keisuke Fuller, Bryce Gagliardi, Laura Galli, Giulia Glick, Jennifer R. Gobbi, Isacco Gokhale, Pranav de la Puente Gonzalez, Salvador Greiner, Johannes Gropp, Bill Grossi, Michele Gull, Emanuel Healy, Burns Hermes, Matthew R. Huang, Benchen Humble, Travis S. Ito, Nobuyasu Izmaylov, Artur F. Javadi-Abhari, Ali Jennewein, Douglas Jha, Shantenu Jiang, Liang Jones, Barbara de Jong, Wibe Albert Jurcevic, Petar Kirby, William Kister, Stefan Kitagawa, Masahiro Klassen, Joel Klymko, Katherine Koh, Kwangwon Kondo, Masaaki Kürkçüoglu, Doga Murat Kurowski, Krzysztof Laino, Teodoro Landfield, Ryan Leininger, Matt Leyton-Ortega, Vicente Li, Ang Lin, Meifeng Liu, Junyu Lorente, Nicolas Luckow, Andre Martiel, Simon Martin-Fernandez, Francisco Martonosi, Margaret Marvinney, Claire Medina, Arcesio Castaneda Merten, Dirk Mezzacapo, Antonio Michielsen, Kristel Mitra, Abhishek Mittal, Tushar Moon, Kyungsun Moore, Joel Mostame, Sarah Motta, Mario Na, Young-Hye Nam, Yunseong Narang, Prineha Ohnishi, Yu-Ya Ottaviani, Daniele Otten, Matthew Pakin, Scott Pascuzzi, Vincent R. Pednault, Edwin Piontek, Tomasz Pitera, Jed Rall, Patrick Ravi, Gokul Subramanian Robertson, Niall Rossi, Matteo A.C. Rydlichowski, Piotr Ryu, Hoon Samsonidze, Georgy Sato, Mitsuhisa Saurabh, Nishant Sharma, Vidushi Sharma, Kunal Shin, Soyoung Slessman, George Steiner, Mathias Sitdikov, Iskandar Suh, In-Saeng Switzer, Eric D. Tang, Wei Thompson, Joel Todo, Synge Tran, Minh C. Trenev, Dimitar Trott, Christian Tseng, Huan-Hsin Tubman, Norm M. Tureci, Esin Valiñas, David García Vallecorsa, Sofia Wever, Christopher Wojciechowski, Konrad Wu, Xiaodi Yoo, Shinjae Yoshioka, Argonne National Laboratory LemontIL60439 United States Corporate Sector Research and Advance Engineering Robert Bosch GmbH Robert-Bosch-Campus 1 RenningenD-71272 Germany IBM Research RJ Rio de Janeiro20031-170 Brazil Centro Brasileiro de Pesquisas Físicas RJ Rio de Janeiro22290-180 Brazil CINECA via Magnanelli 6/3 BO Casalecchio di Reno40033 Italy Arizona State University TempeAZ United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA United States Euskadi Donostia-San Sebastián20018 Spain Ikerbasque Basque Foundation for Science Bilbao48009 Spain Department of Physics Yonsei University Seoul03722 Korea Republic of University of Chicago ChicagoIL United States IBM Quantum IBM T.J. Watson Research Center Yorktown Heights NY10598 United States Cambridge Consultants part of Capgemini Invent Cambridge United Kingdom Geneva1211 Switzerland Virginia Tech BlacksburgVA24061 United States Los Alamos National Laboratory Los AlamosNM87545 United States Osaka University Osaka560-8531 Japan Department of Chemistry Chicago Center for Theoretical Chemistry University of Chicago ChicagoIL United States Fraunhofer ITWM Rheinland-Pfalz Kaiserslautern67663 Germany Infleqtion ChicagoIL60622 United States University of Illinois Urbana-Champaign United States University of Michigan Ann ArborMI48109 United States Research Office Oak Ridge National Laboratory One Bethel Valley Road Oak RidgeTN37831 United States Hyogo Kobe650-0047 Japan Chemical Physics Theory Group Department of Chemistry University of Toronto TorontoONM5S 3H6 Canada Department of Physical and Environmental Sciences University of Toronto Scarborough TorontoONM1C 1A4 Canada Brookhaven National Laboratory UptonNY United States Rutgers University New BrunswickNJ United States IBM Quantum Almaden Research Center San JoseCA95120 United States Applied Mathematics and Computational Research Division

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions. Copyright © 2023, The Authors. All rights reserved.

