scholarly journals Optimal resilience of modular interacting networks

2021 ◽  
Vol 118 (22) ◽  
pp. e1922831118
Author(s):  
Gaogao Dong ◽  
Fan Wang ◽  
Louis M. Shekhtman ◽  
Michael M. Danziger ◽  
Jingfang Fan ◽  
...  
Keyword(s):  
Phase Transition ◽  
Functional Properties ◽  
Real World ◽  
Theoretical Models ◽  
Network Resilience ◽  
World Systems ◽  
Optimal Point ◽  
Exact Location ◽  
Modular Networks ◽  
Interacting Networks

Coupling between networks is widely prevalent in real systems and has dramatic effects on their resilience and functional properties. However, current theoretical models tend to assume homogeneous coupling where all the various subcomponents interact with one another, whereas real-world systems tend to have various different coupling patterns. We develop two frameworks to explore the resilience of such modular networks, including specific deterministic coupling patterns and coupling patterns where specific subnetworks are connected randomly. We find both analytically and numerically that the location of the percolation phase transition varies nonmonotonically with the fraction of interconnected nodes when the total number of interconnecting links remains fixed. Furthermore, there exists an optimal fraction r* of interconnected nodes where the system becomes optimally resilient and is able to withstand more damage. Our results suggest that, although the exact location of the optimal r* varies based on the coupling patterns, for all coupling patterns, there exists such an optimal point. Our findings provide a deeper understanding of network resilience and show how networks can be optimized based on their specific coupling patterns.

Phenomenological Modelling

2018 ◽  
Author(s):  
Ray Huffaker ◽  
Marco Bittelli ◽  
Rodolfo Rosa
Keyword(s):  
Nonlinear Dynamics ◽  
Time Series ◽  
Real World ◽  
Biological Diversity ◽  
False Positives ◽  
World Systems ◽  
Economic Activities ◽  
Essential Services ◽  
Low Dimension ◽  
Convergent Cross Mapping

Detecting causal interactions among climatic, environmental, and human forces in complex biophysical systems is essential for understanding how these systems function and how public policies can be devised that protect the flow of essential services to biological diversity, agriculture, and other core economic activities. Convergent Cross Mapping (CCM) detects causal networks in real-world systems diagnosed with deterministic, low-dimension, and nonlinear dynamics. If CCM detects correspondence between phase spaces reconstructed from observed time series variables, then the variables are determined to causally interact in the same dynamic system. CCM can give false positives by misconstruing synchronized variables as causally interactive. Extended (delayed) CCM screens for false positives among synchronized variables.

scholarly journals Higher-order temporal network effects through triplet evolution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qing Yao ◽  
Bingsheng Chen ◽  
Tim S. Evans ◽  
Kim Christensen
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Higher Order ◽  
Prediction Algorithm ◽  
Interaction Patterns ◽  
Temporal Networks ◽  
World Systems ◽  
Order Interaction ◽  
Space And Time ◽  
Pairwise Interactions

AbstractWe study the evolution of networks through ‘triplets’—three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems.

scholarly journals Asymmetry underlies stability in power grids

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ferenc Molnar ◽  
Takashi Nishikawa ◽  
Adilson E. Motter
Keyword(s):  
Symmetry Breaking ◽  
Real World ◽  
Power Grids ◽  
Stable Operation ◽  
World Systems ◽  
Symmetric State ◽  
Network Systems ◽  
Additional Improvement ◽  
The Stability ◽  
General Method

AbstractBehavioral homogeneity is often critical for the functioning of network systems of interacting entities. In power grids, whose stable operation requires generator frequencies to be synchronized—and thus homogeneous—across the network, previous work suggests that the stability of synchronous states can be improved by making the generators homogeneous. Here, we show that a substantial additional improvement is possible by instead making the generators suitably heterogeneous. We develop a general method for attributing this counterintuitive effect to converse symmetry breaking, a recently established phenomenon in which the system must be asymmetric to maintain a stable symmetric state. These findings constitute the first demonstration of converse symmetry breaking in real-world systems, and our method promises to enable identification of this phenomenon in other networks whose functions rely on behavioral homogeneity.

