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Related papers: Topological Invariants in the Pore Morphology Meth…

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One of the important characteristics of topological phases of matter is the topology of the underlying manifold on which they are defined. In this paper, we present the sensitivity of such phases of matter to the underlying topology, by…

Strongly Correlated Electrons · Physics 2021-10-05 Amit Jamadagni , Arpan Bhattacharyya

This article discusses how the individual morphological properties of basic objects (e.g. neurons, molecules and aggregates), jointly with their particular spatial distribution, can determine the connectivity and dynamics of systems…

Molecular Networks · Quantitative Biology 2007-05-23 Luciano da Fontoura Costa

Topological insulators are insulating in the bulk but feature conducting states on their surfaces. Standard methods for probing their topological properties largely involve probing the surface, even though topological invariants are defined…

The subcritical transition to turbulence, as occurs in pipe flow, is believed to generically be a phase transition in the directed percolation universality class. At its heart is a balance between the decay rate and proliferation rate of…

Fluid Dynamics · Physics 2022-09-16 Anna Frishman , Tobias Grafke

In the last two decades, network science has blossomed and influenced various fields, such as statistical physics, computer science, biology and sociology, from the perspective of the heterogeneous interaction patterns of components…

Physics and Society · Physics 2021-04-20 Ming Li , Run-Ran Liu , Linyuan Lü , Mao-Bin Hu , Shuqi Xu , Yi-Cheng Zhang

The use of machine learning techniques in classical and quantum systems has led to novel techniques to classify ordered and disordered phases, as well as uncover transition points in critical phenomena. Efforts to extend these methods to…

Physics and Society · Physics 2023-10-10 Sayat Mimar , Gourab Ghoshal

The interconnectivity of the porous space is an important characteristic in the study of porous media and their transport properties. Hence we propose a way to quantify it and relate it with the intrinsic permeability of rocks. We propose a…

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds.…

Biological Physics · Physics 2016-07-28 Francis G. Woodhouse , Aden Forrow , Joanna B. Fawcett , Jörn Dunkel

We investigate the geometric properties of loops on two-dimensional lattice graphs, where edge weights are drawn from a distribution that allows for positive and negative weights. We are interested in the appearance of spanning loops of…

Disordered Systems and Neural Networks · Physics 2009-11-13 L. Apolo , O. Melchert , A. K. Hartmann

We show that topology can protect exponentially localized, zero energy edge modes at critical points between one-dimensional symmetry protected topological phases. This is possible even without gapped degrees of freedom in the bulk ---in…

Mesoscale and Nanoscale Physics · Physics 2018-02-02 Ruben Verresen , Nick G. Jones , Frank Pollmann

A model-based description of the scaling and radial location of turbulent fluctuations in turbulent pipe flow is presented and used to illuminate the scaling behaviour of the very large scale motions. The model is derived by treating the…

Fluid Dynamics · Physics 2010-12-06 B. J. McKeon , A. S. Sharma

Percolation is a fundamental concept that brought new understanding on the robustness properties of complex systems. Here we consider percolation on weakly interacting networks, that is, network layers coupled together by much less…

Physics and Society · Physics 2019-04-10 Giacomo Rapisardi , Alex Arenas , Guido Caldarelli , Giulio Cimini

A new kind of invasion percolation is introduced in order to take into account the inertia of the invader fluid. The inertia strength is controlled by the number N of pores (or steps) invaded after the perimeter rupture. The new model…

Statistical Mechanics · Physics 2009-10-31 Reginaldo A. Zara , Roberto N. Onody

Most networks of interest do not live in isolation. Instead they form components of larger systems in which multiple networks with distinct topologies coexist and where elements distributed amongst different networks may interact directly.…

Disordered Systems and Neural Networks · Physics 2009-07-07 E. A. Leicht , Raissa M. D'Souza

We investigate the microscopic mechanisms giving rise to plastic depinning and irreversible flow in vortex matter. The topology of the vortex array crucially determines the flow response of this system. To illustrate this claim, two…

Disordered Systems and Neural Networks · Physics 2015-05-14 Paolo Moretti , M. -Carmen Miguel

When considering flows in biological membranes, they are usually treated as flat, though more often than not, they are curved surfaces, even extremely curved, as in the case of the endoplasmic reticulum. Here, we study the topological…

Fluid Dynamics · Physics 2021-05-27 Rickmoy Samanta , Naomi Oppenheimer

The internal organization of complex networks often has striking consequences on either their response to external perturbations or on their dynamical properties. In addition to small-world and scale-free properties, clustering is the most…

Physics and Society · Physics 2014-05-26 Pol Colomer-de-Simon , Marian Boguna

Recent experiments on mucociliary clearance, an important defense against airborne pathogens, have raised questions about the topology of two-dimensional (2D) flows. We introduce a framework for studying ensembles of 2D time-invariant flow…

Fluid Dynamics · Physics 2024-12-30 M. Kamb , J. Byrum , G. Huber , G. Le Treut , S. Mehta , B. Veytsman , D. Yllanes

Although two-dimensional periodic structures have functioned as the primary platform for exploring topological phenomena, recent advances have substantially expanded this research boundary to include more intricate, aperiodic structures:…

Mesoscale and Nanoscale Physics · Physics 2026-03-12 Sunkyu Yu , Xianji Piao , Namkyoo Park

The irreducible complexity of natural phenomena has led Graph Neural Networks to be employed as a standard model to perform representation learning tasks on graph-structured data. While their capacity to capture local and global patterns is…

Machine Learning · Computer Science 2024-02-13 Lorenzo Giusti