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Quantum spin systems: Toroidal classification and geometric duality

Physical Review B 2024年第14期110卷 L140403页

作者： Vahid Azimi-Mousolou Anders Bergman Anna Delin Olle Eriksson Manuel Pereiro Danny Thonig Erik Sjöqvist Department of Applied Mathematics and Computer Science Faculty of Mathematics and Statistics Department of Physics and Astronomy Department of Applied Physics School of Engineering Sciences (SeRC) Wallenberg Initiative Materials Science for Sustainability (WISE) Wallenberg Initiative Materials Science WISE School of Science and Technology

We demonstrate a toroidal classification for quantum spin systems, revealing an intrinsic geometric duality within this structure. Through our classification and duality, we reveal that various bipartite quantum features in magnon systems can manifest equivalently in both bipartite ferromagnetic and antiferromagnetic materials, based upon the availability of relevant Hamiltonian parameters. Additionally, the results highlight the antiferromagnetic regime as an ultrafast dual counterpart to the ferromagnetic regime, both exhibiting identical capabilities for quantum spintronics and technological applications. Concrete illustrations are provided, demonstrating how splitting and squeezing types of two-mode magnon quantum correlations can be realized across ferro- and antiferromagnetic regimes.

关键词： Magnons Quantum correlations in quantum information Quantum information processing Quantum information theory Spintronics

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Yang-Lee zeros for real-space condensation

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Physical Review E 2025年第1期111卷 L012101-L012101页

作者： Zdzislaw Burda Desmond A. Johnston Mario Kieburg Faculty of Physics and Applied Computer Science AGH University of Krakow al. Mickiewicza 30 30-059 Kraków Poland School of Mathematical and Computer Sciences Heriot-Watt University Riccarton Edinburgh EH14 4AS United Kingdom and Maxwell Institute of Mathematical Sciences Edinburgh United Kingdom School of Mathematics and Statistics University of Melbourne Parkville VIC 3010 Australia Faculty of Physics and Applied Computer Science AGH University of Krakow al. Mickiewicza 30 30-059 Kraków Poland and Faculty of Physics Bielefeld University P.O. Box 100131 D-33501 Bielefeld Germany

Using the electrostatic analogy, we derive an exact formula for the limiting Yang-Lee zero distribution in the random allocation model of general weights. This exhibits a real-space condensation phase transition, which is induced by a pressure change. The exact solution allows one to read off the scaling of the density of zeros at the critical point and the angle at which the locus of zeros hits the critical point. Since the order of the phase transition and critical exponents can be tuned with a single parameter for several families of weights, the model provides a useful testing ground for verifying various relations between the distribution of zeros and the critical behavior, as well as for exploring the behavior of physical quantities in the mesoscopic regime, i.e., systems of large but finite size. The main result is that asymptotically the Yang-Lee zeros are images of a conformal mapping, given by the generating function for the weights, of uniformly distributed complex phases.

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Findings of the Third Shared Task on Multilingual Coreference Resolution 7

Findings of the Third Shared Task on Multilingual Coreferenc...

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7th Workshop on Computational Models of Reference, Anaphora and Coreference, CRAC 2024

作者： Novák, Michal Dohnalová, Barbora Konopík, Miloslav Nedoluzhko, Anna Popel, Martin Pražák, Ondřej Sido, Jakub Straka, Milan Žabokrtský, Zdeněk Zeman, Daniel Charles University Faculty of Mathematics and Physics Institute of Formal and Applied Linguistics Prague Czech Republic University of West Bohemia Faculty of Applied Sciences Department of Computer Science and Engineering Pilsen Czech Republic

ISBN: (纸本)9798891761711

The paper presents an overview of the third edition of the shared task on multilingual coreference resolution, held as part of the CRAC 2024 workshop. Similarly to the previous two editions, the participants were challenged to develop systems capable of identifying mentions and clustering them based on identity coreference. This year’s edition took another step towards real-world application by not providing participants with gold slots for zero anaphora, increasing the task’s complexity and realism. In addition, the shared task was expanded to include a more diverse set of languages, with a particular focus on historical languages. The training and evaluation data were drawn from version 1.2 of the multilingual collection of harmonized coreference resources CorefUD, encompassing 21 datasets across 15 languages. 6 systems competed in this shared task. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Tip-enhanced Raman spectroscopy reveals the structural rearrangements of tau protein aggregates at the growth phase

