Search results for " Brown"

showing 10 items of 136 documents

Statistical distributions for hamiltonian systems coupled to energy reservoirs and applications to molecular energy conversion

2008

We study systems with Hamiltonian dynamics type coupled to reservoirs providing free energy which may be converted into acceleration. In the first part we introduce general concepts, like canonical dissipative systems and find exact solutions of associated Fokker–Planck equations that describe time evolutions of systems at hand. Next we analyze dynamics in ratchets with energy support which might be treated by perturbation theory around canonical dissipative systems. Finally we discuss possible applications of these ratchet systems to model the mechanism of biological energy conversion and molecular motors.

Statistical mechanics noise active Brownian motion
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Large systems of path-repellent Brownian motions in a trap at positive temperature

2006

We study a model of $ N $ mutually repellent Brownian motions under confinement to stay in some bounded region of space. Our model is defined in terms of a transformed path measure under a trap Hamiltonian, which prevents the motions from escaping to infinity, and a pair-interaction Hamiltonian, which imposes a repellency of the $N$ paths. In fact, this interaction is an $N$-dependent regularisation of the Brownian intersection local times, an object which is of independent interest in the theory of stochastic processes. The time horizon (interpreted as the inverse temperature) is kept fixed. We analyse the model for diverging number of Brownian motions in terms of a large deviation princip…

Statistics and ProbabilityFOS: Physical scienceslarge deviationssymbols.namesakeQuantum systemFOS: MathematicsGross-Pitaevskii formula60J6560F10; 60J65; 82B10; 82B26Brownian motionMathematical PhysicsEnergy functionalMathematicsInteracting Brownian motionsStochastic process82B10Mathematical analysisProbability (math.PR)Brownian excursionMathematical Physics (math-ph)Brownian intersection local timessymbolsoccupation measure82B26Large deviations theoryStatistics Probability and UncertaintyHamiltonian (quantum mechanics)Rate functionMathematics - Probability60F10
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Rough linear PDE's with discontinuous coefficients - existence of solutions via regularization by fractional Brownian motion

2020

We consider two related linear PDE's perturbed by a fractional Brownian motion. We allow the drift to be discontinuous, in which case the corresponding deterministic equation is ill-posed. However, the noise will be shown to have a regularizing effect on the equations in the sense that we can prove existence of solutions for almost all paths of the fractional Brownian motion.

Statistics and ProbabilityFractional Brownian motion010102 general mathematicsMathematical analysisProbability (math.PR)fractional Brownian motionlocal times01 natural sciencesRegularization (mathematics)VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410010104 statistics & probabilityDeterministic equation60H05FOS: Mathematics60H1560J5560H1060G220101 mathematicsStatistics Probability and Uncertaintystochastic PDEsrough pathsregularization by noiseMathematics - ProbabilityMathematics
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Fractional Brownian motion and Martingale-differences

2004

Abstract We generalize a result of Sottinen (Finance Stochastics 5 (2001) 343) by proving an approximation theorem for the fractional Brownian motion, with H> 1 2 , using martingale-differences.

Statistics and ProbabilityGeometric Brownian motionFractional Brownian motionMathematics::ProbabilityDiffusion processReflected Brownian motionMathematical analysisBrownian excursionStatistics Probability and UncertaintyHeavy traffic approximationMartingale (probability theory)Martingale representation theoremMathematicsStatistics & Probability Letters
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Hitting Time Distributions in Financial Markets

2006

We analyze the hitting time distributions of stock price returns in different time windows, characterized by different levels of noise present in the market. The study has been performed on two sets of data from US markets. The first one is composed by daily price of 1071 stocks trade for the 12-year period 1987-1998, the second one is composed by high frequency data for 100 stocks for the 4-year period 1995-1998. We compare the probability distribution obtained by our empirical analysis with those obtained from different models for stock market evolution. Specifically by focusing on the statistical properties of the hitting times to reach a barrier or a given threshold, we compare the prob…

Statistics and ProbabilityPhysics - Physics and SocietyAutoregressive conditional heteroskedasticityStock market modelFOS: Physical sciencesPhysics and Society (physics.soc-ph)Langevin-type equationHeston modelEconophysics; Stock market model; Langevin-type equation; Heston model; Complex SystemsFOS: Economics and businessEconometricsMathematicsGeometric Brownian motionStatistical Finance (q-fin.ST)Actuarial scienceEconophysicFinancial marketHitting timeQuantitative Finance - Statistical FinanceComplex SystemsProbability and statisticsCondensed Matter PhysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Heston modelPhysics - Data Analysis Statistics and ProbabilityProbability distributionStock marketData Analysis Statistics and Probability (physics.data-an)
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Statistical mechanics characterization of spatio-compositional inhomogeneity

