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MAXIMAL LINE-FREE SETS IN Fnp

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arXiv 2023年

作者： Elsholtz, Christian Führer, Jakob Füredi, Erik Kovács, Benedek Pach, Péter Pál Simon, Dániel Gábor Velich, Nóra Institute of Analysis and Number Theory Graz University of Technology Kopernikusgasse 24/II Graz8010 Austria ELTE Eötvös Loránd University Faculty of Science Pázmány Péter sétány 1/A Budapest1117 Hungary ELTE Linear Hypergraphs Research Group Eötvös Loránd University Pázmány Péter sétány 1/A Budapest1117 Hungary Department of Computer Science and Information Theory Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary MTA-BME Lendület Arithmetic Combinatorics Research Group Műegyetem rkp. 3. BudapestH-1111 Hungary HUN-REN Alfréd Rényi Institute of Mathematics Reáltanoda street 13-15 BudapestH-1053 Hungary University of Cambridge Lucy Cavendish College Lady Margaret Road CambridgeCB3 0BU United Kingdom

We study subsets of Fnp that do not contain progressions of length k. We denote by rk(Fnp ) the cardinality of such subsets containing a maximal number of elements. In this paper we focus on the case k = p and therefore sets containing no full line. A trivial lower bound rp(Fnp ) ≥ (p−1)n is achieved by a hypercube of side length p−1 and it is known that equality holds for n ∈ {1, 2}. We will however show that rp(F3p) ≥ (p − 1)3 + p − 2√p, which is the first improvement in the three dimensional case that is increasing in p. We will also give the upper bound rp(F3p) ≤ p3−2p2−(√2−1)p+2 as well as generalizations for higher dimensions. Finally we present some bounds for individual p and n, in particular r5(F35) ≥ 70 and r7(F37) ≥ 225 which can be used to give the asymptotic lower bound 4.121n for r5(Fn5 ) and 6.082n for r7(Fn7 ).MSC Codes 51E21, 11B25, 05D05 © 2023, CC BY.

关键词： Combinatorial mathematics

Parametric Verification: An Introduction 39th

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Parametric Verification: An Introduction

39th International Conference on Application and Theory of Petri Nets and Concurrency, Petri Nets 2018, and the 18th International Conference on Application of Concurrency to System Design, ACSD 2018

作者： André, Étienne Knapik, Michal Lime, Didier Penczek, Wojciech Petrucci, Laure LIPN CNRS UMR 7030 Université Paris 13 Villetaneuse France Institute of Computer Science PAS Warsaw Poland École Centrale de Nantes LS2N CNRS UMR 6004 Nantes France University of Natural Sciences and Humanities II Siedlce Poland

ISBN: (纸本)9783662606506

This paper constitutes a short introduction to parametric verification of concurrent systems. It originates from two 1-day tutorial sessions held at the Petri nets conferences in Toruń (2016) and Zaragoza (2017). A video of the presentation is available at https://***/playlist?list=PL9SOLKoGjbeqNcdQVqFpUz7HYqD1fbFIg, consisting of 14 short sequences. The paper presents not only the basic formal concepts tackled in the video version, but also an extensive literature to provide the reader with further references covering the area. We first introduce motivation behind parametric verification in general, and then focus on different models and approaches, for verifying several kinds of systems. They include Parametric Timed Automata, for modelling real-time systems, where the timing constraints are not necessarily known a priori. Similarly, Parametric Interval Markov Chains allow for modelling systems where probabilities of events occurrences are intervals with parametric bounds. Parametric Petri Nets allow for compact representation of systems, and cope with different types of parameters. Finally, Action Synthesis aims at enabling or disabling actions in a concurrent system to guarantee some of its properties. Some tools implementing these approaches were used during hands-on sessions at the tutorial. The corresponding practicals are freely available on the Web. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Petri nets

Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks

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arXiv 2021年

作者： Grandits, Thomas Pezzuto, Simone Costabal, Francisco Sahli Perdikaris, Paris Pock, Thomas Plank, Gernot Krause, Rolf Institute of Computer Graphics and Vision TU Graz Graz Austria BioTechMed-Graz Graz Austria Center for Computational Medicine in Cardiology Institute of Computational Science Università della Svizzera italiana Lugano Switzerland Department of Mechanical and Metallurgical Engineering School of Engineering Pontificia Universidad Católica de Chile Santiago Chile Institute for Biological and Medical Engineering Schools of Engineering Medicine and Biological Sciences Pontificia Universidad Católica de Chile Santiago Chile Millennium Nucleus for Cardiovascular Magnetic Resonance Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania PhiladelphiaPA United States Gottfried Schatz Research Center Division of Biophysics Medical University of Graz Graz Austria

