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For dendrite graphs from biological experiments on mouse's retinal ganglion cells, a paper by Nakatsukasa, Saito and Woei reveals a mysterious phase transition phenomenon in the spectra of the corresponding graph Laplacian matrices. While…

Statistics Theory · Mathematics 2020-01-06 Yuyang Xu , Jianfeng Yao

The notion of tree entropy was introduced by the author as a normalized limit of the number of spanning trees in finite graphs, but is defined on random infinite rooted graphs. We give some new expressions for tree entropy; one uses…

Combinatorics · Mathematics 2010-04-27 Russell Lyons

We study basic spectral features of graph Laplacians associated with a class of rooted trees which contains all regular trees. Trees in this class can be generated by substitution processes. Their spectra are shown to be purely absolutely…

Spectral Theory · Mathematics 2011-01-11 Matthias Keller , Daniel Lenz , Simone Warzel

We consider a uniform spanning tree in a $\delta$-square grid approximation of a planar domain $\Omega$. For given integer $n\ge 2$, we condition the tree on the following $n$-arm event: we pick $n$ branches, emanating from $n$ points…

Probability · Mathematics 2025-12-24 Nathanaël Berestycki , Marcin Lis , Mingchang Liu , Eveliina Peltola

In this paper, we study the relation between the partition function of the free scalar field theory on hypercubes with boundary conditions and asymptotics of discrete partition functions on a sequence of "lattices" which approximate the…

Mathematical Physics · Physics 2019-10-09 Yuhang Hou , Santosh Kandel

We prove a Matrix-Tree Theorem enumerating the spanning trees of a cell complex in terms of the eigenvalues of its cellular Laplacian operators, generalizing a previous result for simplicial complexes. As an application, we obtain explicit…

Combinatorics · Mathematics 2011-10-05 Art M. Duval , Caroline J. Klivans , Jeremy L. Martin

Given a bounded Riemann surface $M$ of finite topological type, we show the existence of a universal and conformally invariant scaling limit for the Temperleyan cycle-rooted spanning forest on any sequence of graphs which approximate $M$ in…

Probability · Mathematics 2024-12-11 Nathanaël Berestycki , Benoit Laslier , Gourab Ray

In this article we study asymptotic slopes of strongly semistable vector bundles on a smooth projective surface. A connection between asymptotic slopes and strong restriction theorem of a strongly semistable vector bundle is shown. We also…

Algebraic Geometry · Mathematics 2022-01-10 Mitra Koley , A. J. Parameswaran

On a finite graph, there is a natural family of Boltzmann probability measures on cycle-rooted spanning forests, parametrized by weights on cycles. For a certain subclass of those weights, we construct Gibbs measures in infinite volume, as…

Probability · Mathematics 2023-08-21 Héloïse Constantin

The conformations of topologically constrained double-folded ring polymers can be described as wrappings of randomly branched primitive trees. We extend previous work on the tree statistics under different (solvent) conditions to explore…

Soft Condensed Matter · Physics 2019-01-23 Angelo Rosa , Ralf Everaers

We show variants of spectral sparsification routines can preserve the total spanning tree counts of graphs, which by Kirchhoff's matrix-tree theorem, is equivalent to determinant of a graph Laplacian minor, or equivalently, of any SDDM…

Data Structures and Algorithms · Computer Science 2017-05-03 David Durfee , John Peebles , Richard Peng , Anup B. Rao

This paper considers the asymptotic distribution of the longest edge of the minimal spanning tree and nearest neighbor graph on X_1,...,X_{N_n} where X_1,X_2,... are i.i.d. in \Re^2 with distribution F and N_n is independent of the X_i and…

Probability · Mathematics 2007-05-23 Tailen Hsing , Holger Rootzen

Study of random networks generally requires the nodes to be independently and uniformly distributed such as a Poisson point process. In this work, we venture beyond this standard paradigm and investigate a stochastic forest obtained from a…

Probability · Mathematics 2023-02-28 Rahul Roy , Kumarjit Saha , Anish Sarkar

Trees of finite cone type have appeared in various contexts. In particular, they come up as simplified models of regular tessellations of the hyperbolic plane. The spectral theory of the associated Laplacians can thus be seen as induced by…

Spectral Theory · Mathematics 2014-03-19 Matthias Keller , Daniel Lenz , Simone Warzel

We consider the Laplacian on a rooted metric tree graph with branching number $ K \geq 2 $ and random edge lengths given by independent and identically distributed bounded variables. Our main result is the stability of the absolutely…

Mathematical Physics · Physics 2007-05-23 Michael Aizenman , Robert Sims , Simone Warzel

We study the asymptotic number of certain monotonically labeled increasing trees arising from a generalized evolution process. The main difference between the presented model and the classical model of binary increasing trees is that the…

Combinatorics · Mathematics 2019-10-30 Olivier Bodini , Antoine Genitrini , Bernhard Gittenberger , Stephan Wagner

The uniform recursive tree (URT) is one of the most important models and has been successfully applied to many fields. Here we study exactly the topological characteristics and spectral properties of the Laplacian matrix of a deterministic…

Statistical Mechanics · Physics 2008-07-11 Zhongzhi Zhang , Shuigeng Zhou , Yi Qi , Jihong Guan

We derive the determinant of the Laplacian for the Hanoi networks and use it to determine their number of spanning trees (or graph complexity) asymptotically. While spanning trees generally proliferate with increasing average degree, the…

Statistical Mechanics · Physics 2015-10-08 Stefan Boettcher , Shanshan Li

Spanning trees are relevant to various aspects of networks. Generally, the number of spanning trees in a network can be obtained by computing a related determinant of the Laplacian matrix of the network. However, for a large generic…

Statistical Mechanics · Physics 2011-11-18 Yuan Lin , Bin Wu , Zhongzhi Zhang , Guanrong Chen

Joint distributions over many variables are frequently modeled by decomposing them into products of simpler, lower-dimensional conditional distributions, such as in sparsely connected Bayesian networks. However, automatically learning such…

Machine Learning · Computer Science 2013-01-07 Scott Davies , Andrew Moore