Search results for "Markov proce"

showing 10 items of 147 documents

Introducing Memory in Coarse-Grained Molecular Simulations

2021

[Image: see text] Preserving the correct dynamics at the coarse-grained (CG) level is a pressing problem in the development of systematic CG models in soft matter simulation. Starting from the seminal idea of simple time-scale mapping, there have been many efforts over the years toward establishing a meticulous connection between the CG and fine-grained (FG) dynamics based on fundamental statistical mechanics approaches. One of the most successful attempts in this context has been the development of CG models based on the Mori–Zwanzig (MZ) theory, where the resulting equation of motion has the form of a generalized Langevin equation (GLE) and closely preserves the underlying FG dynamics. In…

010304 chemical physicsComputer scienceMarkov processEquations of motionContext (language use)Statistical mechanics010402 general chemistry01 natural sciencesField (computer science)0104 chemical sciencesSurfaces Coatings and Filmssymbols.namesakeSimple (abstract algebra)0103 physical sciencesMaterials ChemistrysymbolsStatistical physicsLimit (mathematics)Physical and Theoretical ChemistryFocus (optics)
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Nonlinear response theory for Markov processes II: Fifth-order response functions

2017

The nonlinear response of stochastic models obeying a master equation is calculated up to fifth-order in the external field thus extending the third-order results obtained earlier (G. Diezemann, Phys. Rev. E{\bf 85}, 051502 (2012)). For sinusoidal fields the $5\om$-component of the susceptibility is computed for the model of dipole reorientations in an asymmetric double well potential and for a trap model with a Gaussian density of states. For most realizations of the models a hump is found in the higher-order susceptibilities. In particular, for the asymmetric double well potential model there are two characteristic temperature regimes showing the occurence of such a hump as compared to a …

010304 chemical physicsField (physics)Stochastic modellingMarkov processFOS: Physical sciencesDouble-well potentialCondensed Matter - Soft Condensed Matter01 natural sciencesNonlinear systemDipolesymbols.namesakeQuantum mechanics0103 physical sciencesMaster equationsymbolsRelaxation (physics)Soft Condensed Matter (cond-mat.soft)Statistical physics010306 general physicsMathematics
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Convergence of direct recursive algorithm for identification of Preisach hysteresis model with stochastic input

2015

We consider a recursive iterative algorithm for identification of parameters of the Preisach model, one of the most commonly used models of hysteretic input-output relationships. The classical identification algorithm due to Mayergoyz defines explicitly a series of test inputs that allow one to find parameters of the Preisach model with any desired precision provided that (a) such input time series can be implemented and applied; and, (b) the corresponding output data can be accurately measured and recorded. Recursive iterative identification schemes suitable for a number of engineering applications have been recently proposed as an alternative to the classical algorithm. These recursive sc…

0209 industrial biotechnology93E12 47J40 74N30Markov chainIterative methodApplied MathematicsMarkov processFOS: Physical sciences02 engineering and technologyFunction (mathematics)Nonlinear Sciences - Chaotic Dynamics021001 nanoscience & nanotechnologyParameter identification problemsymbols.namesake020901 industrial engineering & automationRate of convergenceControl theoryPiecewisesymbolsApplied mathematicsOnline algorithmChaotic Dynamics (nlin.CD)0210 nano-technologyMathematics
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Density Flow in Dynamical Networks via Mean-Field Games

2016

Current distributed routing control algorithms for dynamic networks model networks using the time evolution of density at network edges, while the routing control algorithm ensures edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We rearrange the density model to recast the problem within the framework of mean-field games. In doing that, we illustrate an extended state-space solution approach and we study the stochastic case where the density evolution is driven by a Brownian motion. Further, we investigate the case where the density evolution is perturbed by a bounded adversarial disturbance. For both the stochastic a…

0209 industrial biotechnologyDensity flowMathematical optimizationMarkov process02 engineering and technology01 natural sciencessymbols.namesake020901 industrial engineering & automationSettore ING-INF/04 - AutomaticaRobustness (computer science)Applied mathematics0101 mathematicsElectrical and Electronic EngineeringBrownian motionMathematics010102 general mathematicsControl engineering decentralized control intelligent transportation systems traffic controlTime evolutionComputer Science ApplicationsMean field theoryControl and Systems EngineeringBounded functionRepeated gamesymbolsSettore MAT/09 - Ricerca OperativaIEEE Transactions on Automatic Control
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Adaptation, coordination, and local interactions via distributed approachability

2017

This paper investigates the relation between cooperation, competition, and local interactions in large distributed multi-agent\ud systems. The main contribution is the game-theoretic problem formulation and solution approach based on the new framework\ud of distributed approachability, and the study of the convergence properties of the resulting game model. Approachability\ud theory is the theory of two-player repeated games with vector payoffs, and distributed approachability is here presented for\ud the first time as an extension to the case where we have a team of agents cooperating against a team of adversaries under local\ud information and interaction structure. The game model turns i…

0209 industrial biotechnologyMarkov process02 engineering and technologyApproachability01 natural sciencesTerm (time)Repeated gamesApproachabilityDifferential gamesRobust controlNetwork flow010104 statistics & probabilityNonlinear systemsymbols.namesake020901 industrial engineering & automationSettore ING-INF/04 - AutomaticaDifferential inclusionControl and Systems EngineeringConvergence (routing)symbolsRepeated gameTopological graph theorySettore MAT/09 - Ricerca Operativa0101 mathematicsElectrical and Electronic EngineeringMathematical economicsMathematicsAutomatica
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Two-qubit entanglement dynamics for two different non-Markovian environments

2009

We study the time behavior of entanglement between two noninteracting qubits each immersed in its own environment for two different non-Markovian conditions: a high-$Q$ cavity slightly off-resonant with the qubit transition frequency and a nonperfect photonic band-gap, respectively. We find that revivals and retardation of entanglement loss may occur by adjusting the cavity-qubit detuning, in the first case, while partial entanglement trapping occurs in non-ideal photonic-band gap.

