scholarly journals Diffusion-approximation for a kinetic spray-like system with random forcing

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Arnaud Debussche ◽  
Angelo Rosello ◽  
Julien Vovelle
Keyword(s):  
Diffusion Approximation ◽  
Random Forcing ◽  
Kinetic Spray

scholarly journals Diffusion Model of Preemptive-Resume Priority Systems and Its Application to Performance Evaluation of SDN Switches

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5042
Author(s):  
Tomasz Nycz ◽  
Tadeusz Czachórski ◽  
Monika Nycz
Keyword(s):  
Diffusion Approximation ◽  
Numerical Models ◽  
Software Defined Networks ◽  
Detailed Model ◽  
Preemptive Resume ◽  
Central Controller ◽  
Priority Systems ◽  
Primary Element ◽  
Preemptive Resume Priority ◽  
General Distributions

The increasing use of Software-Defined Networks brings the need for their performance analysis and detailed analytical and numerical models of them. The primary element of such research is a model of a SDN switch. This model should take into account non-Poisson traffic and general distributions of service times. Because of frequent changes in SDN flows, it should also analyze transient states of the queues. The method of diffusion approximation can meet these requirements. We present here a diffusion approximation of priority queues and apply it to build a more detailed model of SDN switch where packets returned by the central controller have higher priority than other packets.

On modelling physical systems with stochastic models: diffusion versus Lévy processes

2008 ◽  
Vol 366 (1875) ◽  
pp. 2455-2474 ◽  
Author(s):  
Cécile Penland ◽  
Brian D Ewald
Keyword(s):  
Differential Equations ◽  
Stochastic Models ◽  
Lévy Processes ◽  
Numerical Models ◽  
Gaussian White Noise ◽  
Levy Processes ◽  
Physical Systems ◽  
Random Forcing ◽  
Weather And Climate ◽  
Made In

Stochastic descriptions of multiscale interactions are more and more frequently found in numerical models of weather and climate. These descriptions are often made in terms of differential equations with random forcing components. In this article, we review the basic properties of stochastic differential equations driven by classical Gaussian white noise and compare with systems described by stable Lévy processes. We also discuss aspects of numerically generating these processes.

scholarly journals A NOTE ON THE ANALYSIS OF A HETEROGENEOUS ROD-LIKE CHAIN IN DNA MODELING

2008 ◽  
Vol 22 (14) ◽  
pp. 2213-2224
Author(s):  
YAN DING ◽  
TIEJUN LI
Keyword(s):  
Path Integral ◽  
Lie Group ◽  
Persistence Length ◽  
Elastic Behavior ◽  
Suitable Model ◽  
Weak Disorder ◽  
Integral Analysis ◽  
Basic Model ◽  
Random Forcing ◽  
Sequence Dependent

Two different results concerning the elastic behavior of the heterogeneous worm-like chain (WLC) [D. Bensimon et al., Europhys. Lett.42, 97 (1998)] and rod-like chain (RLC) [P. Nelson, Phys. Rev. Lett.80, 5810 (1998)] are compared. We argue that the RLC is a more suitable model for double-stranded (ds-) DNA. As the hetero-RLC is the basic model for studying sequence-dependent ds-DNA, a rigorous path integral analysis for the effective bending persistence length is performed in the weak disorder limit. The novelty of the paper is in analyzing a path integral on the Lie group SO(3) with random forcing, which supplies a rigorous basis for the analysis of RLC type models.

scholarly journals Reacceleration of Relativistic Electrons by Turbulent Alfvén Waves in Radio Jets

2000 ◽  
Vol 195 ◽  
pp. 439-441
Author(s):  
D.-Y. Wang ◽  
Y. Ma
Keyword(s):  
Electron Energy ◽  
Power Law ◽  
Diffusion Approximation ◽  
Alfven Waves ◽  
Alfvén Waves ◽  
Relativistic Electrons ◽  
Radio Jets

Relativistic electrons may be effectively accelerated by turbulent Alfvén waves in radio jets. The acceleration spectrum is a power law with the electron energy as high as γ ~ 106, but the spectrum index is ~ 1.2 in the condition of diffusion approximation, which is less than the observation value.

Randomly perturbed vibrations

1995 ◽  
Vol 32 (02) ◽  
pp. 417-428 ◽  
Author(s):  
M. Elshamy
Keyword(s):  
Dirichlet Boundary ◽  
Space Variable ◽  
Initial Conditions ◽  
Linear Wave ◽  
Stochastic Perturbations ◽  
Uniform Topology ◽  
Linear Wave Equation ◽  
Random Forcing ◽  
Continuity Properties ◽  
Positive Time

Let u ε(t, x) be the position at time t of a point x on a string, where the time variable t varies in an interval I: = [0, T], T is a fixed positive time, and the space variable x varies in an interval J. The string is performing forced vibrations and also under the influence of small stochastic perturbations of intensity ε. We consider two kinds of random perturbations, one in the form of initial white noise, and the other is a nonlinear random forcing which involves the formal derivative of a Brownian sheet. When J has finite endpoints, a Dirichlet boundary condition is imposed for the solutions of the resulting non-linear wave equation. Assuming that the initial conditions are of sufficient regularity, we analyze the deviations u ε(t, x) from u 0(t, x), the unperturbed position function, as the intensity of perturbation ε ↓ 0 in the uniform topology. We also discuss some continuity properties of the realization of the solutions u ε(t, x).

Noise in Integrate-and-Fire Neurons: From Stochastic Input to Escape Rates

2000 ◽  
Vol 12 (2) ◽  
pp. 367-384 ◽  
Author(s):  
Hans E. Plesser ◽  
Wulfram Gerstner
Keyword(s):  
Membrane Potential ◽  
Diffusion Approximation ◽  
Hazard Function ◽  
Time Dependent ◽  
Integrate And Fire ◽  
Probability Current ◽  
Periodic Input ◽  
Stochastic Input ◽  
Free Membrane ◽  
Noise Models

We analyze the effect of noise in integrate-and-fire neurons driven by time-dependent input and compare the diffusion approximation for the membrane potential to escape noise. It is shown that for time-dependent subthreshold input, diffusive noise can be replaced by escape noise with a hazard function that has a gaussian dependence on the distance between the (noise-free) membrane voltage and threshold. The approximation is improved if we add to the hazard function a probability current proportional to the derivative of the voltage. Stochastic resonance in response to periodic input occurs in both noise models and exhibits similar characteristics.

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