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Related papers: The Primal versus the Dual Ising Model

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The finite size scaling behaviour for the Ising model in five dimensions, with either free or cyclic boundary, has been the subject for a long running debate. The older papers have been based on ideas from e.g. field theory or…

Statistical Mechanics · Physics 2015-02-20 P. H. Lundow , K. Markström

We show that the two dimensional Ising model is complete, in the sense that the partition function of any lattice model on any graph is equal to the partition function of the 2D Ising model with complex coupling. The latter model has all…

Quantum Physics · Physics 2013-05-30 V. Karimipour , M. H. Zarei

We extend recent higher order concentration results in the discrete setting to include functions of possibly dependent variables whose distribution (on the product space) satisfies a logarithmic Sobolev inequality with respect to a…

Probability · Mathematics 2020-05-15 Friedrich Götze , Holger Sambale , Arthur Sinulis

We develop dependent hierarchical normalized random measures and apply them to dynamic topic modeling. The dependency arises via superposition, subsampling and point transition on the underlying Poisson processes of these measures. The…

Machine Learning · Computer Science 2012-06-22 Changyou Chen , Nan Ding , Wray Buntine

The cutoff phenomenon describes a sharp transition in the convergence of a Markov chain to equilibrium. In recent work, the authors established cutoff and its location for the stochastic Ising model on the $d$-dimensional torus $(Z/nZ)^d$…

Probability · Mathematics 2012-11-06 Eyal Lubetzky , Allan Sly

During the past decades, the Ising distribution has attracted interest in many applied disciplines, as the maximum entropy distribution associated to any set of correlated binary (`spin') variables with observed means and covariances.…

Disordered Systems and Neural Networks · Physics 2019-05-13 Adrien Wohrer

We study the domain growth of the one-dimensional kinetic Ising model under the competing influence of Glauber dynamics at temperature T and Kawasaki dynamics with a configuration-independent rate. The scaling of the structure factor is…

Statistical Mechanics · Physics 2009-10-31 Zhi-Feng Huang , Bing-Lin Gu , Yun Tang

We propose a novel way of investigating the universal properties of spin systems by coupling them to an ensemble of causal dynamically triangulated lattices, instead of studying them on a fixed regular or random lattice. Somewhat…

High Energy Physics - Lattice · Physics 2008-11-26 D. Benedetti , R. Loll

We introduce a transfer matrix formalism for the (annealed) Ising model coupled to two-dimensional causal dynamical triangulations. Using the Krein-Rutman theory of positivity preserving operators we study several properties of the emerging…

Mathematical Physics · Physics 2013-07-15 J. C. Hernandez , Y. Suhov , A. Yambartsev , S. Zohren

The Ising model, in presence of an external magnetic field, is isomorphic to a model of localized interacting particles satisfying the Fermi statistics. By using this isomorphism, we construct a general solution of the Ising model which…

Strongly Correlated Electrons · Physics 2007-05-23 Ferdinando Mancini

Most traditional models of uncertainty have focused on the associational relationship among variables as captured by conditional dependence. In order to successfully manage intelligent systems for decision making, however, we must be able…

Artificial Intelligence · Computer Science 2015-05-19 David Heckerman , Ross D. Shachter

In this paper we describe a physical problem, based on electromagnetic fields, whose topological constraints are higher dimensional versions of Kirchhoff's laws, involving $2-$ simplicial complexes embedded in $\mathbb{R} ^3$ rather than…

Combinatorics · Mathematics 2017-11-17 Hariharan Narayanan , H. Narayanan

Gaussian graphical models have been used to study intrinsic dependence among several variables, but the Gaussianity assumption may be restrictive in many applications. A nonparanormal graphical model is a semiparametric generalization for…

Methodology · Statistics 2020-05-20 Jami J. Mulgrave , Subhashis Ghosal

Representing and exploiting multivariate signals requires capturing relations between variables, which we can represent by graphs. Graph dictionaries allow to describe complex relational information as a sparse sum of simpler structures,…

Machine Learning · Computer Science 2026-01-09 William Cappelletti , Pascal Frossard

Exact expressions of the boundary state and the form factors of the Ising model are used to derive differential equations for the one-point functions of the energy and magnetization operators of the model in the presence of a boundary…

High Energy Physics - Theory · Physics 2009-10-28 R. Konik , A. LeClair , G. Mussardo

We study the Ising model under a time-varying, but spatially homogeneous, Gaussian random magnetic field. In the Monte Carlo simulations, we go beyond the standard analysis of the order parameter by measuring the magnetization probability…

Statistical Mechanics · Physics 2026-03-30 Sara Oliver-Bonafoux , Raul Toral , Amitabha Chakrabarti

We study, using Monte Carlo dynamics, the time ($t$) dependent average magnetization per spin $m(t)$ behavior of 2-D kinetic Ising model under a binary ($\pm h_0$) stochastic field $h(t)$. The time dependence of the stochastic field is such…

Statistical Mechanics · Physics 2013-12-02 Asim Ghosh , Bikas K. Chakrabarti

The $Z$-invariant Ising model (Baxter in Philos Trans R Soc Lond A Math Phys Eng Sci 289(1359):315--346, 1978) is defined on an isoradial graph and has coupling constants depending on an elliptic parameter $k$. When $k=0$ the model is…

Probability · Mathematics 2020-10-28 Cédric Boutillier , Béatrice de Tilière , Kilian Raschel

We discuss the finite-size scaling of the ferromagnetic Ising model on random regular graphs. These graphs are locally tree-like, and in the limit of large graphs, the Bethe approximation gives the exact free energy per site. In the…

Statistical Mechanics · Physics 2022-03-09 Suman Kulkarni , Deepak Dhar

In this paper, we explore the two-star Exponential Random Graph Model, which is a two parameter exponential family on the space of simple labeled graphs. We introduce auxiliary variables to express the two-star model as a mixture of the…

Statistics Theory · Mathematics 2021-03-04 Sumit Mukherjee , Yuanzhe Xu