Electroanatomical maps are a key tool in the diagnosis and treatment of atrial fibrillation. Current approaches focus on the activation times recorded. However, more information can be extracted from the available data. The fibers in cardiac tissue conduct the electrical wave faster, and their direction could be inferred from activation times. In this work, we employ a recently developed approach, called physics informed neural networks, to learn the fiber orientations from electroanatomical maps, taking into account the physics of the electrical wave propagation. In particular, we train the neural network to weakly satisfy the anisotropic eikonal equation and to predict the measured activation times. We use a local basis for the anisotropic conductivity tensor, which encodes the fiber orientation. The methodology is tested both in a synthetic example and for patient data. Our approach shows good agreement in both cases, with an RMSE of 2.2ms on the in-silico data and outperforming a state of the art method on the patient data. The results show a first step towards learning the fiber orientations from electroanatomical maps with physics-informed neural networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Tensors

Graph-based parallel large scale structure from motion

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arXiv 2019年

作者： Chen, Yu Shen, Shuhan Chen, Yisong Wang, Guoping Graphics and Interactive Lab Department of Computer Science and Technology School of Electronic Engineering and Computer Science Peking University National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

While Structure from Motion (SfM) achieves great success in 3D reconstruction, it still meets challenges on large scale scenes. In this work, large scale SfM is deemed as a graph problem, and we tackle it in a divide-and-conquer manner. Firstly, the images clustering algorithm divides images into clusters with strong connectivity, leading to robust local reconstructions. Then followed with an image expansion step, the connection and completeness of scenes are enhanced by expanding along with a maximum spanning tree. After local reconstructions, we construct a minimum spanning tree (MST) to find accurate similarity transformations. Then the MST is transformed into a Minimum Height Tree (MHT) to find a proper anchor node and is further utilized to prevent error accumulation. When evaluated on different kinds of datasets, our approach shows superiority over the state-of-the-art in accuracy and efficiency. Our algorithm is open-sourced in https://***/AIBluefisher/GraphSfM. Copyright © 2019, The Authors. All rights reserved.

关键词： Clustering algorithms

Magnetic Excitations in Strained Infinite-layer Nickelate PrNiO2

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arXiv 2022年

作者： Gao, Qiang Fan, Shiyu Wang, Qisi Li, Jiarui Ren, Xiaolin Bialo, Izabela Drewanowski, Annabella Rothenbühler, Pascal Choi, Jaewon Wang, Yao Xiang, Tao Hu, Jiangping Zhou, Ke-Jin Bisogni, Valentina Comin, Riccardo Chang, J. Pelliciari, Jonathan Zhou, X.J. Zhu, Zhihai Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China National Synchrotron Light Source II Brookhaven National Laboratory UptonNY11973 United States Physik-Institut Universität Zürich Winterthurerstrasse 190 ZürichCH-8057 Switzerland Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States University of Chinese Academy of Sciences Beijing100049 China AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków30-059 Poland Diamond Light Source Harwell Campus DidcotOX11 0DE United Kingdom Department of Physics and Astronomy Clemson University ClemsonSC29631 United States Beijing Academy of Quantum Information Sciences Beijing100193 China Songshan Lake Materials Laboratory Dongguan523808 China

Strongly correlated materials often respond sensitively to the external perturbations. In the recently discovered superconducting infinite-layer nickelates, the superconducting transition temperature can be dramatically enhanced via only ~1% compressive strain-tuning enabled by substrate design. However, the root of such enhancement remains elusive. While the superconducting pairing mechanism is still not settled, magnetic Cooper pairing - similar to the cuprates has been proposed. Using resonant inelastic x-ray scattering, we investigate the magnetic excitations in infinite-layer PrNiO2 thin films for different strain conditions. The magnon bandwidth of PrNiO2 shows only marginal response to strain-tuning, in sharp contrast to the striking enhancement of the superconducting transition temperature Tc in the doped superconducting samples. These results suggest the enhancement of Tc is not mediated by spin excitations and thus provide important empirics for the understanding of superconductivity in infinite-layer nickelates. © 2022, CC BY.

关键词： Praseodymium compounds

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

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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

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Spectrum of QCD with one flavor: A window for supersymmetric dynamics

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Physical Review D 2023年第11期107卷 114506-114506页

作者： Michele Della Morte Benjamin Jäger Francesco Sannino J. Tobias Tsang Felix P. G. Ziegler CP3-Origins Department of Mathematics and Computer Science University of Southern Denmark 5230 Odense M Denmark Danish Institute for Advanced Study University of Southern Denmark 5230 Odense M Denmark CP3-Origins Department of Physics Chemistry and Pharmacy University of Southern Denmark 5230 Odense M Denmark Dipartimento di Fisica “E. Pancini” Università di Napoli Federico II—INFN sezione di Napoli Complesso Universitario di Monte S. Angelo 80126 Napoli Italy CERN Theoretical Physics Department 1211 Geneva 23 Switzerland School of Physics and Astronomy The University of Edinburgh EH9 3FD Edinburgh United Kingdom

