{"title":"Gradient-type estimates for the dynamic φ24-model","authors":"Florian Kunick , Pavlos Tsatsoulis","doi":"10.1016/j.spa.2024.104548","DOIUrl":null,"url":null,"abstract":"<div><div>We prove gradient bounds for the Markov semigroup of the dynamic <span><math><msubsup><mrow><mi>φ</mi></mrow><mrow><mn>2</mn></mrow><mrow><mn>4</mn></mrow></msubsup></math></span>-model on a torus of fixed size <span><math><mrow><mi>L</mi><mo>></mo><mn>0</mn></mrow></math></span>. For sufficiently large mass <span><math><mrow><mi>m</mi><mo>></mo><mn>0</mn></mrow></math></span> these estimates imply exponential contraction of the Markov semigroup. Our method is based on pathwise estimates of the linearized equation. To compensate the lack of exponential integrability of the stochastic drivers we use a stopping time argument in the spirit of Cass–Litterer–Lyons (Cass et al., 2013) and the strong Markov property. Following the classical approach of Bakry-Émery, as a corollary we prove a Poincaré/spectral gap inequality for the <span><math><msubsup><mrow><mi>φ</mi></mrow><mrow><mn>2</mn></mrow><mrow><mn>4</mn></mrow></msubsup></math></span>-measure of sufficiently large mass <span><math><mrow><mi>m</mi><mo>></mo><mn>0</mn></mrow></math></span> with almost optimal <em>carré du champ</em>.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"181 ","pages":"Article 104548"},"PeriodicalIF":1.1000,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stochastic Processes and their Applications","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304414924002564","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
We prove gradient bounds for the Markov semigroup of the dynamic -model on a torus of fixed size . For sufficiently large mass these estimates imply exponential contraction of the Markov semigroup. Our method is based on pathwise estimates of the linearized equation. To compensate the lack of exponential integrability of the stochastic drivers we use a stopping time argument in the spirit of Cass–Litterer–Lyons (Cass et al., 2013) and the strong Markov property. Following the classical approach of Bakry-Émery, as a corollary we prove a Poincaré/spectral gap inequality for the -measure of sufficiently large mass with almost optimal carré du champ.
期刊介绍:
Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests.
Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.