EJP Reading Tools

A Singular Parabolic Anderson Model

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	A Singular Parabolic Anderson Model
2.	Creator	Author's name, affiliation, country	Carl E Mueller; University of Rochester
2.	Creator	Author's name, affiliation, country	Roger Tribe; University of Warwick
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	stochastic partial differential equations
3.	Subject	Subject classification	Primary, 60H15; Secondary, 35R60, 35L05
4.	Description	Abstract	We consider the heat equation with a singular random potential term. The potential is Gaussian with mean 0 and covariance given by a small constant times the inverse square of the distance. Solutions exist as singular measures, under suitable assumptions on the initial conditions and for sufficiently small noise. We investigate various properties of the solutions using such tools as scaling, self-duality and moment formulae. This model lies on the boundary between nonexistence and smooth solutions. It gives a new model, other than the superprocess, which has measure-valued solutions.
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)	NSF, NSA
7.	Date	(YYYY-MM-DD)	2004-02-25
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	http://ejp.ejpecp.org/article/view/189
10.	Identifier	Digital Object Identifier	10.1214/EJP.v9-189
11.	Source	Journal/conference title; vol., no. (year)	Electronic Journal of Probability; Vol 9
12.	Language	English=en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
15.	Rights	Copyright and permissions	The Electronic Journal of Probability applies the Creative Commons Attribution License (CCAL) to all articles we publish in this journal. Under the CCAL, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles published in EJP, so long as the original authors and source are credited. This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available. Summary of the Creative Commons Attribution License You are free to copy, distribute, display, and perform the work to make derivative works to make commercial use of the work under the following condition of Attribution: others must attribute the work if displayed on the web or stored in any electronic archive by making a link back to the website of EJP via its Digital Object Identifier (DOI), or if published in other media by acknowledging prior publication in this Journal with a precise citation including the DOI. For any further reuse or distribution, the same terms apply. Any of these conditions can be waived by permission of the Corresponding Author.