Gaussian measure
Prof. Hormozi will change the lecture on Nov. 11 to Nov. 14, same time.
In this course we discuss analysis for the Gaussian measure $\gamma_d$ on $\mathbb{R}^d$ from a semigroup and harmonic–analytic point of view. We begin with the geometry of $\gamma_d$ (global non-doubling and the local-doubling calculus via admissible balls) and the Ornstein–Uhlenbeck operator $L$, introduced through Mehler’s kernel and the associated semigroup. On the spectral side we use Hermite polynomials and the Wiener–It\^o chaos decomposition of $L^2(\gamma_d)$, and we build the basic function spaces $L^p(\gamma_d)$, together with Sobolev and Hardy spaces adapted to $\gamma_d$. Central tools include hypercontractivity and logarithmic Sobolev inequalities, maximal functions, spectral multipliers and the holomorphic functional calculus for $L$, and the behavior of Gaussian Riesz transforms. Throughout, the lack of translation invariance forces techniques different from the Euclidean case; proofs are organized around semigroup methods, covering arguments adapted to $\gamma_d$, and Littlewood–Paley theory in the Gaussian setting. The course prepares participants for modern Gaussian harmonic analysis and for applications in stochastic analysis.
In this course we discuss analysis for the Gaussian measure $\gamma_d$ on $\mathbb{R}^d$ from a semigroup and harmonic–analytic point of view. We begin with the geometry of $\gamma_d$ (global non-doubling and the local-doubling calculus via admissible balls) and the Ornstein–Uhlenbeck operator $L$, introduced through Mehler’s kernel and the associated semigroup. On the spectral side we use Hermite polynomials and the Wiener–It\^o chaos decomposition of $L^2(\gamma_d)$, and we build the basic function spaces $L^p(\gamma_d)$, together with Sobolev and Hardy spaces adapted to $\gamma_d$. Central tools include hypercontractivity and logarithmic Sobolev inequalities, maximal functions, spectral multipliers and the holomorphic functional calculus for $L$, and the behavior of Gaussian Riesz transforms. Throughout, the lack of translation invariance forces techniques different from the Euclidean case; proofs are organized around semigroup methods, covering arguments adapted to $\gamma_d$, and Littlewood–Paley theory in the Gaussian setting. The course prepares participants for modern Gaussian harmonic analysis and for applications in stochastic analysis.
讲师
日期
2025年10月14日 至 12月30日
位置
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| 周二 | 15:20 - 16:55 | A7-302 | ZOOM 12 | 815 762 8413 | BIMSA |
听众
Graduate
, 博士后
, Researcher
视频公开
不公开
笔记公开
不公开
语言
英文