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From the perspective of network analysis, the ubiquitous networks are comprised of regular and irregular components, which makes uncovering the complexity of network structures to be a fundamental challenge. Exploring the regular…

Social and Information Networks · Computer Science 2018-08-30 Tao Wu , Shaojie Qiao , Xingping Xian , Xi-Zhao Wang , Wei Wang , Yanbing Liu

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing demand, the introduction of distributed renewable energy sources, and the…

Physics and Society · Physics 2016-07-13 Antonio Scala , Pier Giorgio De Sanctis Lucentini

Considering diffusion in the presence of asymmetric disorder, an exact relationship between the strength of weak disorder and the electric resistance of the corresponding resistor network is revealed, which is valid in arbitrary networks.…

Disordered Systems and Neural Networks · Physics 2015-06-04 Róbert Juhász

We introduce the concept of natural connectivity as a robustness measure of complex networks. The natural connectivity has a clear physical meaning and a simple mathematical formulation. It characterizes the redundancy of alternative paths…

Statistical Mechanics · Physics 2008-02-20 Jun Wu , Yue-Jin Tan , Hong-Zhong Deng , Yong Li , Bin Liu , Xin Lv

Using dimensionally reduced models for the numerical simulation of thin objects is highly attractive as this reduces the computational work substantially. The case of narrow thin elastic bands is considered and a convergent finite element…

Numerical Analysis · Mathematics 2019-11-20 Sören Bartels

We present time-efficient distributed algorithms for decomposing graphs with large edge or vertex connectivity into multiple spanning or dominating trees, respectively. As their primary applications, these decompositions allow us to achieve…

Data Structures and Algorithms · Computer Science 2013-11-22 Keren Censor-Hillel , Mohsen Ghaffari , Fabian Kuhn

We investigate the role of architected thin films in the interfacial failure properties of bi-layer composites. Our results show that, while graded structures can be used to prescribe failure at the interface, they do not offer significant…

Materials Science · Physics 2026-03-10 Christian Greff , Leon Pyka , Michael Zaiser , Paolo Moretti

When circuits are set up and dismantled dynamically in elastic optical networks, spectrum tends to become fragmented in the fiber links. The fragmentation limits the available path choices and may lead to significant blocking of connection…

Networking and Internet Architecture · Computer Science 2022-11-07 Anjali Sharma , Varsha Lohani , Yatindra Nath Singh

In this paper the problem of a plane strain hydraulic fracture in elasto-plastic material is analyzed. The analysis is based on Finite Element Method computations of crack propagation and closure to simulate the Mini-Frac calibration test.…

Materials Science · Physics 2022-12-06 Michal Wrobel , Panos Papanastasiou , Martin Dutko

This paper introduces a chordal decomposition approach for scalable analysis of linear networked systems, including stability, $\mathcal{H}_2$ and $\mathcal{H}_{\infty}$ performance. Our main strategy is to exploit any sparsity within these…

Optimization and Control · Mathematics 2018-03-19 Yang Zheng , Maryam Kamgarpour , Aivar Sootla , Antonis Papachristodoulou

We explore the robustness of complex networks against physical damage. We focus on spatially embedded network models and datasets where links are physical objects or physically transfer some quantity, which can be disrupted at any point…

Statistical Mechanics · Physics 2024-12-13 Luka Blagojević , Ivan Bonamassa , Márton Pósfai

Dropout and DropConnect are well-known techniques that apply a consistent drop rate to randomly deactivate neurons or edges in a neural network layer during training. This paper introduces a novel methodology that assigns dynamic drop rates…

Machine Learning · Computer Science 2025-02-28 Yuan-Chih Yang , Hung-Hsuan Chen

The rapid advancement of technology underscores the critical importance of robustness in complex network systems. This paper presents a framework for investigating the structural robustness of interconnected network models. This paper…

Physics and Society · Physics 2023-11-01 Dong Gaogao , Sun Nannan , Wang Fan

Deep neural network architectures often consist of repetitive structural elements. We introduce an approach that reveals these patterns and can be broadly applied to the study of deep learning. Similarly to how a power strip helps untangle…

Statistical Mechanics · Physics 2025-07-03 Donghee Lee , Hye-Sung Lee , Jaeok Yi

The theory of disordered elastic systems is one of the most powerful frameworks to assess the physics of multiple systems that span from ferromagnets to migrating biological cells. In this formalism, one assumes that the system can be…

Disordered Systems and Neural Networks · Physics 2022-11-28 Nirvana Caballero , Thierry Giamarchi

This paper theoretically analyzes cable network disconnection due to randomly occurring natural disasters, where the disaster-endurance (DE) levels of the network are determined by a network entity such as the type of shielding method used…

Networking and Internet Architecture · Computer Science 2021-05-04 Hiroshi Saito

We propose a mathematical framework for designing robust networks of coupled phase-oscillators by leveraging a vulnerability measure proposed by Tyloo et. al that quantifies how much a small perturbation to a phase-oscillator's natural…

Optimization and Control · Mathematics 2023-08-14 Shriya V. Nagpal , Gokul G. Nair , Francesca Parise , C. Lindsay Anderson

We show that the problem of recovering the topology and admittance of an electrical network from power and voltage data at all vertices is often ill-posed, and sometimes it even has multiple solutions. We reformulate the problem to seek for…

Optimization and Control · Mathematics 2026-01-19 Álvaro Samperio

In this paper we present a general procedure that allows for the reduction or expansion of any network (considered as a weighted graph). This procedure maintains the spectrum of the network's adjacency matrix up to a set of eigenvalues…

Dynamical Systems · Mathematics 2011-11-15 L. A. Bunimovich , B. Z. Webb

While renormalization groups are fundamental in physics, renormalization of complex networks remains vague in its conceptual definition and methodology. Here, we propose a novel strategy to renormalize complex networks. Rather than…

Statistical Mechanics · Physics 2024-03-13 Sungwon Jung , Sang Hoon Lee , Jaeyoon Cho
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