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We study the ferromagnetic Ising model with long-range interactions in two dimensions. We first present results of a Monte Carlo study which shows that the long-range interactions dominate over the short-range ones in the intermediate…

Statistical Mechanics · Physics 2014-07-17 Thibault Blanchard , Marco Picco , M. A. Rajabpour

We study the q-dependent susceptibility chi(q) of a Z-invariant ferromagnetic Ising model on a Penrose tiling, as first introduced by Korepin using de Bruijn's pentagrid for the rapidity lines. The pair-correlation function for this model…

Statistical Mechanics · Physics 2015-06-24 Helen Au-Yang , Jacques H. H. Perk

The lack of evidence in favor of any new physics models means that the search for new physics beyond the Standard Model (BSM) is wide open, with no direction clearly more promising than any other. This marks a turn towards what can be…

History and Philosophy of Physics · Physics 2025-07-08 Martin King

Multiplex networks consist of a fixed set of nodes connected by several sets of edges which are generated separately and correspond to different networks ("layers"). Here, a simple variant of the Ising model on multiplex networks with two…

Statistical Mechanics · Physics 2018-01-17 Andrzej Krawiecki

Finite size effects for the Ising Model coupled to two dimensional random surfaces are studied by exploiting the exact results from the 2-matrix models. The fixed area partition function is numerically calculated with arbitrary precision by…

High Energy Physics - Theory · Physics 2009-10-28 N. D. Hari Dass , B. E. Hanlon , T. Yukawa

Statistical inference for exponential-family models of random graphs with dependent edges is challenging. We stress the importance of additional structure and show that additional structure facilitates statistical inference. A simple…

Statistics Theory · Mathematics 2020-03-13 Michael Schweinberger , Jonathan Stewart

The problem of structure estimation in graphical models with latent variables is considered. We characterize conditions for tractable graph estimation and develop efficient methods with provable guarantees. We consider models where the…

Machine Learning · Statistics 2013-04-23 Animashree Anandkumar , Ragupathyraj Valluvan

The demagnetizing factor has an important effect on the physics of ferromagnets. For cuboidal samples it depends on susceptibility and the historic problem of determining this function continues to generate theoretical and experimental…

Strongly Correlated Electrons · Physics 2020-10-22 Mikael Twengström , Laura Bovo , Oleg A. Petrenko , Steven T. Bramwell , Patrik Henelius

This paper introduces simple analytical formulas for the grid impedance of electrically dense arrays of square patches and for the surface impedance of high-impedance surfaces based on the dense arrays of metal strips or square patches over…

We examined in this work the effect of the inter-grains distributions as well as the scaling of the complex impedance in order to analyze its frequency dependance for composite metal-insulator films. The dependance of the characteristic…

Disordered Systems and Neural Networks · Physics 2007-05-23 Lotfi Zekri , Nouredine Zekri , Jean-Pierre Clerc

We propose an importance sampling scheme to estimate the partition function of the two-dimensional ferromagnetic Ising model and the two-dimensional ferromagnetic $q$-state Potts model, both in the presence of an external magnetic field.…

Computation · Statistics 2015-02-06 Mehdi Molkaraie

The ferromagnetic Ising spins are modeled on a recursive lattice constructed from random-angled rhombus units with stochastic configurations, to study the magnetic properties of the bulk Fe-based metallic glass. The integration of spins on…

Materials Science · Physics 2015-07-06 Ran Huang , Ling Zhang , Chong Chen , Chengjie Wu , Linyin Yan

We study detection methods for multivariable signals under dependent noise. The main focus is on three-dimensional signals, i.e. on signals in the space-time domain. Examples for such signals are multifaceted. They include geographic and…

Probability · Mathematics 2018-03-20 Annabel Prause , Ansgar Steland

We describe a method for deriving effective low-energy theories of electronic interactions at graphene edges. Our method is applicable to general edges of honeycomb lattices (zigzag, chiral, and even disordered) as long as localized…

Strongly Correlated Electrons · Physics 2013-07-22 Manuel J. Schmidt , Michael Golor , Thomas C. Lang , Stefan Wessel

The Ising model with ferromagnetic couplings on the Hanoi networks is analyzed with an exact renormalization group. In particular, the fixed-points are determined and the renormalization-group flow for certain initial conditions is…

Disordered Systems and Neural Networks · Physics 2015-03-17 S. Boettcher , C. T. Brunson

Finite-range interacting spin models are the simplest models to study the effect of beyond nearest-neighbour interactions and access new effects caused by the range of the interactions. Recent experiments have reached the regime of dominant…

Atomic Physics · Physics 2018-01-16 Peter Schauss

Inferring a binary connectivity graph from resting-state fMRI data for a single subject requires making several methodological choices and assumptions that can significantly affect the results. In this study, we investigate the robustness…

Methodology · Statistics 2025-03-20 Alice Chevaux , Ali Fahkar , Kévin Polisano , Irène Gannaz , Sophie Achard

We focus on causal discovery in the presence of measurement error in linear systems where the mixing matrix, i.e., the matrix indicating the independent exogenous noise terms pertaining to the observed variables, is identified up to…

Machine Learning · Computer Science 2022-11-09 Yuqin Yang , AmirEmad Ghassami , Mohamed Nafea , Negar Kiyavash , Kun Zhang , Ilya Shpitser

There is proposed a model of scale-free random graphs which are locally close to the uncorrelated complex random networks with divergent $\langle k^2 \rangle$ studied in e.g. S. N. Dorogovtsev {\it et al}, Rev. Mod. Phys. {\bf 80}, 1275…

Mathematical Physics · Physics 2011-09-22 Yuri Kozitsky

This study highlights the importance of conducting comprehensive model inspection as part of comparative performance analyses. Here, we investigate the effect of modelling choices on the feature learning characteristics of graph neural…

Machine Learning · Computer Science 2024-05-03 Nairouz Shehata , Carolina Piçarra , Anees Kazi , Ben Glocker