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Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several…

Quantitative Methods · Quantitative Biology 2018-02-06 M. De Domenico

We consider the application of multilevel Monte Carlo methods to steady state Darcy flow in a random porous medium, described mathematically by elliptic partial differential equations with random coefficients. The levels in the multilevel…

Numerical Analysis · Mathematics 2015-06-16 Minho Park , Aretha Teckentrup

A finite-volume scheme for a cross-diffusion model arising from the mean-field limit of an interacting particle system for multiple population species is studied. The existence of discrete solutions and a discrete entropy production…

Numerical Analysis · Mathematics 2019-11-27 Ansgar Jüngel , Antoine Zurek

In this paper, I outline several conceptual and methodological issues related to modeling individual and group processes embedded in clustered/hierarchical data structures. We position multilevel modeling techniques within a broader set of…

Methodology · Statistics 2022-12-29 Amira Ibrahim El-Desokey

The study of quantum evolution on graphs for diversified topologies is beneficial to modeling various realistic systems. A systematic method, the dimerized decomposition, is proposed to analyze the dynamics on an arbitrary network. By…

Quantum Physics · Physics 2020-03-04 He Feng , Tian-Min Yan , Y. H. Jiang

The correct choice of interface conditions and effective parameters for coupled macroscale free-flow and porous-medium models is crucial for a complete mathematical description of the problem under consideration and for accurate numerical…

Numerical Analysis · Mathematics 2019-06-27 Iryna Rybak , Christoph Schwarzmeier , Elissa Eggenweiler , Ulrich Rüde

Permeability is the key parameter for quantifying fluid flow in porous rocks. Knowledge of the spatial distribution of the connected pore space allows, in principle, to predict the permeability of a rock sample. However, limitations in…

This paper deals with the derivation of a collective model of cell populations out of an individual-based description of the underlying physical particle system. By looking at the spatial distribution of cells in terms of time-evolving…

Mathematical Physics · Physics 2014-11-12 Annachiara Colombi , Marco Scianna , Andrea Tosin

Networks are important structures used to model complex systems where interactions take place. In a basic network model, entities are represented as nodes, and interaction and relations among them are represented as edges. However, in a…

Social and Information Networks · Computer Science 2021-02-18 Mehmet Emin Aktas , Esra Akbas

Latent variable models for network data extract a summary of the relational structure underlying an observed network. The simplest possible models subdivide nodes of the network into clusters; the probability of a link between any two nodes…

Machine Learning · Computer Science 2012-07-03 Konstantina Palla , David Knowles , Zoubin Ghahramani

The modeling of multi-phase flow is very challenging, given the range of scales as well as the diversity of flow regimes that one encounters in this context. We revisit the discrete equation method (DEM) for two-phase flow in the absence of…

Numerical Analysis · Mathematics 2023-03-01 Marco Petrella , Remi Abgrall , Siddhartha Mishra

Large datasets with interactions between objects are common to numerous scientific fields (i.e. social science, internet, biology...). The interactions naturally define a graph and a common way to explore or summarize such dataset is graph…

Applications · Statistics 2009-10-13 Hugo Zanghi , Stevenn Volant , Christophe Ambroise

The structure of real-world networks is usually difficult to characterize owing to the variation of topological scales, the nondyadic complex interactions, and the fluctuations in the network. We aim to address these problems by introducing…

Social and Information Networks · Computer Science 2019-09-25 Quoc Hoan Tran , Van Tuan Vo , Yoshihiko Hasegawa

In this paper we propose a new modeling framework for large eddy simulations (LES) of particle-laden turbulent flows that captures the interaction between the particle and fluid phase on both the resolved and subgrid-scales. Unlike the vast…

Fluid Dynamics · Physics 2023-10-26 Max Hausmann , Fabien Evrard , Berend van Wachem

A major challenge in flow through porous media is to better understand the link between microstructure and macroscale flow and transport. For idealised microstructures, the mathematical framework of homogenisation theory can be used for…

In this note we introduce a mixed dimensional Stokes-Darcy coupling where a $d$ dimensional Stokes' flow is coupled to a Darcy model on the $d-1$ dimensional boundary of the domain. The porous layer introduces tangential creeping flow along…

Numerical Analysis · Mathematics 2019-12-19 Erik Burman , Miguel A. Fernández , Stefan Frei , Fannie M. Gerosa

We introduce the Iterated Global model as a deterministic graph process that simulates several properties of complex networks. In this model, for every set $S$ of nodes of a prescribed cardinality, we add a new node that is adjacent to…

Discrete Mathematics · Computer Science 2020-02-21 Anthony Bonato , Erin Meger

Comprehending complex systems by simplifying and highlighting important dynamical patterns requires modeling and mapping higher-order network flows. However, complex systems come in many forms and demand a range of representations,…

Social and Information Networks · Computer Science 2017-10-18 Daniel Edler , Ludvig Bohlin , Martin Rosvall

In this work, we analyze the flow filtration process of slightly compressible fluids in porous media containing man made fractures with complex geometries. We model the coupled fracture-porous media system where the linear Darcy flow is…

Analysis of PDEs · Mathematics 2024-05-29 Pushpi Paranamana , Eugenio Aulisa , Akif Ibragimov , Magdalena Toda

A wide variety of complex networks (social, biological, information etc.) exhibit local clustering with substantial variation in the clustering coefficient (the probability of neighbors being connected). Existing models of large graphs…

Discrete Mathematics · Computer Science 2017-09-28 Samantha Petti , Santosh Vempala
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