Article
Engineering, Mechanical
Lin Zhang, Zeyang Cheng, Huiying Wen, Da Lei, Shubin Li
Summary: With the interdisciplinary study between transportation and network topological dynamics, this research focuses on exploring vulnerability bottlenecks in large-scale bus transit networks by distinguishing and simulating two types of disruptions based on different stakeholders' concerns. An integrated vulnerability evaluation indicator is designed to compare attacks at various scales and perspectives. The case study reveals that the areas accessing and interacting with urban rail transit stations are vulnerability bottlenecks, and the destructiveness of a failure edge is linked to the scale of sudden failures it constitutes. This research improves the understanding of disruptions and provides insights for operational management policies.
NONLINEAR DYNAMICS
(2022)
Article
Physics, Multidisciplinary
Flavio Iannelli, Igor M. Sokolov
Summary: The path-integral formulation of network-based measures extends the concept of geodesic distance, offering insights into disease transmission dynamics and efficient numerical estimation of infection arrival time.
EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS
(2021)
Article
Multidisciplinary Sciences
Mansi Sood, Anirudh Sridhar, Rashad Eletreby, Chai Wah Wu, Simon A. Levin, Osman Yagan, H. Vincent Poor
Summary: A key scientific challenge during the outbreak of novel infectious diseases is predicting changes in the epidemic under countermeasures that limit population interaction. Pathogens have the capacity to mutate and new strains can emerge, posing a threat to public health. Different transmission risks in different settings and the emergence of new strains should be considered when evaluating the impact of mitigation measures.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Physics, Multidisciplinary
Xiuming Zhao, Hongtao Yu, Shaomei Li, Shuxin Liu, Jianpeng Zhang, Xiaochun Cao
Summary: Most real-world networks, particularly biological and social networks, are complex and dynamic. Existing models often overlook the effects of memory, which is proven to be important in network evolution and dynamic processes. To address this gap, we propose a novel model that incorporates memory, accurately representing multi-node interactions in network dynamics.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Physics, Multidisciplinary
Hanlin Sun, David Saad, Andrey Y. Lokhov
Summary: Competition and collaboration play crucial roles in multiagent probabilistic spreading processes, with examples including competitive marketing campaigns and joint spread of infectious diseases. By deriving dynamic message-passing equations and developing low-complexity models, the dynamics of spreading processes on networks can be predicted. A theoretical framework for optimal control through optimized resource allocation has been proposed, and the efficacy of the framework and optimization method has been demonstrated on both synthetic and real-world networks.
Article
Physics, Fluids & Plasmas
Davide Ghio, Antoine L. M. Aragon, Indaco Biazzo, Lenka Zdeborova
Summary: This study focuses on a class of spreading processes on networks and analyzes the inference of dynamics based on partial observations. The belief propagation algorithm is used to solve these inference problems on random networks. The research investigates whether the algorithm performs optimally by analyzing the Nishimori conditions. The findings suggest that the algorithm can solve the problems optimally in most parameter regions, but struggles to converge in limited areas due to finite-size effects.
Article
Computer Science, Artificial Intelligence
Jie Yang, Yu Wu
Summary: This paper investigates using changes in network structure to identify bursty events, which is more sensitive and widely applicable compared to text-based methods.
APPLIED INTELLIGENCE
(2022)
Article
Mathematics, Interdisciplinary Applications
Haofei Yin, Aobo Zhang, An Zeng
Summary: Using measurable data for targeted spreading of vital nodes in complex networks is crucial for real-world applications such as advertising and military attack. However, the challenge lies in identifying target nodes, which obstructs the optimal allocation of initial spreaders. This study presents a framework to solve this issue, mapping target node identification to underdetermined equations using a compressed sensing algorithm.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Physics, Fluids & Plasmas
Lukasz G. Gajewski, Jan Choloniewski, Mateusz Wilinski
Summary: When dealing with spreading processes on networks, testing data reliability and identifying potential unobserved spreading paths are of utmost importance. This paper proposes methods for hidden layer identification and reconstruction, showing success rates exceeding those of a null model. By analyzing synthetic and real-world networks, evidence for the viability of the approach presented is provided.