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NANOSCALE 2024年第10期16卷 5294-5301页

作者： Sofinska, Kamila Seweryn, Sara Skirlinska-Nosek, Katarzyna Barbasz, Jakub Lipiec, Ewelina [a]Jagiellonian University Faculty of Physics Astronomy and Applied Computer Science M. Smoluchowski Institute of Physics Łojasiewicza 11 30-348 Krakow Poland [b]Jagiellonian University Doctoral School of Exact and Natural Sciences Krakow Poland [c]Jerzy Haber Institute of Catalysis and Surface Chemistry Polish Academy of Sciences Niezapominajek 8 30-239 Krakow Poland

Tau protein aggregates inside neurons in the course of Alzheimer's disease (AD). Because of the enormous number of people suffering from AD, this disease has become one of the world's major health and social problems. The presence of tau lesions clearly correlates with cognitive impairments in AD patients, thus, tau is the target of potential treatments for AD, next to amyloid-beta. The exact mechanism of tau aggregation has not been understood in detail so far;especially little is known about the structural rearrangements of tau aggregates at the growth phase. The research into tau conformation at each step of the aggregation pathway will contribute to the design of effective therapeutic approaches. To follow the secondary structure of individual tau aggregates at the growth phase, we applied tip-enhanced Raman spectroscopy (TERS). The nanospectroscopic approach enabled us to follow the structure of individual aggregates occurring in the subsequent phases of tau aggregation. We applied multivariate data analysis to extract the spectral differences for tau aggregates at different aggregation phases. Moreover, atomic force microscopy (AFM) allowed the tracking of the morphological alterations for species occurring with the progression of tau aggregation. Tip-enhanced Raman spectroscopy (TERS) enabled the structural differences between tau protein aggregates to be revealed, specifically tau protofibrils and young fibrils at the level of individual aggregates.

关键词： Aggregates

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Random Forest Pruning Techniques: A Recent Review

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Operations Research Forum 2023年第2期4卷 43页

作者： Manzali, Youness Elfar, Mohamed Laboratory of Applied Physics Computer Science and Statistics Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fez Morocco

Random forest is one of the most used machine learning algorithms since its high predictive performance. However, many studies criticize it for the fact that it generates a large number of trees, which requires important storage space and a significant learning time. In addition, the final model induced by RF may contain redundant trees and others that do not contribute to the prediction that may even disadvantage performance. This is why many researchers try to reduce the number of trees in a forest called forest pruning. This article presents a study of the pruning work of random forest classifiers, explains in detail the operating principle of each technique, and cites their advantages and disadvantages. Finally, it compares their classification performance in terms of accuracy, speed of learning, and complexity. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Ensemble method Pruning techniques Random forest Tree selection

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Completely entangled subspaces of entanglement depth k

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Physical Review A 2024年第1期110卷 012403-012403页

作者： Maciej Demianowicz Kajetan Vogtt Remigiusz Augusiak Institute of Physics and Applied Computer Science Faculty of Applied Physics and Mathematics Polish Academy of Sciences Aleja Lotników 32/46 02-668 Warsaw Poland Faculty of Physics

We introduce a class of entangled subspaces: completely entangled subspaces of entanglement depth k (k−CESs). These are subspaces of multipartite Hilbert spaces containing only pure states with an entanglement depth of at least k. We present an efficient construction of k−CESs of any achievable dimensionality in any multipartite scenario. Further, we discuss the relation between these subspaces and unextendible product bases (UPBs). In particular, we establish that there is a nontrivial bound on the cardinality of a UPB whose orthocomplement is a k−CES. Further, we discuss the existence of such UPBs for qubit systems.

关键词： Entanglement detection Quantum entanglement Quantum error correction Quantum information theory

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Findings of the Second Shared Task on Multilingual Coreference Resolution 6

Findings of the Second Shared Task on Multilingual Coreferen...

