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

GbyAI
GbyAI
Y
Y Combinator Blog
F
Fortinet All Blogs
H
Hackread – Cybersecurity News, Data Breaches, AI and More
N
Netflix TechBlog - Medium
T
Tailwind CSS Blog
aimingoo的专栏
aimingoo的专栏
博客园 - Franky
T
The Blog of Author Tim Ferriss
D
DataBreaches.Net
量子位
博客园 - 三生石上(FineUI控件)
I
InfoQ
Engineering at Meta
Engineering at Meta
WordPress大学
WordPress大学
阮一峰的网络日志
阮一峰的网络日志
爱范儿
爱范儿
D
Docker
美团技术团队
雷峰网
雷峰网
U
Unit 42
Stack Overflow Blog
Stack Overflow Blog
Recent Announcements
Recent Announcements
人人都是产品经理
人人都是产品经理

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
Gaussian free field light cones and SLE$_κ(ρ)$
Jason Miller, Scott Sheffield · 2016-06-08 · via math.PR updates on arXiv.org

We derive a surprising correspondence between SLE$_κ(ρ)$ processes and light cones of the Gaussian free field (GFF). Recall that (one-sided, chordal, origin-seeded) SLE$_κ(ρ)$ processes are in some sense the simplest and most natural variants of the Schramm-Loewner evolution. They were originally defined only for $ρ> -2$, but one can use Lévy compensation to extend the definition to any $ρ> -2-\tfracκ{2}$ and to obtain qualitatively different curves. The triangle $T = \{(κ, ρ): (-2-\tfracκ{2})\vee (\tfracκ{2}-4) < ρ< -2 \}$ is the primary focus of this paper. When $(κ, ρ) \in T$, the SLE$_κ(ρ)$ curves are highly non-simple (and double points are dense) even though $κ< 4$. Let $h$ be an instance of the GFF. Fix $κ\in (0,4)$ and $χ= 2/\sqrtκ - \sqrtκ/2$. Recall that an imaginary geometry ray is a flow line of $e^{i(h/χ+θ)}$ that looks locally like SLE$_κ$. The light cone with parameter $θ\in [0, π]$ is the set of points reachable from the origin by a sequence of rays with angles in $[-θ/2, θ/2]$. When $θ=0$, the light cone looks like SLE$_κ$, and when $θ= π$ it looks like the range of an SLE$_{16/κ}$. We find that when $θ\in (0, π)$ the light cones are either fractal carpets with a dense set of holes or space-filling regions with no holes. We show that every non-space-filling light cone (with $θ\in (0,π]$ and $κ\in (0,4)$) agrees in law with the range of an SLE$_κ(ρ)$ process with $(κ, ρ) \in T$. Conversely, the range of any SLE$_κ(ρ)$ with $(κ,ρ) \in T$ agrees in law with a non-space-filling light cone. As a consequence, we obtain the first proof that these SLE$_κ(ρ)$ processes are continuous and show that they are natural path-valued functions of the GFF.