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The burning number of a graph $G$ is the smallest number $b$ such that the vertices of $G$ can be covered by balls of radii $0, 1, \dots, b-1$. As computing the burning number of a graph is known to be NP-hard, even on trees, it is natural…

Combinatorics · Mathematics 2023-09-07 Anders Martinsson

We consider sampling in the so-called low-temperature regime, which is typically characterised by non-local behaviour and strong global correlations. Canonical examples include sampling independent sets on bipartite graphs and sampling from…

Discrete Mathematics · Computer Science 2025-04-23 Andreas Galanis , Leslie Ann Goldberg , Paulina Smolarova

We present approximation algorithms for the following NP-hard optimization problems related to bottleneck spanning trees in metric spaces. 1. The disjoint bottleneck spanning tree problem: Given $n$ pairs of points in a metric space, find…

Computational Geometry · Computer Science 2021-11-11 Ahmad Biniaz , Anil Maheshwari , Michiel Smid

We consider the problem of approximating the partition function of the hard-core model on planar graphs of degree at most 4. We show that when the activity lambda is sufficiently large, there is no fully polynomial randomised approximation…

Computational Complexity · Computer Science 2014-07-08 Leslie Ann Goldberg , Mark Jerrum , Colin McQuillan

We show that the one-loop effective action at finite temperature for a scalar field with quartic interaction has the same renormalized expression as at zero temperature if written in terms of a certain classical field $\phi_c$, and if we…

High Energy Physics - Phenomenology · Physics 2014-11-21 A. Bessa , F. T. Brandt , C. A. A. de Carvalho , E. S. Fraga

We express the partition functions of the spanning tree on finite square lattices under five different sets of boundary conditions (free, cylindrical, toroidal, M\"obius strip, and Klein bottle) in terms of a principal partition function…

Statistical Mechanics · Physics 2016-10-26 Nickolay Izmailian , Ralph Kenna

Methods for understanding classical disordered spin systems with interactions conforming to some idealized graphical structure are well developed. The equilibrium properties of the Sherrington-Kirkpatrick model, which has a densely…

Disordered Systems and Neural Networks · Physics 2013-05-29 Jack Raymond , David Saad

Diamond "lattices" are sequences of recursively-defined graphs that provide a network of directed pathways between two fixed root nodes, $A$ and $B$. The construction recipe for diamond graphs depends on a branching number $b\in \mathbb{N}$…

Probability · Mathematics 2017-09-06 Jeremy Clark

The Bethe approximation, or loopy belief propagation algorithm is a successful method for approximating partition functions of probabilistic models associated with a graph. Chertkov and Chernyak derived an interesting formula called Loop…

Discrete Mathematics · Computer Science 2009-11-14 Yusuke Watanabe , Kenji Fukumizu

A common subgraph of two graphs $G_1$ and $G_2$ is a graph that is isomorphic to subgraphs of $G_1$ and $G_2$. In the largest common subgraph problem the task is to determine a common subgraph for two given graphs $G_1$ and $G_2$ that is of…

Data Structures and Algorithms · Computer Science 2024-03-07 Dieter Rautenbach , Florian Werner

Twin-width is a structural width parameter introduced by Bonnet, Kim, Thomass\'e and Watrigant [FOCS 2020]. Very briefly, its essence is a gradual reduction (a contraction sequence) of the given graph down to a single vertex while…

We present a detailed study of simple `tree' models for off equilibrium dynamics and aging in glassy systems. The simplest tree describes the landscape of a random energy model, whereas multifurcating trees occur in the solution of the…

Condensed Matter · Physics 2009-10-22 J-P. Bouchaud , D. S. Dean

Algorithms for binary classification based on adaptive tree partitioning are formulated and analyzed for both their risk performance and their friendliness to numerical implementation. The algorithms can be viewed as generating a set…

Statistics Theory · Mathematics 2014-11-05 Peter Binev , Albert Cohen , Wolfgang Dahmen , Ronald DeVore

We study the ground states of the pieces' model in the Fermi-Dirac statistics in the thermodynamic limit. In other words, we consider the minimizing configurations of $ n $ interacting fermions in an interval $ \Lambda $ divided into pieces…

Mathematical Physics · Physics 2023-03-29 Vadim Ognov

We study the arboricity A and the maximum number T of edge-disjoint spanning trees of the Erdos-Renyi random graph G(n,p). For all p(n) in [0,1], we show that, with high probability, T is precisely the minimum between delta and…

Combinatorics · Mathematics 2014-05-29 Pu Gao , Xavier Pérez-Giménez , Cristiane M. Sato

We present a new tensor network algorithm for calculating the partition function of interacting quantum field theories in 2 dimensions. It is based on the Tensor Renormalization Group (TRG) protocol, adapted to operate entirely at the level…

Quantum Physics · Physics 2021-11-24 Manuel Campos , German Sierra , Esperanza Lopez

Sparse approximations using highly over-complete dictionaries is a state-of-the-art tool for many imaging applications including denoising, super-resolution, compressive sensing, light-field analysis, and object recognition. Unfortunately,…

Computer Vision and Pattern Recognition · Computer Science 2014-12-03 Ali Ayremlou , Thomas Goldstein , Ashok Veeraraghavan , Richard Baraniuk

The virial expansion method is applied within a harmonic approximation to an interacting N-body system of identical fermions. We compute the canonical partition functions for two and three particles to get the two lowest orders in the…

Statistical Mechanics · Physics 2012-12-27 J. R. Armstrong , N. T. Zinner , D. V. Fedorov , A. S. Jensen

We study approximations of the partition function of dense graphical models. Partition functions of graphical models play a fundamental role is statistical physics, in statistics and in machine learning. Two of the main methods for…

Machine Learning · Computer Science 2018-02-21 Vishesh Jain , Frederic Koehler , Elchanan Mossel

We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estimation, we do not assume the true distribution corresponds to…

Machine Learning · Statistics 2010-10-21 Han Liu , Min Xu , Haijie Gu , Anupam Gupta , John Lafferty , Larry Wasserman
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