03.67.Mn Entanglement measures witnesses and other characterizationCondensed Matter::Quantum GasesPhysicsQuantum Physicsbusiness.industryDynamics (mechanics)FOS: Physical sciencesMarkov process03.65.Ud Entanglement and quantum nonlocality (e.g. EPR paradox Bell's inequalities GHZ states etc.)Quantum PhysicsTrappingQuantum entanglementCondensed Matter PhysicsAtomic and Molecular Physics and OpticsSettore FIS/03 - Fisica Della Materiasymbols.namesake03.67.Mn Entanglement measures witnesses and other characterizations; 03.65.Ud Entanglement and quantum nonlocality (e.g. EPR paradox Bell's inequalities GHZ states etc.); 03.67.Lx Quantum computation architectures and implementationsQuantum mechanicsQubitsymbolsPhotonicsQuantum Physics (quant-ph)business03.67.Lx Quantum computation architectures and implementationsMathematical Physics
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Dynamic coarse-graining fills the gap between atomistic simulations and experimental investigations of mechanical unfolding

2017

We present a dynamic coarse-graining technique that allows to simulate the mechanical unfolding of biomolecules or molecular complexes on experimentally relevant time scales. It is based on Markov state models (MSM), which we construct from molecular dynamics simulations using the pulling coordinate as an order parameter. We obtain a sequence of MSMs as a function of the discretized pulling coordinate, and the pulling process is modeled by switching among the MSMs according to the protocol applied to unfold the complex. This way we cover seven orders of magnitude in pulling speed. In the region of rapid pulling we additionally perform steered molecular dynamics simulations and find excellen…

0301 basic medicineDiscretizationGeneral Physics and AstronomyMarkov processFOS: Physical sciencesCondensed Matter - Soft Condensed Matter01 natural sciences03 medical and health sciencesMolecular dynamicssymbols.namesake0103 physical sciencesPhysics - Biological PhysicsStatistical physicsPhysical and Theoretical Chemistry010306 general physicsPhysicsQuantitative Biology::BiomoleculesMarkov chainMolecular biophysicsBiomolecules (q-bio.BM)Function (mathematics)030104 developmental biologyQuantitative Biology - BiomoleculesOrders of magnitude (time)Biological Physics (physics.bio-ph)FOS: Biological sciencessymbolsSoft Condensed Matter (cond-mat.soft)Granularity
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On the stability of some controlled Markov chains and its applications to stochastic approximation with Markovian dynamic

2015

We develop a practical approach to establish the stability, that is, the recurrence in a given set, of a large class of controlled Markov chains. These processes arise in various areas of applied science and encompass important numerical methods. We show in particular how individual Lyapunov functions and associated drift conditions for the parametrized family of Markov transition probabilities and the parameter update can be combined to form Lyapunov functions for the joint process, leading to the proof of the desired stability property. Of particular interest is the fact that the approach applies even in situations where the two components of the process present a time-scale separation, w…

65C05FOS: Computer and information sciencesStatistics and ProbabilityLyapunov functionStability (learning theory)Markov processContext (language use)Mathematics - Statistics Theorycontrolled Markov chainsStatistics Theory (math.ST)Stochastic approximation01 natural sciencesMethodology (stat.ME)010104 statistics & probabilitysymbols.namesake60J05stochastic approximationFOS: MathematicsComputational statisticsApplied mathematics60J220101 mathematicsStatistics - MethodologyMathematicsSequenceMarkov chain010102 general mathematicsStability Markov chainssymbolsStatistics Probability and Uncertaintyadaptive Markov chain Monte Carlo
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Gradient flows in random walk spaces

2021

El món digital ha comportat l'aparició de molts tipus de dades, de mida i complexitat creixents. De fet, els dispositius moderns ens permeten obtenir fàcilment imatges de major resolució, així com recopilar dades sobre cerques a la xarxa, anàlisis sanitàries, xarxes socials, sistemes d'informació geogràfica, etc. En conseqüència, l'estudi i el tractament d'aquests grans conjunts de dades té un gran interès i valor. En aquest sentit, els grafs ponderats proporcionen un espai de treball natural i flexible on representar les dades. En aquest context, un vèrtex representa una dada concreta i a cada aresta se li assigna un pes segons alguna mesura de semblança adequadament triada entre els vèrte…

:MATEMÁTICAS [UNESCO]markov processescheeger problemrof modelnonlocal nonlinear partial differential equationsgradient flowsrandom walk spacescalculus of variationsevolution problemsUNESCO::MATEMÁTICAS
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A Criterium for the Strict Positivity of the Density of the Law of a Poisson Process

2011

We translate in semigroup theory our result (Leandre, 1990) giving a necessary condition so that the law of a Markov process with jumps could have a strictly positive density. This result express, that we have to jump in a finite number of jumps in a "submersive" way from the starting point to the end point if the density of the jump process is strictly positive in . We use the Malliavin Calculus of Bismut type of (Leandre, (2008;2010)) translated in semi-group theory as a tool, and the interpretation in semi-group theory of some classical results of the stochastic analysis for Poisson process as, for instance, the formula giving the law of a compound Poisson process.

Algebra and Number TheorySemigroupStochastic processlcsh:MathematicsApplied MathematicsMarkov processlcsh:QA1-939Malliavin calculussymbols.namesakeLawCompound Poisson processJumpsymbolsFinite setJump processAnalysisMathematicsAdvances in Difference Equations
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