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学术报告83:黄兴 — Exponential Ergodicity in W1 for SDEs with Distribution Dependent Noise and Partially Dissipative Drifts

时间:2024-10-17 作者: 点击数:

报告时间:2024年10月25日(星期五)16:00-17:00

报告地点:科教楼B座1710

告人:黄兴 副教授

工作单位:天津大学

举办单位:数学学院

报告简介:

In this paper, the exponential ergodicity in $\W_1$ for McKean--Vlasov SDEs driven by distribution dependent L\'{e}vy noise is established. The results are applied in non-degenerate multiplicative Brownian motion case, additive kinetic SDEs with Brownian noise and additive L\'{e}vy noise. In all these models, the coefficients before the noise are allowed to be distribution dependent and the drifts are only assumed to be partially dissipative drifts. These results considerably improve the existing ones in which the noise is distribution free.

报告人简介:

黄兴,2017年博士毕业北京师范大学概率论与数理统计专业,现为天津大学应用数学中心副教授。研究方向:随机分析。主持国家自然科学基金青年、面上项目,参与科技部重点研发项目。主要关注分布依赖的随机微分方程的解的适定性,定量混沌传播和分布性质如正则性估计和维数无关的Harnack不等式等。已在Stochastic Process. Appl.,Electron. J. Probab.,J. Differential Equations和Sci. China Math.等国内外学术期刊上发表论文近40篇。

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