Indexing metadata

Large systems of path-repellent Brownian motions in a trap at positive temperature


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document Large systems of path-repellent Brownian motions in a trap at positive temperature
 
2. Creator Author's name, affiliation, country Stefan Adams; Max Planck Institute for Mathematics in the Sciences
 
2. Creator Author's name, affiliation, country Jean-Bernard Bru; Johannes-Gutenberg-Universitat Mainz
 
2. Creator Author's name, affiliation, country Wolfgang Koenig; Universitat Leipzig
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) Interacting Brownian motions; Brownian intersection local times; large deviations; occupation measure; Gross-Pitaevskii formula
 
3. Subject Subject classification 60F10; 60J65; 82B10; 82B26
 
4. Description Abstract We study a model of $ N $ mutually repellent Brownian motions under confinement to stay in some bounded region of space. Our model is defined in terms of a transformed path measure under a trap Hamiltonian, which prevents the motions from escaping to infinity, and a pair-interaction Hamiltonian, which imposes a repellency of the $N$ paths. In fact, this interaction is an $N$-dependent regularisation of the Brownian intersection local times, an object which is of independent interest in the theory of stochastic processes. The time horizon (interpreted as the inverse temperature) is kept fixed. We analyse the model for diverging number of Brownian motions in terms of a large deviation principle. The resulting variational formula is the positive-temperature analogue of the well-known Gross-Pitaevskii formula, which approximates the ground state of a certain dilute large quantum system; the kinetic energy term of that formula is replaced by a probabilistic energy functional. This study is a continuation of the analysis in [ABK06] where we considered the limit of diverging time (i.e., the zero-temperature limit) with fixed number of Brownian motions, followed by the limit for diverging number of motions.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s) This work was partially supported by DFG grant AD 194/1-1
 
7. Date (YYYY-MM-DD) 2006-06-29
 
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/330
 
10. Identifier Digital Object Identifier 10.1214/EJP.v11-330
 
11. Source Journal/conference title; vol., no. (year) Electronic Journal of Probability; Vol 11
 
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.