6,607 research outputs found
Lower bounds for the density of locally elliptic It\^{o} processes
We give lower bounds for the density of the law of , the
solution of under the following local
ellipticity hypothesis: there exists a deterministic differentiable curve , such that and for all
The lower bound is expressed in terms of a distance
related to the skeleton of the diffusion process. This distance appears when we
optimize over all the curves which verify the above ellipticity assumption. The
arguments which lead to the above result work in a general context which
includes a large class of Wiener functionals, for example, It\^{o} processes.
Our starting point is work of Kohatsu-Higa which presents a general framework
including stochastic PDE's.Comment: Published at http://dx.doi.org/10.1214/009117906000000458 in the
Annals of Probability (http://www.imstat.org/aop/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Filamentary structure in the Orion molecular cloud
A large scale 13CO map (containing 33,000 spectra) of the giant molecular cloud located in the southern part of Orion is presented which contains the Orion Nebula, NGC1977, and the LI641 dark cloud complex. The overall structure of the cloud is filamentary, with individual features having a length up to 40 times their width. This morphology may result from the effects of star formation in the region or embedded magnetic fields in the cloud. We suggest a simple picture for the evolution of the Orion-A cloud and the formation of the major filament. A rotating proto-cloud (counter rotating with respect to the galaxy) contians a b-field aligned with the galaxtic plane. The northern protion of this cloud collapsed first, perhaps triggered by the pressure of the Ori I OB association. The magnetic field combined with the anisotropic pressure produced by the OB-association breaks the symmetry of the pancake instability, a filament rather than a disc is produced. The growth of instabilities in the filament formed sub-condensations which are recent sites of star formation
A generic construction for high order approximation schemes of semigroups using random grids
Our aim is to construct high order approximation schemes for general
semigroups of linear operators . In order to do it, we fix a
time horizon and the discretization steps and we suppose that we have at hand some short time approximation
operators such that for some
. Then, we consider random time grids such that for all ,
for some , and
we associate the approximation discrete semigroup Our main result is the following: for any
approximation order , we can construct random grids
and coefficients , with such that % with the expectation concerning the random grids
Besides, and the complexity of the
algorithm is of order , for any order of approximation . The standard
example concerns diffusion processes, using the Euler approximation for~.
In this particular case and under suitable conditions, we are able to gather
the terms in order to produce an estimator of with finite variance.
However, an important feature of our approach is its universality in the sense
that it works for every general semigroup and approximations. Besides,
approximation schemes sharing the same lead to the same random grids
and coefficients . Numerical illustrations are given for
ordinary differential equations, piecewise deterministic Markov processes and
diffusions
Riesz transform and integration by parts formulas for random variables
We use integration by parts formulas to give estimates for the norm of
the Riesz transform. This is motivated by the representation formula for
conditional expectations of functionals on the Wiener space already given in
Malliavin and Thalmaier. As a consequence, we obtain regularity and estimates
for the density of non degenerated functionals on the Wiener space. We also
give a semi-distance which characterizes the convergence to the boundary of the
set of the strict positivity points for the density
On the distance between probability density functions
We give estimates of the distance between the densities of the laws of two
functionals and on the Wiener space in terms of the Malliavin-Sobolev
norm of We actually consider a more general framework which allows one
to treat with similar (Malliavin type) methods functionals of a Poisson point
measure (solutions of jump type stochastic equations). We use the above
estimates in order to obtain a criterion which ensures that convergence in
distribution implies convergence in total variation distance; in particular, if
the functionals at hand are absolutely continuous, this implies convergence in
of the densities
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