Article
Chemistry, Physical
Julia Wiktor, Erik Fransson, Dominik Kubicki, Paul Erhart
Summary: Halide perovskites are promising materials for optoelectronic applications due to their favorable properties, but their dynamic softness causes apparent disagreements between local and global structures. In this study, we use large-scale molecular dynamics simulations to assess the local tilt angles in perovskite structures and compare results obtained from different density functionals. We also demonstrate strong short-range ordering in the cubic phase of halide perovskites, which provides a bridge between the disordered local structure and the global arrangement. These findings enhance our understanding of the structural properties of halide perovskites and contribute to further exploration of their optoelectronic properties.
CHEMISTRY OF MATERIALS
(2023)
Article
Physics, Multidisciplinary
Heyang Li, An Zeng
Summary: This paper examines human online behavior patterns and discovers that users tend to choose items with longer network distance after a long period of inactivity. It also proposes adjusting recommendation diversity based on user inactivity time, and further improves recommendation algorithms by balancing accuracy and complexity.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Physics, Multidisciplinary
Carles Blanch-Mercader, Pau Guillamat, Aurelien Roux, Karsten Kruse
Summary: Research shows that cell monolayers exert compressive stresses at defect centers, leading to localized cell differentiation and formation of three-dimensional shapes in these regions.
PHYSICAL REVIEW LETTERS
(2021)
Article
Biochemistry & Molecular Biology
Apurva Badkas, Sebastien De Landtsheer, Thomas Sauter
Summary: Glioblastoma multiforme (GBM), a challenging disease with a poor prognosis, exhibits high molecular heterogeneity and limited therapeutic options. This study used network-based analysis to identify key proteins in GBM and proposed 18 novel candidate proteins based on their expression, mutation, and survival analysis. Further investigations are needed to determine their functional roles, clinical relevance, and potential as therapeutic targets in GBM.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Mathematics, Interdisciplinary Applications
Giacomo Gradenigo, Matteo Paoluzzi
Summary: Early studies have shown that the geometric features of the energy landscape play a fundamental role in the crossover from high-temperature simple relaxational dynamics to low-temperature activated relaxation in the glass transition. Active particles are shown to be useful in gaining insight into this topological crossover, especially in inducing critical non-equilibrium correlations in the presence of self-propulsion.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Physics, Multidisciplinary
Guillermo Arregui, Jordi Gomis-Bresco, Clivia M. Sotomayor-Torres, Pedro David Garcia
Summary: The article analyzes the impact of the backscattering mean free path and the group velocity slowdown factor on slow-light transmission in topological photonic waveguides, highlighting the importance of considering these two factors when assessing the robustness of topological and conventional slow-light transport at the nanoscale.
PHYSICAL REVIEW LETTERS
(2021)
Article
Computer Science, Artificial Intelligence
Christoph Stoeckl, Wolfgang Maass
Summary: Optimizing spiking neuron models for information transmission enhances the efficiency and accuracy of deep learning applications through reducing the number of spikes emitted per neuron. This new method improves latency and throughput of resulting spiking networks, offering a low-energy solution for edge and mobile devices in image classification tasks.
NATURE MACHINE INTELLIGENCE
(2021)
Article
Mathematics, Interdisciplinary Applications
Alberto Ceria, Shlomo Havlin, Alan Hanjalic, Huijuan Wang
Summary: This article proposes a method to characterize temporal and topological relations of contacts in temporal networks, and finds that temporal-topological correlation of contacts is more evident in virtual contact networks than in physical contact networks.
JOURNAL OF COMPLEX NETWORKS
(2022)
Article
Physics, Fluids & Plasmas
Chongpu Zhai, Nahuel Albayrak, Jonas Engqvist, Stephen A. Hall, Jonathan Wright, Marta Majkut, Eric B. Herbold, Ryan C. Hurley
Summary: The study investigates the local rearrangements that occur during the deformation process of 3D granular materials under different boundary conditions. The results show that these rearrangements are correlated on a scale of three to four particle diameters, exhibit volumetric strain-shear strain and nonaffine displacement-rotation coupling, and may occur repeatedly during incremental sample strain. The findings suggest that local structure may play at least as important of a role as local stress in determining the nature of local rearrangements.