Article
Biology
Yingnan Hou, Tengyu Xie, Liuqing He, Liang Tao, Jing Huang
Summary: The study revealed the presence of topological links in protein complexes predicted by AlphaFold-Multimer, highlighting the significance for protein structure prediction and the study of protein-protein interactions.
COMMUNICATIONS BIOLOGY
(2023)
Review
Automation & Control Systems
Kazumune Hashimoto, Yuga Onoue, Masaki Ogura, Toshimitsu Ushio
Summary: The paper investigates the design of event-triggered controllers for containing epidemic processes in complex networks, focusing on the susceptible-infected-susceptible (SIS) model. It analyzes the stability of the proposed controller and derives a sufficient condition for achieving control objectives. A novel emulation-based approach is proposed for designing the event-triggered controller, showing effectiveness through numerical simulations in an air transportation network.
ANNUAL REVIEWS IN CONTROL
(2021)
Article
Multidisciplinary Sciences
Douglas Guilbeault, Damon Centola
Summary: The study highlights the differences between complex contagions and simple contagions, showing that exposure to multiple peers may be necessary for adoption in complex contagions. Traditional measures of path length fail to accurately define network connectedness and node centrality for complex contagions. To address this issue, researchers have developed new measures of complex path length and complex centrality.
NATURE COMMUNICATIONS
(2021)
Article
Mathematics, Interdisciplinary Applications
Jun Ai, Tao He, Zhan Su, Lihui Shang
Summary: The identification of node importance is a challenging topic in network science. This paper proposes a novel method based on node propagation capability to measure the importance of nodes, and validates the effectiveness of the method through empirical analysis.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Physics, Multidisciplinary
Giulia Cencetti, Diego Andres Contreras, Marco Mancastroppa, Alain Barrat
Summary: Contagion processes on networks can be described as simple or complex contagion, but it is difficult to determine the underlying mechanism based on empirical data. We propose a strategy to distinguish between these mechanisms by observing the order of node infection and its correlation with local topology. Our results enhance understanding of contagion processes and offer a method to differentiate between different contagion mechanisms with limited information.
PHYSICAL REVIEW LETTERS
(2023)
Article
Multidisciplinary Sciences
Casey Doyle, Thushara Gunda, Asmeret Naugle
Summary: In this paper, the effects of corporate hierarchies on innovation spread across multilayer networks are explored using an elaborated SIR framework. It is found that adding management layers can significantly improve spreading processes, and utilizing a more centralized working relationship network can further increase innovation reach. The selection of seed nodes also affects the stability of the adopted community, with nodes near high positions sometimes producing larger and more stable peak adoption.
Article
Physiology
Abbas Karimi Rizi, Mina Zamani, Amirhossein Shirazi, G. Reza Jafari, Janos Kertesz
Summary: Genes communicate through regulatory effects, leading to different network structures in cells, with differences observed between normal and cancerous cells. The study found that cancer cells have fewer imbalanced triangles in their network compared to normal cells, where such motifs are isolated from the main part of the network. This suggests that the structure of complex networks in cancer cells differs from that of normal cells due to genes' collective behavior.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Multidisciplinary Sciences
Gergo Toth, Johannes Wachs, Riccardo Di Clemente, Akos Jakobi, Bence Sagvari, Janos Kertesz, Balazs Lengyel
Summary: Social networks amplify inequalities through mechanisms such as homophily and triadic closure, leading to social segregation reflected in fragmented network structures. Geographical barriers like rivers and railroads in towns contribute to higher network fragmentation, along with neighborhoods being distant from the town center and amenities being spatially concentrated. These urban geography features are shown to have significant relationships with income inequality via social network fragmentation.