We compute the spectrum of the low-lying mesonic states with vector, scalar and pseudoscalar quantum numbers in QCD with one flavor. With three colors the fundamental and the two-index antisymmetric representations of the gauge group coincide. The latter is an orientifold theory that maps into the bosonic sector of N=1 super Yang-Mills theory in the large number of colors limit. We employ Wilson fermions along with tree-level improvement in the gluonic and fermionic parts of the action. In this setup the Dirac operator can develop real negative eigenvalues. We therefore perform a detailed study in order to identify configurations where the fermion determinant is negative and eventually reweight them. We finally compare results with effective field theory predictions valid in the large NC limit and find reasonably consistent values despite NC being only three. Additionally, the spin-one sector provides a novel window for supersymmetric dynamics.

关键词： Lattice QCD Lattice field theory Nonperturbative effects in field theory Supersymmetric models

Hybrid learning environments by data-driven augmented reality

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Procedia Manufacturing 2019年 31卷 32-37页

作者： Dörte Sonntag Georgia Albuquerque Marcus Magnor Oliver Bodensiek Institute for Science Education Research Technische Universität Braunschweig Bienroder Weg 82 38106 Braunschweig Germany Computer Graphics Lab Technische Universität Braunschweig Mühlenpfordtstraße 23 38106 Braunschweig Germany

Augmented Reality (AR) offers the potential to integrate physical, digital and social learning experiences in hybrid learning environments and thereby to achieve learning gains, higher motivation or improved interaction and collaboration. Moreover, by means of AR, theory- or calculus-based learning and experimental exploration in the lab can be brought closer together. Here we present a data-driven AR enhancement of experiments in an electricity and magnetism lab course, where measurement data such as actual current and voltage, are transmitted to a head-mounted semi-transparent display (HMD). In addition, preliminary evaluation results are presented. An improved technical understanding of the subject and especially more dense interrelations between individual learners conceptions are observed.

关键词： augmented reality mixed reality learning environments data-driven visualization

Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at (Formula presented.) TeV with the ATLAS detector

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Journal of High Energy Physics 2024年第4期2024卷 26页

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Abusleme Hoffman, A.C. Acharya, B.S. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Allendes Flores, C.A. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Alviggi, M.G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Amor Dos Santos, S.P. Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Appelt, C. Apyan, A. Aranzabal, N. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Bakalis, C. Baker, O.K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. Bandieramont Department of Physics University of Adelaide Department of Physics University of Alberta Department of Physics Ankara University Division of Physics TOBB University of Economics and Technology LAPP Université Savoie Mont Blanc CNRS/IN2P3 APC Université Paris Cité CNRS/IN2P3 High Energy Physics Division Argonne National Laboratory Department of Physics University of Arizona Department of Physics University of Texas at Arlington Physics Department National and Kapodistrian University of Athens Physics Department National Technical University of Athens Department of Physics University of Texas at Austin Institute of Physics Azerbaijan Academy of Sciences Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Institute of High Energy Physics Chinese Academy of Sciences Physics Department Tsinghua University Department of Physics Nanjing University School of Science Shenzhen Campus of Sun Yat-sen University University of Chinese Academy of Science (UCAS) Institute of Physics University of Belgrade Department for Physics and Technology University of Bergen Physics Division Lawrence Berkeley National Laboratory University of California Institut für Physik Humboldt Universität zu Berlin Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern School of Physics and Astronomy University of Birmingham Department of Physics Bogazici University Department of Physics Engineering Gaziantep University Department of Physics Istanbul University Facultad de Ciencias y Centro de Investigaciónes Universidad Antonio Nariño Departamento de Física Universidad Nacional de Colombia Dipartimento di Fisica e Astronomia A. Righi Università di Bologna INFN Sezione di Bologna Physikalisches Institut Universität Bonn Department of Physics Boston University Department of Physics Brandeis University Transilvania University of Brasov Horia Hulubei National Institute of Physics and Nuclear Engineering Department of Physics Alexandru

This paper presents the measurement of fiducial and differential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W^±W^±jj) using 139 fb⁻¹ of proton-proton collision data recorded at a centre-of-mass energy of s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity difference. The measured fiducial cross sections for electroweak and inclusive W^±W^±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.) fb and 3.38 ± 0.22 (stat.) ± 0.19 (syst.) fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confidence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H^±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H^±± mass near 450 GeV, with a global significance of 2.5 standard deviations. © The Author(s) 2024.

关键词： Hadron-Hadron Scattering Vector Boson Production