Search results for "topological properties"

showing 4 items of 4 documents

Towards realistic artificial benchmark for community detection algorithms evaluation

2013

Many algorithms have been proposed for revealing the community structure in complex networks. Tests under a wide range of realistic conditions must be performed in order to select the most appropriate for a particular application. Artificially generated networks are often used for this purpose. The most realistic generative method to date has been proposed by Lancichinetti, Fortunato and Radicchi (LFR). However, it does not produce networks with some typical features of real-world networks. To overcome this drawback, we investigate two alternative modifications of this algorithm. Experimental results show that in both cases, centralisation and degree correlation values of generated networks…

FOS: Computer and information sciencesPhysics - Physics and Societypreferential attachmentComputer Networks and CommunicationsComputer science[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]FOS: Physical sciencesvirtual communitiesPhysics and Society (physics.soc-ph)01 natural sciences010305 fluids & plasmasEducation0103 physical sciencescommunity detectionbenchmarking010306 general physicsSocial and Information Networks (cs.SI)CommunicationComputer Science - Social and Information Networkscomplex networksweb based communitiesonline communitiesconfiguration modellingIdentification (information)LFR benchmarkBenchmark (computing)[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]community structureAlgorithmtopological propertiesSoftware
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Aberrant brain functional networks in type 2 diabetes mellitus: A graph theoretical and support-vector machine approach

2022

ObjectiveType 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities.MethodsA total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were ana…

kognitiiviset taidottype 2 diabetes mellitusmagneettikuvaushermoverkot (biologia)resting-state MRIbiomarkkeritBehavioral NeurosciencePsychiatry and Mental healthkoneoppiminenaivokuoriNeuropsychology and Physiological PsychologyNeurologyauditory cortexsupport vector machinetopological propertiesaikuistyypin diabetescognitive functionBiological PsychiatryFrontiers in Human Neuroscience
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Comparing equilibration schemes of high-molecular-weight polymer melts with topological indicators.

2021

Abstract Recent theoretical studies have demonstrated that the behaviour of molecular knots is a sensitive indicator of polymer structure. Here, we use knots to verify the ability of two state-of-the-art algorithms—configuration assembly and hierarchical backmapping—to equilibrate high-molecular-weight (MW) polymer melts. Specifically, we consider melts with MWs equivalent to several tens of entanglement lengths and various chain flexibilities, generated with both strategies. We compare their unknotting probability, unknotting length, knot spectra, and knot length distributions. The excellent agreement between the two independent methods with respect to knotting properties provides an addit…

PaperMaterials sciencemolecular knots; multiscale simulations; polymer melts; polymer modelling; topological propertiesStructure (category theory)02 engineering and technologyQuantum entanglementTopologyMultiscale Simulation Methods for Soft Matter Systemspolymer melts01 natural sciencesSpectral lineMolecular dynamicsKnot (unit)multiscale simulationsChain (algebraic topology)Consistency (statistics)0103 physical sciencesGeneral Materials Sciencepolymer modelling010306 general physicsmolecular knotschemistry.chemical_classificationPolymer021001 nanoscience & nanotechnologyCondensed Matter PhysicsMathematics::Geometric Topologychemistry0210 nano-technologytopological properties
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Finite-temperature geometric properties of the Kitaev honeycomb model

2018

We study finite temperature topological phase transitions of the Kitaev's spin honeycomb model in the vortex-free sector with the use of the recently introduced mean Uhlmann curvature. We employ an appropriate Fermionisation procedure to study the system as a two-band p-wave superconductor described by a BdG Hamiltonian. This allows to study relevant quantities such as Berry and mean Uhlmann curvatures in a simple setting. More specifically, we consider the spin honeycomb in the presence of an external magnetic field breaking time reversal symmetry. The introduction of such an external perturbation opens a gap in the phase of the system characterised by non-Abelian statistics, and makes the…

Mathematics::Analysis of PDEsFOS: Physical sciencesPerturbation (astronomy)02 engineering and technologyCurvature01 natural sciencesSettore FIS/03 - Fisica Della Materiasymbols.namesakeMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciencesFinite-temperature topological properties Kitaev honeycomb model Berry curvature mean Uhlmann curvature010306 general physicsPhase diagramMathematical physicsPhysicsSuperconductivityQuantum PhysicsCondensed Matter - Mesoscale and Nanoscale Physics021001 nanoscience & nanotechnologyMagnetic fieldsymbolsThermal stateBerry connection and curvatureQuantum Physics (quant-ph)0210 nano-technologyHamiltonian (quantum mechanics)Physical Review B
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