NATURE COMMUNICATIONS
(2021)
Article
Mathematics, Interdisciplinary Applications
Hao Cui, Janos Kertesz
Summary: Understanding attention dynamics on social media during pandemics could help governments minimize the effects. This study focused on how COVID-19 influenced attention dynamics on Sina Weibo, analyzing the changes in hashtag topics on the HSL during the pandemic. Significant increase of COVID-19 related hashtags started appearing on HSL around January 20, reaching 30-70% of the list. Three key periods were identified during the investigation, showing changes in topical correlations and clustering across different stages.
Article
Physics, Multidisciplinary
Olalla A. Castro-Alvaredo, David X. Horvath
Summary: The quantum sine-Gordon model is studied in this paper, focusing on the computation of low particle-number form factors and the correlation functions of the branch point twist field for measuring entanglement. The theory's attractive regime with solitons, antisolitons, and breathers is considered, with form factors computed using the fusion procedure. The study shows undamped oscillations in von Neumann and Renyi entropies over time, with frequencies and amplitudes related to the breather masses and form factors respectively.
Article
Multidisciplinary Sciences
Pierluigi Contucci, Janos Kertesz, Godwin Osabutey
Summary: The advent of artificial intelligence machines can be seen as both an opportunity and a threat. This study proposes a model that simulates a Human-AI ecosystem to examine the effects of different proportions of artificial intelligence agents. The findings suggest that even small changes in these proportions can result in dramatic changes for the system.
Article
Multidisciplinary Sciences
Christian Diem, Andras Borsos, Tobias Reisch, Janos Kertesz, Stefan Thurner
Summary: Crises like COVID-19 have revealed the vulnerability of highly interconnected corporate supply networks and the complex production processes they rely on. This study uses a unique value added tax dataset to construct a firm-level production network for an entire country and proposes a novel approach to calculate the economic systemic risk of all firms within this network. The findings indicate that a small percentage of companies have exceptionally high risk, and any default by them could significantly impact national economic production. Firm size does not explain individual companies' risk, but their position in the production network is crucial.
SCIENTIFIC REPORTS
(2022)
Article
Physics, Particles & Fields
Luca Capizzi, David X. Horvath, Pasquale Calabrese, Olalla A. Castro-Alvaredo
Summary: In this paper, the form factor bootstrap approach is applied to branch point twist fields in the q-state Potts model for q <= 3. The model is an integrable interacting quantum field theory with an internal discrete Z(3) symmetry for q = 3, making it an ideal starting point for investigating symmetry resolved entanglement entropies. Furthermore, the standard Renyi and entanglement entropies can also be accessed through the bootstrap program for q <= 3. Form factor solutions are presented for both the standard branch point twist field with q <= 3 and the composite branch point twist field with q = 3, with the solutions carefully checked via the Delta-sum rule. The leading finite-size corrections to the entanglement entropy and entanglement equipartition for a single interval in the ground state are computed using the analytical predictions.
JOURNAL OF HIGH ENERGY PHYSICS
(2022)
Article
Physics, Multidisciplinary
David Horvath, Pasquale Calabrese, Olalla Castro-Alvaredo
Summary: In this paper, we continue our study of entanglement measures in the sine-Gordon model. We focus on the symmetry resolved entanglement and develop its associated twist field description. We solve the form factor equations for various examples in the breather sector and show that the leading contribution to the symmetry resolved entanglement is independent of the symmetry sector.
Article
Physics, Multidisciplinary
David X. Horvath, Spyros Sotiriadis, Marton Kormos, Gabor Takacs
Summary: We study inhomogeneous quantum quenches in the attractive regime of the sine-Gordon model. We observe an interesting transition in the expectation value of the soliton density by varying either the interaction strength of the sine-Gordon model or the amplitude of the external source field. The interplay between bosonic and fermionic excitations influences the dynamics of the system in arbitrary inhomogeneous settings.