2009

On the basis of a model system of pillars built of unit cubes, a two-component entropic measure for the multiscale analysis of spatio-compositional inhomogeneity is proposed. It quantifies the statistical dissimilarity per cell of the actual configurational macrostate and the theoretical reference one that maximizes entropy. Two kinds of disorder compete: i) the spatial one connected with possible positions of pillars inside a cell (the first component of the measure), ii) the compositional one linked to compositions of each local sum of their integer heights into a number of pillars occupying the cell (the second component). As both the number of pillars and sum of their heights are conser…

Statistics and ProbabilityPhysicsFractional Brownian motionStatistical Mechanics (cond-mat.stat-mech)Entropy (statistical thermodynamics)PillarTime evolutionFOS: Physical sciencesModel systemStatistical mechanicsCondensed Matter PhysicsCombinatoricsUnit cubeStatistical physicsCondensed Matter - Statistical Mechanics
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Noise driven translocation of short polymers in crowded solutions

2008

In this work we study the noise induced effects on the dynamics of short polymers crossing a potential barrier, in the presence of a metastable state. An improved version of the Rouse model for a flexible polymer has been adopted to mimic the molecular dynamics by taking into account both the interactions between adjacent monomers and introducing a Lennard-Jones potential between all beads. A bending recoil torque has also been included in our model. The polymer dynamics is simulated in a two-dimensional domain by numerically solving the Langevin equations of motion with a Gaussian uncorrelated noise. We find a nonmonotonic behaviour of the mean first passage time and the most probable tran…

Statistics and ProbabilityPhysicschemistry.chemical_classificationQuantitative Biology::BiomoleculesStatistical Mechanics (cond-mat.stat-mech)Thermal fluctuationsEquations of motionFOS: Physical sciencesdynamics (theory) mechanical properties (DNA RNA membranes bio-polymers) (theory) Brownian MotionStatistical and Nonlinear PhysicsContext (language use)PolymerNoise (electronics)Condensed Matter::Soft Condensed MatterMolecular dynamicschemistryChemical physicsRectangular potential barrierStatistics Probability and UncertaintyFirst-hitting-time modelCondensed Matter - Statistical Mechanics
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Erratum to “Simulation of BSDEs with jumps by Wiener Chaos expansion” [Stochastic Process. Appl. 126 (2016) 2123–2162]

2017

Abstract We correct Proposition 2.9 from “Simulation of BSDEs with jumps by Wiener Chaos expansion” published in Stochastic Processes and their Applications, 126 (2016) 2123–2162. The proposition which provides an expression for the expectation of products of multiple integrals (w.r.t. Brownian motion and compensated Poisson process) requires a stronger integrability assumption on the kernels than previously stated. This does not affect the remaining results of the article.

Statistics and ProbabilityPolynomial chaosStochastic processApplied MathematicsMultiple integral010102 general mathematicsMathematical analysisMotion (geometry)Poisson processExpression (computer science)01 natural sciences010104 statistics & probabilitysymbols.namesakeMathematics::ProbabilityReflected Brownian motionModeling and SimulationsymbolsApplied mathematics0101 mathematicsMathematicsStochastic Processes and their Applications
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A new stochastic representation for the decay from a metastable state

2002

Abstract We show that a stochastic process on a complex plane can simulate decay from a metastable state. The simplest application of the method to a model in which the approach to equilibrium occurs through transitions over a potential barrier is discussed. The results are compared with direct numerical simulations of the stochastic differential equations describing system's evolution. We have found that the new method is much more efficient from computational point of view than the direct simulations.

Statistics and ProbabilityStochastic partial differential equationGeometric Brownian motionStochastic differential equationContinuous-time stochastic processQuantum stochastic calculusStochastic processLocal timeDiscrete-time stochastic processStatistical physicsCondensed Matter PhysicsMathematicsPhysica A: Statistical Mechanics and its Applications
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BROWNIAN DYNAMICS SIMULATIONS WITHOUT GAUSSIAN RANDOM NUMBERS

1991

We point out that in a Brownian dynamics simulation it is justified to use arbitrary distribution functions of random numbers if the moments exhibit the correct limiting behavior prescribed by the Fokker-Planck equation. Our argument is supported by a simple analytical consideration and some numerical examples: We simulate the Wiener process, the Ornstein-Uhlenbeck process and the diffusion in a Φ4 potential, using both Gaussian and uniform random numbers. In these examples, the rate of convergence of the mean first exit time is found to be nearly identical for both types of random numbers.

Stochastic processMathematical analysisGeneral Physics and AstronomyStatistical and Nonlinear PhysicsOrnstein–Uhlenbeck processBrownian excursionBrownian bridgeComputer Science Applicationssymbols.namesakeComputational Theory and MathematicsWiener processReflected Brownian motionStochastic simulationsymbolsStatistical physicsGaussian processMathematical PhysicsMathematicsInternational Journal of Modern Physics C
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