Paper detail

Recursive Scheme for Angles of Random Simplices, and Applications to Random Polytopes

Consider a random simplex $[X_1,\ldots,X_n]$ defined as the convex hull of independent identically distributed random points $X_1,\ldots,X_n$ in $\mathbb{R}^{n-1}$ with the following beta density: $$ f_{n-1,β} (x) \propto (1-\|x\|^2)^β 1_{\{\|x\| < 1\}}, \qquad x\in\mathbb{R}^{n-1}, \quad β>-1. $$ Let $J_{n,k}(β)$ be the expected internal angle of the simplex $[X_1,\ldots,X_n]$ at its face $[X_1,\ldots,X_k]$. Define $\tilde J_{n,k}(β)$ analogously for i.i.d. random points distributed according to the beta&#39; density $$ \tilde f_{n-1,β} (x) \propto (1+\|x\|^2)^{-β}, \qquad x\in\mathbb{R}^{n-1}, \quad β> \frac{n-1}{2}. $$ We derive formulae for $J_{n,k}(β)$ and $\tilde J_{n,k}(β)$ which make it possible to compute these quantities symbolically, in finitely many steps, for any integer or half-integer value of $β$. For $J_{n,1}(\pm 1/2)$ we even provide explicit formulae in terms of products of Gamma functions. We give applications of these results to two seemingly unrelated problems of stochastic geometry. (i) We compute the expected $f$-vectors of the typical Poisson-Voronoi cells in dimensions up to $10$. (ii) Consider the random polytope $K_{n,d} := [U_1,\ldots,U_n]$ where $U_1,\ldots,U_n$ are i.i.d. random points sampled uniformly inside some $d$-dimensional convex body $K$ with smooth boundary and unit volume. M. Reitzner proved the existence of the limit of the normalized expected $f$-vector of $K_{n,d}$: $$ \lim_{n\to\infty} n^{-{\frac{d-1}{d+1}}}\mathbb E \mathbf f(K_{n,d}) = \mathbf c_d \cdot Ω(K), $$ where $Ω(K)$ is the affine surface area of $K$, and $\mathbf c_d$ is an unknown vector not depending on $K$. We compute $\mathbf c_d$ explicitly in dimensions up to $d=10$ and also solve the analogous problem for random polytopes with vertices distributed uniformly on the sphere.

preprint2020arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.