Article
Quantum Science & Technology
Debarshi Das, Ananda G. Maity, Debashis Saha, A. S. Majumdar
Summary: Certification of quantum devices is crucial before utilizing them for information processing tasks. This paper presents a certification protocol for a particular set of d-outcome quantum measurements, using a setup comprising of preparation and two sequential measurements. The protocol involves a set of temporal inequalities involving correlation functions and quantum violations of these inequalities are used to certify specific d-outcome measurements efficiently in an experiment. The protocol is robust against practical non-ideal realizations and does not require prior knowledge about the system dimension. Additionally, a scheme for secure certification of quantum randomness is presented as an offshoot of the protocol.
Article
Physics, Multidisciplinary
Vittoria Sposini, Aleksei Chechkin, Igor M. Sokolov, Sandalo Roldan-Vargas
Summary: Lennard-Jones mixtures are commonly used for studying glass-forming liquids, which exhibit slow dynamics characterized by spatio/temporal heterogeneity and rare events. Single-particle motion in these liquids can be described as a sequence of waiting times and jumps, and the presence of negative correlations between waiting times is found to be more pronounced at lower temperatures.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2022)
Article
Ecology
Claudia A. Huaylla, Marcos E. Nacif, Carolina Coulin, Marcelo N. Kuperman, Lucas A. Garibaldi
Summary: Constructing and analyzing a network to capture the topological structure of species interactions is an effective way to understand ecosystem functioning at different scales. By comparing the modularity values of the original network with randomized versions, this study presents a reliable method to identify keystone species. The analysis based on modularity measurement proves to be a valuable tool for characterizing ecological networks and could be applied to other networks in the literature.
ECOLOGICAL MODELLING
(2021)
Article
Quantum Science & Technology
Y. Lahlou, L. Bakmou, B. Maroufi, M. Daoud
Summary: In this study, we propose a scheme to investigate the dynamic evolution of quantum correlations in two-mode Gaussian states under the influence of a Gaussian thermal environment. By quantifying the Gaussian interferometric power and the Gaussian entanglement of formation, we find that the behavior of quantum correlations depends on the parameters of the input states, and the Gaussian interferometric power is less affected by the environment.
QUANTUM INFORMATION PROCESSING
(2022)
Article
Computer Science, Information Systems
Wenfei Fan, Ruochun Jin, Ping Lu, Chao Tian, Ruiqi Xu
Summary: This paper proposes a new class of temporal association rules, TACOs, for event prediction. Unlike previous graph rules, TACOs monitor updates to graphs and can capture temporal interests and detect behavior changes such as frauds. The paper addresses the complexity of reasoning about TACOs and introduces a system called TASTE for discovering and applying these rules. Experimental results show that TASTE is significantly faster and more accurate than conventional data mining methods in TACO discovery.
PROCEEDINGS OF THE VLDB ENDOWMENT
(2022)
Article
Biochemical Research Methods
Paul Manuel J. Mueller, Christian Meisel
Summary: A study found spatial and temporal correlations in information processing in the brain, which are closely linked to the critical point. The study also discovered that these correlations decrease and break down under drug action and during slow-wave sleep. These findings provide important mechanistic and functional links to understand the changing information processing capabilities of the brain.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Mathematics, Interdisciplinary Applications
Frank Schweitzer, Antonios Garas, Mario Tomasello, Giacomo Vaccario, Luca Verginer
Summary: We used a data-driven agent-based model to study the core-periphery structure of two collaboration networks, and introduced a coreness value to characterize the network embeddedness of agents. The study found that the coreness values of collaboration partners were consistent with the empirical coreness differences, and explained the reason for the change in partner selection for agents with high network embeddedness.