scholarly journals Modeling and simulation of economic processes

2010 ◽  
Author(s):  
Bogdan Brumar
Keyword(s):  
Decision Analysis ◽  
Modeling And Simulation ◽  
Real World ◽  
Analytical Methods ◽  
Simulation Experiment ◽  
Management Decision ◽  
Economic Systems ◽  
World Systems ◽  
Simulation Techniques ◽  
Laborious Work

In general, any activity requires a longer action often characterized by a degree of uncertainty, insecurity, in terms of size of the objective pursued. Because of the complexity of real economic systems, the stochastic dependencies between different variables and parameters considered, not all systems can be adequately represented by a model that can be solved by analytical methods and covering all issues for management decision analysis-economic horizon real. Often in such cases, it is considered that the simulation technique is the only alternative available. Using simulation techniques to study real-world systems often requires a laborious work. Making a simulation experiment is a process that takes place in several stages.

scholarly journals Interactions of Na+ Cations with a Highly Charged Fatty Acid Langmuir Monolayer: Molecular Description of the Phase Transition

2019 ◽  
Author(s):  
Adrien Sthoer ◽  
Eric Tyrode
Keyword(s):  
Phase Transition ◽  
Surface Charge ◽  
Surface Potential ◽  
Arachidic Acid ◽  
Ion Pairs ◽  
Theoretical Models ◽  
Langmuir Monolayer ◽  
Vibrational Sum Frequency Spectroscopy ◽  
Ion Size ◽  
Contact Ion Pairs

Vibrational sum frequency spectroscopy has been used to study the molecular properties upon compression of a highly charged arachidic acid Langmuir monolayer, which displays a first order phase transition plateau in the surface pressure - molecular area (p-A) isotherm. By targeting vibrational modes from the carboxylic acid headgroup, alkyl chain, and interfacial water molecules, information regarding the surface charge, surface potential, type of ion pair formed, and conformational order of the monolayer could be extracted. The monolayer in the liquid expanded phase is found to be fully charged until reaching the 2D-phase transition plateau, where partial reprotonation, as well as the formation of COO⎺ Na<sup>+ </sup>contact-ion pairs, start to take place. In the condensed phase after the transition, three headgroup species, mainly hydrated COO⎺, COOH, and COO⎺ Na<sup>+ </sup>contact-ion pairs could be identified and their proportions quantified. Comparison with theoretical models shows that despite the low ionic strengths used (i.e. 10 mM), the predictions from the Gouy Chapman model are only adequate for the lowest surface densities, when the surface charge does not exceed -0.1 C/m<sup>2</sup>. In contrast, a modified Poisson-Boltzmann (MPB) model that accounts for the steric effects associated with the finite ion-size, captures many of the experimental observables, including the partial reprotonation, and surface potential changes upon compression. The agreement highlights the importance of hydronium ion – carboxylate interactions, as well as the layer of sodium ions packed at the steric limit, for explaining the phase transition behavior. The MPB model, however, does not explicitly consider the formation of contact ion pairs with the sodium counterion. The experimental results provide a quantitative molecular insight that could be used to test potential extensions to the theory.

scholarly journals Identifying important nodes from content-associated heterogeneous graph by LeaderRank

2021 ◽  
Vol 2113 (1) ◽  
pp. 012082
Author(s):  
Yulong Dai ◽  
Qiyou Shen ◽  
Xiangqian Xu ◽  
Jun Yang
Keyword(s):  
Real World ◽  
Experimental Analysis ◽  
Differential Information ◽  
World Systems ◽  
Ranking Problem ◽  
Data Set ◽  
Importance Ranking ◽  
Basic Concepts ◽  
Important Nodes ◽  
Graph Nodes

Abstract Most real-world systems consist of a large number of interacting entities of many types. However, most of the current researches on systems are based on the assumption that the type of node or link in the network is unique. In other words, the network is homogeneous, containing the same type of nodes and links. Based on this assumption, differential information between nodes and edges is ignored. This paper firstly introduces the research background, challenges and significance of this research. Secondly, the basic concepts of the model are introduced. Thirdly, a novel type-sensitive LeaderRank algorithm is proposed and combined with distance rule to solve the importance ranking problem of content-associated heterogeneous graph nodes. Finally, the writer influence data set is used for experimental analysis to further prove the validity of the model.

Sign in / Sign up

Export Citation Format

Share Document