報(bào)告人：張讓讓 副教授

報(bào)告題目：Wong-Zakai approximation and support theorem for quasilinear parabolic stochastic partial differential equations

報(bào)告時(shí)間：2025年11月23日（周日）上午9：00

報(bào)告地點(diǎn)：云龍校區(qū)6號(hào)樓304會(huì)議室

主辦單位：數(shù)學(xué)與統(tǒng)計(jì)學(xué)院、數(shù)學(xué)研究院、科學(xué)技術(shù)研究院

報(bào)告人簡(jiǎn)介：

張讓讓，北京理工大學(xué)數(shù)學(xué)與統(tǒng)計(jì)學(xué)院副教授。博士畢業(yè)于中國(guó)科學(xué)院數(shù)學(xué)與系統(tǒng)科學(xué)研究院，研究領(lǐng)域?yàn)殡S機(jī)偏微分方程。在《Communications in Mathematical Physics》、《The Annals of Applied Probability》、《Journal of Differential Equations》、《Electronic Journal of Probability》等期刊發(fā)表論文二十余篇，主持國(guó)家自然科學(xué)基金面上項(xiàng)目、青年基金項(xiàng)目和北京市自然科學(xué)基金面上項(xiàng)目等。

報(bào)告摘要：

In this talk, we are concerned with Wong-Zakai approximation and support theorem for quasilinear parabolic stochastic partial differential equations. Since this class of equations is not locally monotone, we implement a regularization strategy using a sequence of heat kernel to modify the matrix-valued diffusion term, thereby recovering the monotonicity. As a result, the problem is reduced to prove two results of further layer approximations. To this end, we further employ a kinetic formulation of the approximating solutions in the L^1 setting and fully use the doubling variables techniques. This is based on a joint work with Tusheng Zhang.