878 research outputs found
Smoluchowski-Kramers approximation in the case of variable friction
We consider the small mass asymptotics (Smoluchowski-Kramers approximation)
for the Langevin equation with a variable friction coefficient. The limit of
the solution in the classical sense does not exist in this case. We study a
modification of the Smoluchowski-Kramers approximation. Some applications of
the Smoluchowski-Kramers approximation to problems with fast oscillating or
discontinuous coefficients are considered.Comment: already publishe
On second order elliptic equations with a small parameter
The Neumann problem with a small parameter
is
considered in this paper. The operators and are self-adjoint second
order operators. We assume that has a non-negative characteristic form
and is strictly elliptic. The reflection is with respect to inward
co-normal unit vector . The behavior of
is effectively described via
the solution of an ordinary differential equation on a tree. We calculate the
differential operators inside the edges of this tree and the gluing condition
at the root. Our approach is based on an analysis of the corresponding
diffusion processes.Comment: 28 pages, 1 figure, revised versio
Large Deviations Principle for a Large Class of One-Dimensional Markov Processes
We study the large deviations principle for one dimensional, continuous,
homogeneous, strong Markov processes that do not necessarily behave locally as
a Wiener process. Any strong Markov process in that is
continuous with probability one, under some minimal regularity conditions, is
governed by a generalized elliptic operator , where and are
two strictly increasing functions, is right continuous and is
continuous. In this paper, we study large deviations principle for Markov
processes whose infinitesimal generator is where
. This result generalizes the classical large deviations
results for a large class of one dimensional "classical" stochastic processes.
Moreover, we consider reaction-diffusion equations governed by a generalized
operator . We apply our results to the problem of wave front
propagation for these type of reaction-diffusion equations.Comment: 23 page
Localized growth modes, dynamic textures, and upper critical dimension for the Kardar-Parisi-Zhang equation in the weak noise limit
A nonperturbative weak noise scheme is applied to the Kardar-Parisi-Zhang
equation for a growing interface in all dimensions. It is shown that the growth
morphology can be interpreted in terms of a dynamically evolving texture of
localized growth modes with superimposed diffusive modes. Applying Derrick's
theorem it is conjectured that the upper critical dimension is four.Comment: 10 pages in revtex and 2 figures in eps, a few typos correcte
Pathways of activated escape in periodically modulated systems
We investigate dynamics of activated escape in periodically modulated
systems. The trajectories followed in escape form diffusion broadened tubes,
which are periodically repeated in time. We show that these tubes can be
directly observed and find their shape. Quantitatively, the tubes are
characterized by the distribution of trajectories that, after escape, pass
through a given point in phase space for a given modulation phase. This
distribution may display several peaks separated by the modulation period.
Analytical results agree with the results of simulations of a model Brownian
particle in a modulated potential
On stochasticity in nearly-elastic systems
Nearly-elastic model systems with one or two degrees of freedom are
considered: the system is undergoing a small loss of energy in each collision
with the "wall". We show that instabilities in this purely deterministic system
lead to stochasticity of its long-time behavior. Various ways to give a
rigorous meaning to the last statement are considered. All of them, if
applicable, lead to the same stochasticity which is described explicitly. So
that the stochasticity of the long-time behavior is an intrinsic property of
the deterministic systems.Comment: 35 pages, 12 figures, already online at Stochastics and Dynamic
Numerical computation of rare events via large deviation theory
An overview of rare events algorithms based on large deviation theory (LDT)
is presented. It covers a range of numerical schemes to compute the large
deviation minimizer in various setups, and discusses best practices, common
pitfalls, and implementation trade-offs. Generalizations, extensions, and
improvements of the minimum action methods are proposed. These algorithms are
tested on example problems which illustrate several common difficulties which
arise e.g. when the forcing is degenerate or multiplicative, or the systems are
infinite-dimensional. Generalizations to processes driven by non-Gaussian
noises or random initial data and parameters are also discussed, along with the
connection between the LDT-based approach reviewed here and other methods, such
as stochastic field theory and optimal control. Finally, the integration of
this approach in importance sampling methods using e.g. genealogical algorithms
is explored
A Note on the Smoluchowski-Kramers Approximation for the Langevin Equation with Reflection
According to the Smoluchowski-Kramers approximation, the solution of the
equation
converges to the solution of the equation
as {\mu}->0. We consider here
a similar result for the Langevin process with elastic reflection on the
boundary.Comment: 14 pages, 2 figure
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