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

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
Apple Machine Learning Research
Apple Machine Learning Research
Last Week in AI
Last Week in AI
Blog — PlanetScale
Blog — PlanetScale
V
Visual Studio Blog
月光博客
月光博客
博客园 - 三生石上(FineUI控件)
博客园 - Franky
IT之家
IT之家
博客园 - 叶小钗
Engineering at Meta
Engineering at Meta
The GitHub Blog
The GitHub Blog
雷峰网
雷峰网
腾讯CDC
博客园 - 聂微东
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
V
V2EX
人人都是产品经理
人人都是产品经理
MongoDB | Blog
MongoDB | Blog
大猫的无限游戏
大猫的无限游戏
Martin Fowler
Martin Fowler
宝玉的分享
宝玉的分享
博客园_首页
G
Google Developers 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
Environment seen from infinite geodesics in Liouville Qua...
Riddhipratim Basu, Manan Bhatia, Shirshendu Ganguly · 2021-07-27 · via math.PR updates on arXiv.org

First passage percolation (FPP) on $\mathbb{Z}^d$ or $\mathbb{R}^d$ is a canonical model of a random metric space where the standard Euclidean geometry is distorted by random noise. Of central interest is the length and the geometry of the geodesic, the shortest path between points. Since the latter, owing to its length minimization, traverses through atypically low values of the underlying noise variables, it is an important problem to quantify the disparity between the environment rooted at a point on the geodesic and the typical one. We investigate this in the context of $γ$-Liouville Quantum Gravity (LQG) (where $γ\in (0,2)$ is a parameter) -- a random Riemannian surface induced on the complex plane by the random metric tensor $e^{2γh/d_γ} ({dx^2+dy^2}),$ where $h$ is the whole plane, properly centered, Gaussian Free Field (GFF), and $d_γ$ is the associated dimension. We consider the unique infinite geodesic $Γ$ from the origin, parametrized by the logarithm of its chemical length, and show that, for an almost sure realization of $h$, the distributions of the appropriately scaled field and the induced metric on a ball, rooted at a point "uniformly" sampled on $Γ$, converge to deterministic measures on the space of generalized functions and continuous metrics on the unit disk respectively. Moreover, we show that the limiting objects living on the unit disk are singular with respect to their typical counterparts, but become absolutely continuous away from the origin. Our arguments rely on unearthing a regeneration structure with fast decay of correlation in the geodesic owing to coalescence and the domain Markov property of the GFF. While there have been significant recent advances around this question for stochastic planar growth models in the KPZ class, the present work initiates this research program in the context of LQG.