惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园 - 三生石上(FineUI控件)
S
SegmentFault 最新的问题
Jina AI
Jina AI
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
IT之家
IT之家
美团技术团队
V
Visual Studio Blog
人人都是产品经理
人人都是产品经理
博客园 - 叶小钗
有赞技术团队
有赞技术团队
GbyAI
GbyAI
宝玉的分享
宝玉的分享
腾讯CDC
M
MIT News - Artificial intelligence
博客园 - 【当耐特】
Google DeepMind News
Google DeepMind News
月光博客
月光博客
MyScale Blog
MyScale Blog
Last Week in AI
Last Week in AI
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园 - 司徒正美
Recent Announcements
Recent Announcements
MongoDB | Blog
MongoDB | Blog

math.PR updates on arXiv.org

Visibility in the Boolean Model on Harmonic Manifolds Global estimates on the Brenier map Geodesics and Wandering Exponents in Brochette First-Passage Percolation State-dependent inverse-subordinator time changes of regenerative processes: Excursion structure and multiscale occupation-time limits Randomly twisted transfer operators and singular values statistics Generalized Bessel-Dunkl diffusions An almost sure invariance principle for the Takagi-van der Waerden class functions Central limit theorems for high dimensional lattice polytopes: cosmological polytopes Convergence rate estimates for semigroups and heat kernels associated with resistance forms Second-order Poincaré inequalities and localization on the Poisson space Maximum Probability of Independence in Transitive Matroids On global solutions to the semidiscrete stochastic heat equation The Poisson Tail Conjecture for primes in short intervals A Complete Spectral Analysis of the CEV Operator with Applications to Arbitrage Holographic functions and neural networks From Betting to Empirical Bernstein LIL Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise Pointwise Generalization in Deep Neural Networks Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriors Wasserstein bounds for denoising diffusion probabilistic models via the Föllmer process A note on connections between the Föllmer process and the denoising diffusion probabilistic model Simple Approximation and Derivative Free Inference-Time Scaling for Diffusion Models via Sequential Monte Carlo on Path Measures Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations A Fourier perspective on the learning dynamics of neural networks: from sample complexities to mechanistic insights Propagation of Chaos in Contextual Flow Maps Dimension-Uniform Discretization Analysis of Preconditioned Annealed Langevin Dynamics for Multimodal Gaussian Mixtures $α$-TCAV: A Unified Framework for Testing with Concept Activation Vectors Scaling Laws from Sequential Feature Recovery: A Solvable Hierarchical Model On the Limits of Latent Reuse in Diffusion Models State-of-art minibatches via novel DPP kernels: discretization, wavelets, and rough objectives
On the dimension of limit sets on $\mathbb{P}(\mathbb{R}^...
Jialun Li, Wenyu Pan, Disheng Xu · 2023-11-17 · via math.PR updates on arXiv.org

This paper investigates the (semi)group action of $\mathrm{SL}_3(\mathbb{R})$ on $\mathbb{P}(\mathbb{R}^3)$, a primary example of non-conformal, non-linear, and non-strictly contracting action. We study the Hausdorff dimension of a dynamically defined limit set in $\mathbb{P}(\mathbb{R}^3)$ and generalize the classical Patterson-Sullivan formula using the approach of stationary measures. The two main examples are Anosov representations in $\mathrm{SL}_3(\mathbb{R})$ and the Rauzy gasket. 1. For Anosov representations in $\mathrm{SL}_3(\mathbb{R})$, we establish a sharp lower bound for the dimension of their limit sets in $\mathbb{P}(\mathbb{R}^3)$. Coupled with the upper bound in Pozzetti-Sambarino-Wienhard, it shows that their Hausdorff dimensions equal the affinity exponents. The merit of our approach is that it works uniformly for all the components of irreducible Anosov representations in $\mathrm{SL}_3(\mathbb{R})$. As an application, it reveals a surprising dimension jump phenomenon in the Barbot component, which is a local generalization of Bowen's dimension rigidity result. 2. For the Rauzy gasket, we confirm a folklore conjecture about the Hausdorff dimension of the gasket and improve the numerical lower bound to $3/2$. These results originate from a dimension formula of stationary measures on $\mathbb{P}(\mathbb{R}^3)$. Let $ν$ be a probability measure on $\mathrm{SL}_3(\mathbb{R})$ whose support is finite and spans a Zariski dense subgroup. Let $μ$ be the associated stationary measure for the action on $\mathbb{P}(\mathbb{R}^3)$. Under the exponential separation condition on $ν$, we prove that the Hausdorff dimension of $μ$ equals its Lyapunov dimension, which extends Hochman-Solomyak and Bárány-Hochman-Rapaport to non-conformal and projective settings respectively.