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Series-parallel network topologies generally exhibit simplified dynamical behavior and avoid high combinatorial complexity. A comprehensive analysis of how flow complexity emerges with a graph's deviation from series-parallel topology is…

Systems and Control · Electrical Eng. & Systems 2024-03-12 Shashank A Deshpande , Hamsa Balakrishnan

Climate change is reshaping species interactions and movement across fragmented landscapes. Despite this, most mathematical models assume random diffusion, overlooking the influence of directed movement. Here, we develop a graph based…

Dynamical Systems · Mathematics 2026-04-08 Pranali Roy Chowdhury , Soumyendu Raha

Topology identification and inference of processes evolving over graphs arise in timely applications involving brain, transportation, financial, power, as well as social and information networks. This chapter provides an overview of graph…

Signal Processing · Electrical Eng. & Systems 2025-12-12 Gonzalo Mateos , Yanning Shen , Georgios B. Giannakis , Ananthram Swami

In this article we demonstrate how graph theory can be used to identify those stations in the London underground network which have the greatest influence on the functionality of the traffic, and proceed, in an innovative way, to assess the…

Signal Processing · Electrical Eng. & Systems 2019-12-19 Bruno Scalzo Dees , Anthony G. Constantinides , Danilo P. Mandic

Rapid reliability assessment of transportation networks can enhance preparedness, risk mitigation, and response management procedures related to these systems. Network reliability analysis commonly considers network-level performance and…

Machine Learning · Computer Science 2024-08-26 Tong Liu , Hadi Meidani

We solve the problem of identifying (reconstructing) network topology from steady state network measurements. Concretely, given only a data matrix $\mathbf{X}$ where the $X_{ij}$ entry corresponds to flow in edge $i$ in configuration…

Machine Learning · Computer Science 2016-01-22 Aravind Rajeswaran , Shankar Narasimhan

Transportation and distribution networks are a class of spatial networks that have been of interest in recent years. These networks are often characterized by the presence of complex structures such as central loops paired with peripheral…

Physics and Society · Physics 2023-01-23 Sebastiano Bontorin , Giulia Cencetti , Riccardo Gallotti , Bruno Lepri , Manlio De Domenico

Modeling power transmission networks is an important area of research with applications such as vulnerability analysis, study of cascading failures, and location of measurement devices. Graph-theoretic approaches have been widely used to…

Link failures in supply networks can have catastrophic consequences that can lead to a complete collapse of the network. Strategies to prevent failure spreading are thus heavily sought after. Here, we make use of a spanning tree formulation…

Physics and Society · Physics 2021-06-09 Franz Kaiser , Dirk Witthaut

Urban mobility forecast and analysis can be addressed through grid-based and graph-based models. However, graph-based representations have the advantage of more realistically depicting the mobility networks and being more robust since they…

Discrete Mathematics · Computer Science 2023-10-11 Rafael Martínez Márquez , Giuseppe Patanè

Power system studies require the topological structures of real-world power networks; however, such data is confidential due to important security concerns. Thus, power grid synthesis (PGS), i.e., creating realistic power grids that imitate…

Social and Information Networks · Computer Science 2019-04-15 Mahdi Khodayar , Jianhui Wang , Zhaoyu Wang

The increasing urban population imposes a substantial and growing burden on the supporting infrastructure, such as electricity, water, heating, natural gas, road transportation, etc. This paper presents a Hetero-functional graph theory…

Systems and Control · Electrical Eng. & Systems 2021-04-30 Sai Munikoti , Kexing Lai , Balasubramaniam Natarajan

The increasing complexity of energy systems due to sector coupling and decarbonization calls for unified modeling frameworks that capture the physical and structural interactions between electricity, gas, and heat networks. This paper…

Systems and Control · Electrical Eng. & Systems 2026-01-08 Marwan Mostafa , Daniel Wenser , Payam Teimourzadeh Baboli , Christian Becker

Deterministic equilibrium flows in transport networks can be investigated by means of Markov's processes defined on the dual graph representations of the network. Sustained movement patterns are generated by a subset of automorphisms of the…

Physics and Society · Physics 2007-10-30 D. Volchenkov , Ph. Blanchard

We live in a world increasingly dominated by networks -- communications, social, information, biological etc. A central attribute of many of these networks is that they are dynamic, that is, they exhibit structural changes over time. While…

Networking and Internet Architecture · Computer Science 2010-12-02 Prithwish Basu , Amotz Bar-Noy , Ram Ramanathan , Matthew P. Johnson

Many physical systems--from mechanical lattices and electrical circuits to biological tissues and architected metamaterials--can be understood as networks transmitting physical quantities. We present a unified mathematical framework for…

Soft Condensed Matter · Physics 2025-08-07 José M. Ortiz-Tavárez , William Stephenson , Xiaoming Mao

Ensuring robustness and resilience in intermodal transportation systems is essential for the continuity and reliability of global logistics. These systems are vulnerable to various disruptions, including natural disasters and technical…

A stable population network is hard to interrupt without any ecological consequences. A communication blockage between patches may destabilize the populations in the ecological network. This work deals with the construction of a safe cut…

Dynamical Systems · Mathematics 2018-04-25 Dinesh Kumar , Jatin Gupta , Soumyendu Raha

Liquid water, besides being fundamental for life on Earth, has long fascinated scientists due to several anomalies. Different hypotheses have been put forward to explain these peculiarities. The most accredited one foresees the presence in…

Numerical Analysis · Mathematics 2022-10-26 Michele Benzi , Isabella Daidone , Chiara Faccio , Laura Zanetti-Polzi

Scattering transforms are non-trainable deep convolutional architectures that exploit the multi-scale resolution of a wavelet filter bank to obtain an appropriate representation of data. More importantly, they are proven invariant to…

Machine Learning · Computer Science 2019-06-13 Fernando Gama , Joan Bruna , Alejandro Ribeiro