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We construct an almost sure bijection that recovers the directed landscape on the half-plane from a sequence of independent Brownian motions. This map is the natural scaling limit of the Robinson--Schensted--Knuth (RSK) correspondence. The…

Probability · Mathematics 2026-05-18 Duncan Dauvergne , Bálint Virág

The directed landscape is a random directed metric on the plane that arises as the scaling limit of classical metric models in the KPZ universality class. Typical pairs of points in the directed landscape are connected by a unique geodesic.…

Probability · Mathematics 2023-06-23 Duncan Dauvergne

We consider planar directed last-passage percolation on the square lattice with general i.i.d. weights and study the geometry of the full set of semi-infinite geodesics in a typical realization of the random environment. The structure of…

Probability · Mathematics 2023-08-01 Christopher Janjigian , Firas Rassoul-Agha , Timo Seppäläinen

Geodesic coalescence, or the tendency of geodesics to merge together, is a hallmark phenomenon observed in a variety of planar random geometries involving a random distortion of the Euclidean metric. As a result of this, the union of…

Probability · Mathematics 2024-04-03 Manan Bhatia

The directed landscape is a random directed metric on the plane that arises as the scaling limit of metric models in the KPZ universality class. For a pair of points p, q, the disjointness gap G(p; q) measures the shortfall when we optimize…

Probability · Mathematics 2026-02-11 Duncan Dauvergne , Oliver Scott Pankratz

The directed landscape is a prominent model of random geometry which is believed to be the universal scaling limit of all planar random geometries in the Kardar-Parisi-Zhang universality class. It comes equipped with a few different natural…

Probability · Mathematics 2024-04-04 Manan Bhatia

We present a proof of the almost sure existence, uniqueness and coalescence of directed semi-infinite geodesics in planar growth models that is based on properties of an increment-stationary version of the growth process. The argument is…

Probability · Mathematics 2019-07-16 Timo Seppäläinen

We show existence, uniqueness, and directedness properties for infinite geodesics in the FPP model. After giving the fundamental definitions, we describe results by Newman and collaborators giving existence and uniqueness of directed…

Probability · Mathematics 2018-04-17 Jack Hanson

We show that the directed landscape is the unique coupling of the KPZ fixed point from all initial conditions satisfying three natural properties: independent increments, monotonicity, and shift commutativity. Equivalently, we show that the…

Probability · Mathematics 2025-08-12 Duncan Dauvergne , Lingfu Zhang

We prove the existence of semi-infinite geodesics for Brownian last-passage percolation (BLPP). Specifically, on a single event of probability one, there exist semi-infinite geodesics started from every space-time point and traveling in…

Probability · Mathematics 2023-01-18 Timo Seppäläinen , Evan Sorensen

Reconstruction of directional fields is a need in many geometry processing tasks, such as image tracing, extraction of 3D geometric features, and finding principal surface directions. A common approach to the construction of directional…

Computer Vision and Pattern Recognition · Computer Science 2019-07-02 Maria Taktasheva , Albert Matveev , Alexey Artemov , Evgeny Burnaev

When the value $L$ of the directed landscape at a point $(\mathbf{p};\mathbf{q})$ is sufficiently large, the geodesic from $\mathbf{p}$ to $\mathbf{q}$ is rigid and its location fluctuates of order $L^{-1/4}$ around its expectation. We…

Probability · Mathematics 2022-07-13 Zhipeng Liu

We establish fundamental properties of infinite geodesics and competition interfaces in the directed landscape. We construct infinite geodesics in the directed landscape, establish their uniqueness and coalescence, and define Busemann…

Probability · Mathematics 2025-07-08 Mustazee Rahman , Balint Virag

We show that geodesics in the directed landscape have $3/2$-variation and that weight functions along the geodesics have cubic variation. We show that the geodesic and its landscape environment around an interior point has a small-scale…

Probability · Mathematics 2024-10-31 Duncan Dauvergne , Sourav Sarkar , Bálint Virág

The clear understanding of the non-convex landscape of neural network is a complex incomplete problem. This paper studies the landscape of linear (residual) network, the simplified version of the nonlinear network. By treating the gradient…

Algebraic Geometry · Mathematics 2021-02-09 Xiuyi Yang

In this paper, we consider the problem of reconstructing a directed graph using path queries. In this query model of learning, a graph is hidden from the learner, and the learner can access information about it with path queries. For a…

Data Structures and Algorithms · Computer Science 2021-03-17 Mano Vikash Janardhanan , Lev Reyzin

We prove that two half-space models in the KPZ universality class, exponential last-passage percolation and a family of Poisson-avoiding metrics generalizing colored TASEP, converge to a common scaling limit. This scaling limit is the…

Probability · Mathematics 2026-05-11 Duncan Dauvergne , Lingfu Zhang

We consider the Busemann process in planar directed first passage percolation. We extend existing techniques to establish the existence of the process in our setting and determine its distribution in a number of integrable models. As…

Probability · Mathematics 2025-10-23 Sam McKeown

It is a significant challenge to predict the network topology from a small amount of dynamical observations. Different from the usual framework of the node-based reconstruction, two optimization approaches (i.e., the global and partitioned…

Physics and Society · Physics 2016-03-03 Ming Xu , Chuan-Yun Xu , Huan Wang , Yong-Kui Li , Jing-Bo Hu , Ke-Fei Cao

We analyze multi-bounce propagation of light in an unknown hidden volume and demonstrate that the reflected light contains sufficient information to recover the 3D structure of the hidden scene. We formulate the forward and inverse theory…

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