ADVANCES IN COMPLEX SYSTEMS
(2022)
Editorial Material
Mathematics, Interdisciplinary Applications
Miguel Fuentes, Claudio J. Tessone, Bernardo Alves Furtado
Article
Physics, Multidisciplinary
Frank Schweitzer
Summary: We evaluate the robustness and adaptivity of social groups with heterogeneous agents, characterized by binary states, the ability to change states, status, and preferred relations to other agents. The hexagrams of the I Ching are operationalized to define group structures, and the influence of agents is quantified based on the social impact theory. We propose a weighted stability measure for triads involving three agents, which combines robustness and adaptivity to determine group resilience. A stochastic approach is used to determine the probabilities of finding robust and adaptive groups. The discussion focuses on the generalization of the approach.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Bo-Lun Chen, Wen-Xin Jiang, Yong-Tao Yu, Lei Zhou, Claudio J. Tessone
Summary: This study introduces the concept of swarm intelligence in social networks to simulate the propagation of negative influence using ant colony, and identifies high-value and low-cost suppression nodes. Experimental results show that the proposed algorithm effectively limits the spread of negative influence.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Political Science
Laurence Brandenberger, Giona Casiraghi, Georges Andres, Simon Schweighofer, Frank Schweitzer
Summary: This study compares online and offline political support among members of the Swiss National Council and finds that online endorsements are predominantly driven by partisanship and lack the diversity found in offline support behavior.
SWISS POLITICAL SCIENCE REVIEW
(2022)
Article
Physics, Multidisciplinary
Francesco Maria De Collibus, Matija Piskorec, Alberto Partida, Claudio J. Tessone
Summary: This paper applies network science methods to analyze the transaction networks of tokens on the Ethereum blockchain, focusing on the importance of smart contracts and exchange-related addresses. The study reveals that these addresses play a structural role in transaction networks in both DeFi and Ethereum.
Article
Mathematics, Interdisciplinary Applications
Edoardo Fadda, Junda He, Claudio J. Tessone, Paolo Barucca
Summary: Research shows that in blockchain systems, nodes with central positions can more easily form a majority in the consensus process, and the network topology plays a significant role in the consensus formation.
Article
Mathematics, Interdisciplinary Applications
Frank Schweitzer, Georges Andres, Giona Casiraghi, Christoph Gote, Ramona Roller, Ingo Scholtes, Giacomo Vaccario, Christian Zingg
Summary: Resilience refers to the ability of a system to resist shocks and recover from them. A framework has been developed to quantify the resilience of volatile social organizations, such as collectives or collaborating teams. It involves four steps: delimitation, conceptualization, formal representation, and operationalization.
ADVANCES IN COMPLEX SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Christoph Gote, Giona Casiraghi, Frank Schweitzer, Ingo Scholtes
Summary: In addition to nodes and links, data on paths is important for understanding the structure and dynamics of complex systems. Accurately modeling and predicting paths is also crucial for engineered systems. This paper introduces MOGen, a generative modeling framework that can predict paths with high accuracy and consistency. It automatically selects the optimal model from data, making it parameter-free, and outperforms state-of-the-art sequence modeling techniques in empirical data.
APPLIED NETWORK SCIENCE
(2023)
Proceedings Paper
Computer Science, Cybernetics
Luka Petrovic, Ingo Scholtes
Summary: We address the problem of learning the Markov order in categorical sequences representing paths in a network. We develop a Bayesian learning technique that detects the correct Markov order reliably, requires less data, and is robust against partial knowledge of the underlying constraints.
PROCEEDINGS OF THE ACM WEB CONFERENCE 2022 (WWW'22)
(2022)
Article
Mathematics, Interdisciplinary Applications
Timothy LaRock, Ingo Scholtes, Tina Eliassi-Rad
Summary: This research focuses on counting and analyzing sequential motifs in trajectory data and proposes a method to evaluate their importance by mapping edges of higher-order network models to sequential motifs. The results demonstrate that these sequential motifs correspond to traversal patterns in real systems.
JOURNAL OF COMPLEX NETWORKS
(2022)
Article
Physics, Fluids & Plasmas
Nikos Papanikolaou, Giacomo Vaccario, Erik Hormann, Renaud Lambiotte, Frank Schweitzer
Summary: This study investigates the impact of group interactions on the emergence of consensus in a spin system. The research finds that group interactions amplify initial opinion biases, accelerate consensus formation, and result in a drift of the average magnetization.
Article
Physics, Fluids & Plasmas
Frank Schweitzer, Georges Andres
Summary: This article examines the formation and development of social groups, and the impact of different parameters on their formation and coexistence. Using an agent-based model and analytic investigations, critical density parameters that control the formation and coexistence of groups are derived.
