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Large deviation principles for first-order scalar conservation laws with stochastic forcing
Zhao Dong,
Jiang-lun Wu,
Rangrang Zhang,
Tusheng Zhang
The Annals of Applied Probability, Volume: 30, Issue: 1, Pages: 324 - 367
Swansea University Author: Jiang-lun Wu
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DOI (Published version): 10.1214/19-aap1503
Abstract
In this paper, we established the Freidlin-Wentzell type large deviation principles for first- order scalar conservation laws perturbed by small multiplicative noise. Due to the lack of the viscous terms in the stochastic equations, the kinetic solution to the Cauchy problem for these first-order co...
Published in: | The Annals of Applied Probability |
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ISSN: | 1050-5164 2168-8737 |
Published: |
Institute of Mathematical Statistics
Institute of Mathematical Statistics
2020
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URI: | https://cronfa.swan.ac.uk/Record/cronfa48584 |
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2020-07-09T20:48:38.3780994 v2 48584 2019-01-28 Large deviation principles for first-order scalar conservation laws with stochastic forcing dbd67e30d59b0f32592b15b5705af885 Jiang-lun Wu Jiang-lun Wu true false 2019-01-28 In this paper, we established the Freidlin-Wentzell type large deviation principles for first- order scalar conservation laws perturbed by small multiplicative noise. Due to the lack of the viscous terms in the stochastic equations, the kinetic solution to the Cauchy problem for these first-order conser- vation laws is studied. Then, based on the well-posedness of the kinetic solutions, we show that the large deviations holds by utilising the weak convergence approach. Journal Article The Annals of Applied Probability 30 1 324 367 Institute of Mathematical Statistics Institute of Mathematical Statistics 1050-5164 2168-8737 large deviations; first-order conservation laws; weak convergence approach; kinetic solution. 25 2 2020 2020-02-25 10.1214/19-aap1503 COLLEGE NANME COLLEGE CODE Swansea University 2020-07-09T20:48:38.3780994 2019-01-28T15:12:28.7540646 Zhao Dong 1 Jiang-lun Wu 2 Rangrang Zhang 3 Tusheng Zhang 4 48584__14058__cbfd09b1e37542ffb82e79bb33c8e7ac.pdf DWZZ2019-0129.pdf 2019-05-29T18:23:25.4700000 Output 251929 application/pdf Accepted Manuscript true 2019-05-29T00:00:00.0000000 true eng |
title |
Large deviation principles for first-order scalar conservation laws with stochastic forcing |
spellingShingle |
Large deviation principles for first-order scalar conservation laws with stochastic forcing Jiang-lun Wu |
title_short |
Large deviation principles for first-order scalar conservation laws with stochastic forcing |
title_full |
Large deviation principles for first-order scalar conservation laws with stochastic forcing |
title_fullStr |
Large deviation principles for first-order scalar conservation laws with stochastic forcing |
title_full_unstemmed |
Large deviation principles for first-order scalar conservation laws with stochastic forcing |
title_sort |
Large deviation principles for first-order scalar conservation laws with stochastic forcing |
author_id_str_mv |
dbd67e30d59b0f32592b15b5705af885 |
author_id_fullname_str_mv |
dbd67e30d59b0f32592b15b5705af885_***_Jiang-lun Wu |
author |
Jiang-lun Wu |
author2 |
Zhao Dong Jiang-lun Wu Rangrang Zhang Tusheng Zhang |
format |
Journal article |
container_title |
The Annals of Applied Probability |
container_volume |
30 |
container_issue |
1 |
container_start_page |
324 |
publishDate |
2020 |
institution |
Swansea University |
issn |
1050-5164 2168-8737 |
doi_str_mv |
10.1214/19-aap1503 |
publisher |
Institute of Mathematical Statistics |
document_store_str |
1 |
active_str |
0 |
description |
In this paper, we established the Freidlin-Wentzell type large deviation principles for first- order scalar conservation laws perturbed by small multiplicative noise. Due to the lack of the viscous terms in the stochastic equations, the kinetic solution to the Cauchy problem for these first-order conser- vation laws is studied. Then, based on the well-posedness of the kinetic solutions, we show that the large deviations holds by utilising the weak convergence approach. |
published_date |
2020-02-25T19:39:18Z |
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1821345011301613568 |
score |
11.04748 |