Paper detail

Stochastic Quantization of Laser Propagation Models

This paper identifies certain interesting mathematical problems of stochastic quantization type in the modeling of Laser propagation through turbulent media. In some of the typical physical contexts the problem reduces to stochastic Schrodinger equation with space-time white noise of Gaussian, Poisson and Levy type. We identify their mathematical resolution via stochastic quantization. Nonlinear phenomena such as Kerr effect can be modeled by stochastic nonlinear Schrodinger equation in the focusing case with space-time white noise. A treatment of stochastic transport equation, the Korteweg-de Vries Equation as well as a number of other nonlinear wave equations with space-time white noise is also given. Main technique is the S-transform (we will actually use closely related Hermite transform) which converts the stochastic partial differential equation with space time white noise to a deterministic partial differential equation defined on the Hida-Kondratiev white noise distribution space. We then utlize the inverse S-transform/Hermite transform known as the characterization theorem combined with the infinite dimensional implicit function theorem for analytic maps to establish local existence and uniqueness theorems for pathwise solutions of these class of problems. The particular focus of this paper on singular white noise distributions is motivated by practical situations where the refractive index fluctuations in propagation medium in space and time are intense due to turbulence, ionospheric plasma turbulence, marine-layer fluctuations, etc. Since a large class of partial differential equations that arise in nonlinear wave propagation have polynomial type nonlinearities, white noise distribution theory is an effective tool in studying these problems subject to different types of white noises.

preprint2022arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.