关键词： Characterization (materials science)

Electrostatic nano-mask patterned 180° domain walls in a ferroelectric film

学校读者我要写书评

暂无评论

science Advances 2025年第24期11卷 eadv9194页

作者： Xiangbin Cai Yueze Tan Chao Chen Changsheng Chen Xiangli Che Chao Xu Yan Zhao Haiyang Pan Yaoding Lou Jefferson Zhe Liu Jesús Zúñiga Pérez Weibo Gao Long-Qing Chen Jun-Ming Liu Deyang Chen Ye Zhu Department of Applied Physics Research Institute for Smart Energy The Hong Kong Polytechnic University Kowloon Hong Kong China. Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore. Materials Research Institute and Department of Materials Science and Engineering The Pennsylvania State University University Park PA 16802 USA. Guangdong Provincial Key Laboratory of Optical Information Materials and Technology and Institute for Advanced Materials South China Academy of Advanced Optoelectronics South China Normal University Guangzhou 510006 China. Department of Mechanical Engineering The University of Melbourne Parkville VIC 3010 Australia. Majulab International Joint Research Unit UMI 3654 CNRS Université Côte d’Azûr Sorbonne Université National University of Singapore Nanyang Technological University Singapore 637371 Singapore. School of Electrical and Electronic Engineering The Photonics Institute and Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore 639798 Singapore. Centre for Quantum Technologies National University of Singapore Singapore 117543 Singapore. Laboratory of Solid State Microstructures and Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China.

Ferroelectric domain walls (FDWs) exhibit exotic structural and electronic properties, positioning them as a promising functional element for next-generation nanoelectronics. However, achieving the deterministic creation of FDWs with nanoscale precision and controlled polarization of domains remains a substantial challenge for the scalable FDW-device fabrication and circuit design. Here, we demonstrate a strategy for FDW engineering by tailoring the interfacial electrostatic profile. Using SrRuO3 islands as “nano-masks,” we spatially modulate the interfacial atomic termination to generate alternating positive and negative built-in electric fields. The boundaries where the electric field switches polarity drive the formation of 180° FDWs in BiFeO3 thin films. This mechanism is validated through theoretical calculations and direct experimental observations. Furthermore, atomic-scale analysis reveals localized lattice distortions, structural chirality of the FDWs, as well as the edge effect of SrRuO3 islands on the position precision of FDW nucleation. Our findings pave the way toward a scalable and controllable bottom-up FDW-growth technique for future FDW nanoelectronics.

关键词：

Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

学校读者我要写书评

暂无评论

Nature methods 2024年第10期21卷 1959页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

Fear not, vote truthfully: Secure multiparty computation of score based rules

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Dery, Lihi Tassa, Tamir Yanai, Avishay Department Of Industrial Engineering And Management Ariel University Ariel Israel Ariel Cyber Innovation Center Ariel Israel Department Of Mathematics And Computer Science The Open University Raanana Israel VMware Research Herzliya Israel

We propose a secure voting protocol for score-based voting rules, where independent talliers perform the tallying procedure. The protocol outputs the winning candidate(s) while preserving the privacy of the voters and the secrecy of the ballots. It offers perfect secrecy, in the sense that apart from the desired output, all other information - the ballots, intermediate values, and the final scores received by each of the candidates - is not disclosed to any party, including the talliers. Such perfect secrecy may increase the voters' confidence and, consequently, encourage them to vote according to their true preferences. The protocol is extremely lightweight, and therefore it can be easily deployed in real life voting scenarios. Copyright © 2019, The Authors. All rights reserved.

关键词： Privacy-preserving techniques

Discovery of a maximally charged Weyl point

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Chen, Qiaolu Chen, Fujia Yan, Qinghui Zhang, Li Gao, Zhen Yang, Shengyuan A. Yu, Zhi-Ming Chen, Hongsheng Zhang, Baile Yang, Yihao Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou310027 China International Joint Innovation Center Key Lab. of Advanced Micro Nano Electronic Devices & Smart Systems of Zhejiang The Electromagnetics Academy Zhejiang University Zhejiang University Haining314400 China Jinhua Institute of Zhejiang University Zhejiang University Jinhua321099 China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China Research Laboratory for Quantum Materials Singapore University of Technology and Design 487372 Singapore School of Physics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing100081 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link 637371 Singapore Centre for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 50 Nanyang Avenue 639798 Singapore

The hypothetical Weyl particles in high-energy physics have been discovered in three-dimensional crystals as collective quasiparticle excitations near two-fold degenerate Weyl points1-5. Such momentum-space Weyl particles carry quantized chiral charges, which can be measured by counting the number of Fermi arcs emanating from the corresponding Weyl points. It is known that merging unit-charged Weyl particles can create new ones with more charges6. However, only very recently has it been realised that there is an upper limit - the maximal charge number that a two-fold Weyl point can host is four - achievable only in crystals without spin-orbit coupling7-9. Here, we report the experimental realisation of such a maximally charged Weyl point in a three-dimensional photonic crystal. The four charges support quadruple-helicoid Fermi arcs, forming an unprecedented topology of two non-contractible loops in the surface Brillouin zone. The helicoid Fermi arcs also exhibit the long-pursued type-II van Hove singularities that can reside at arbitrary momenta. This discovery reveals a type of maximally charged Weyl particles beyond conventional topological particles in crystals. Copyright © 2022, The Authors. All rights reserved.

关键词： Topology