Article
Computer Science, Interdisciplinary Applications
D. X. Horvth, K. Hdsgi, G. Takcs
Summary: The Truncated Conformal Space Approach (TCSA) is an efficient method for computing spectra, operator matrix elements, and time evolution in quantum field theories. The Chirally Factorised TCSA (CFTCSA) algorithm improves the truncation level and allows for more precise calculations and larger Hilbert space dimensions.
COMPUTER PHYSICS COMMUNICATIONS
(2022)
Article
Mechanics
Stefano Scopa, David X. Horvath
Summary: The study investigates the non-equilibrium dynamics of symmetry-resolved Renyi entropies in a one-dimensional gas of non-interacting spinless fermions using quantum generalised hydrodynamics. The research shows an asymptotic logarithmic growth of charged moments at half system and an asymptotic restoration of equipartition of entropy among symmetry sectors with deviations proportional to the square of the inverse of the total entropy as time and the entangling position change.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Mathematics, Interdisciplinary Applications
Antonio F. Peralta, Janos Kertesz, Gerardo Iniguez
Summary: The study investigates opinion dynamics and information spreading on networks affected by content filtering technologies. It discovers evolution equations for global opinion variables considering algorithmic bias, network community structure, noise, and interactions. The research reveals that a strong imbalance in favor of one opinion on social platforms can determine the final global opinion and population dynamics.
JOURNAL OF PHYSICS-COMPLEXITY
(2021)
Article
Physics, Particles & Fields
David X. Horvath, Luca Capizzi, Pasquale Calabrese
Summary: In this study, the form factor bootstrap approach is extended to integrable field theories with U(1) symmetry to derive matrix elements of composite branch-point twist fields associated with symmetry resolved entanglement entropies. The exact and complete solution for the bootstrap equations is presented for the free massive Dirac and complex boson theories, including vacuum expectation values and form factors involving any type and arbitrarily number of particles. The novel form factors of the U(1) composite branch-point twist fields allow for the re-derivation of earlier results showing entanglement equipartition for an interval in the ground state of the two models.
JOURNAL OF HIGH ENERGY PHYSICS
(2021)
Article
Computer Science, Artificial Intelligence
Johannes Wachs, Mihaly Fazekas, Janos Kertesz
Summary: Using network science methods, we analyzed over 4 million public procurement contracts from European Union member states from 2008 to 2016 to identify the distribution of corruption risk. We found that highly centralized markets tend to have higher corruption risk, and corruption risk is significantly clustered in all EU countries analyzed. The same level of corruption risk may have entirely different distributions in different countries.
INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS
(2021)
Article
Ethics
Mirco Nanni, Gennady Andrienko, Albert-Laszlo Barabasi, Chiara Boldrini, Francesco Bonchi, Ciro Cattuto, Francesca Chiaromonte, Giovanni Comande, Marco Conti, Mark Cote, Frank Dignum, Virginia Dignum, Josep Domingo-Ferrer, Paolo Ferragina, Fosca Giannotti, Riccardo Guidotti, Dirk Helbing, Kimmo Kaski, Janos Kertesz, Sune Lehmann, Bruno Lepri, Paul Lukowicz, Stan Matwin, David Megias Jimenez, Anna Monreale, Katharina Morik, Nuria Oliver, Andrea Passarella, Andrea Passerini, Dino Pedreschi, Alex Pentland, Fabio Pianesi, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Arno Siebes, Vicenc Torra, Roberto Trasarti, Jeroen van den Hoven, Alessandro Vespignani
Summary: The rapid spread of COVID-19 requires quick and effective tracking of virus transmission chains and early detection of outbreaks, especially as lockdown measures are lifted. A decentralized approach to contact-tracing apps offers better protection of citizens' privacy and allows for detailed information gathering for infected individuals in a privacy-preserving manner, enabling more effective contact tracing and early detection of outbreak hotspots.
ETHICS AND INFORMATION TECHNOLOGY
(2021)