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CRAC Shared Task on Multilingual Coreference Resolution at 6th Workshop on Computational Models of Reference, Anaphora and Coreference, CRAC 2023

作者： Žabokrtský, Zdeněk Konopík, Miloslav Nedoluzhko, Anna Novák, Michal Ogrodniczuk, Maciej Popel, Martin Pražák, Ondřej Sido, Jakub Zeman, Daniel Charles University Faculty of Mathematics and Physics Institute of Formal and Applied Linguistics Prague Czech Republic University of West Bohemia Faculty of Applied Sciences Department of Computer Science and Engineering Pilsen Czech Republic Institute of Computer Science Polish Academy of Sciences Warsaw Poland

ISBN: (纸本)9781955917025

This paper summarizes the second edition of the shared task on multilingual coreference resolution, held with the CRAC 2023 workshop. Just like last year, participants of the shared task were to create trainable systems that detect mentions and group them based on identity coreference;however, this year’s edition uses a slightly different primary evaluation score, and is also broader in terms of covered languages: version 1.1 of the multilingual collection of harmonized coreference resources CorefUD was used as the source of training and evaluation data this time, with 17 datasets for 12 languages. 7 systems competed in this shared task. © CRAC 2023. All Rights Reserved.

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A feature weighted K-nearest neighbor algorithm based on association rules

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Journal of Ambient Intelligence and Humanized Computing 2024年第7期15卷 2995-3008页

作者： Manzali, Youness Barry, Khalidou Abdoulaye Flouchi, Rachid Balouki, Youssef Elfar, Mohamed Laboratory of Applied Physics Computer Science and Statistics Faculty of Sciences Dhar El Mehraz Sidi Mohamed Ben Abdellah University Fez Morocco Laboratory of Microbial Biotechnology and Bioactive Molecules Science and Technologies Faculty Sidi Mohamed Ben Abdellah University Fez Morocco Science and Technologies Faculty University Hassan 1st Settat Morocco

K-nearest neighbors (kNN) is a popular machine learning algorithm because of its clarity, simplicity, and efficacy. kNN has numerous drawbacks, including ignoring issues like class distribution, feature relevance, neighbor contribution, and the number of individuals for each class. In particular, some features could be more important than others for classifying a data point, and increasing their weight in the distance computation can make the kNN algorithm more accurate. Researchers propose different feature weightings, such as correlation-based feature selection, mutual information, and chi-square feature selection. This paper presents a new feature weighting technique based on association rules and information gain. The proposed approach gives a good performance compared to other similar methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Association rules

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An improved KNN algorithm based on ensemble methods and correlation 7

An improved KNN algorithm based on ensemble methods and corr...

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7th IEEE International Congress on Information Science and Technology, CiSt 2023

作者： Manzali, Youness Barry, Khalidou Abdoulaye Far, Mohamed El Faculty of Sciences Dhar El Mahraz Sidi Mohammed Ben Abdellah University Applied Physics Computer Science and Statistics Laboratory Fez Morocco

ISBN: (纸本)9781665461337

K-Nearest Neighbors is a widely used algorithm due to its simplicity and efficacity. However, KNN suffers from many drawbacks, such as it does not work well with datasets with a high number of features. Also, not all the features contribute to the classification process. To resolve these issues, we present an improved KNN algorithm which uses KNN as a base learner in an ensemble method and correlation for selecting the features subsets. The experiment results show that the proposed algorithm performed better than other machine learning algorithms. © 2023 IEEE.

关键词： Learning algorithms

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DISTANCE BETWEEN SPECIES BY CONFUSION OPERATORS OF MULTI-CLASS CLASSIFIERS

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UPB Scientific Bulletin, Series A: applied Mathematics and physics 2025年第1期2025卷 171-182页

作者： Tarbă, Nicolae Irimescu, Ionela N. Pleavă, Ana M. Scarlat, Eugen N. Mihăilescu, Mona Doctoral School Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania Applied Sciences Doctoral School National University of Science and Technology POLITEHNICA Bucharest Romania CAMPUS Research Center National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept Research Center for Applied Sciences in Engineering National University of Science and Technology POLITEHNICA Bucharest Romania

We introduce a method to evaluate the similarities between classes of objects based on the confusion matrices coming from the multi-class machine learning (ML) predictors that operate in the vector space generated by the classes. Operation in the confusion domain allows us to use the distance as evaluation metric of the closeness of the relevant properties carried by the classes. We applied the method to semiquantitatively evaluate the effects of X-ray and carbon ion radiation on cultured SW1353 chondrosarcoma cells with respect to the non-irradiated reference. We prove that it is possible to draw useful information on the strength of cells nuclei changes. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Radiation effects

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