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We introduce a hierarchical class of approximations of the random Ising spin glass in $d$ dimensions. The attention is focused on finite clusters of spins where the action of the rest of the system is properly taken into account. At the…

Disordered Systems and Neural Networks · Physics 2009-10-30 R. Baviera , M. Pasquini , M. Serva

We present a systematic small-correlation expansion to solve the inverse Ising problem: find a set of couplings and fields corresponding to a given set of correlations and magnetizations. Couplings are calculated up to the third order in…

Disordered Systems and Neural Networks · Physics 2009-01-07 Vitor Sessak , Rémi Monasson

We introduce a numerical linked cluster expansion for square-lattice models whose building block is an L-shape cluster. For the spin-1/2 models studied in this work, we find that this expansion exhibits a similar or better convergence of…

Statistical Mechanics · Physics 2025-07-10 Mahmoud Abdelshafy , Marcos Rigol

We prove functional limit theorems for dynamical systems in the presence of clusters of large values which, when summed and suitably normalised, get collapsed in a jump of the limiting process observed at the same time point. To keep track…

Dynamical Systems · Mathematics 2025-06-04 Ana Cristina Moreira Freitas , Jorge Milhazes Freitas , Mike Todd

We propose an algorithm to obtain numerically approximate solutions of the direct Ising problem, that is, to compute the free energy and the equilibrium observables of spin systems with arbitrary two-spin interactions. To this purpose we…

Statistical Mechanics · Physics 2019-11-20 Simona Cocco , Giancarlo Croce , Francesco Zamponi

We review some recent progress on applications of Cluster Expansions. We focus on a system of classical particles living in a continuous medium and interacting via a stable and tempered pair potential. We review the cluster expansion in…

Mathematical Physics · Physics 2023-04-26 Dimitrios Tsagkarogiannis

We present the first exact asymptotic characterization of sequential dynamics for a broad class of local update algorithms on the Sherrington-Kirkpatrick (SK) model with Ising spins. Focusing on dynamics implemented via systematic scan --…

Disordered Systems and Neural Networks · Physics 2025-06-13 Yatin Dandi , David Gamarnik , Francisco Pernice , Lenka Zdeborová

We introduce a white graph expansion for the method of perturbative continuous unitary transformations when implemented as a linked cluster expansion. The essential idea behind an expansion in white graphs is to perform an optimized…

Strongly Correlated Electrons · Physics 2015-09-02 K. Coester , K. P. Schmidt

We consider a binary system of small and large objects in the continuous space interacting via a non-negative potential. By integrating over the small objects, the effective interaction between the large ones becomes multi-body. We prove…

Mathematical Physics · Physics 2020-02-19 Sabine Jansen , Dimitrios Tsagkarogiannis

We revisit the classical approach to cluster expansions, based on tree graphs, and establish a new convergence condition that improves those by Kotecky-Preiss and Dobrushin, as we show in some examples. The two ingredients of our approach…

Mathematical Physics · Physics 2009-11-11 Roberto Fernandez , Aldo Procacci

In this paper, we further explore the local-to-global approach for expansion of simplicial complexes that we call local spectral expansion. Specifically, we prove that local expansion in the links imply the global expansion phenomena of…

Combinatorics · Mathematics 2018-03-06 Izhar Oppenheim

"Cluster" extensions of the dynamical mean field method to include longer range correlations are discussed. It is argued that the clusters arising in these methods are naturally interpreted not as actual subunits of a physical lattice but…

Strongly Correlated Electrons · Physics 2009-11-10 S. Okamoto , A. J. Millis , H. Monien , A. Fuhrmann , .

We consider a two-dimensional Ising model with random i.i.d. nearest-neighbor ferromagnetic couplings and no external magnetic field. We show that, if the probability of supercritical couplings is small enough, the system admits a…

Disordered Systems and Neural Networks · Physics 2015-05-30 L. Bertini , Emilio N. M. Cirillo , E. Olivieri

We formulate a general setting for the cluster expansion method and we discuss sufficient criteria for its convergence. We apply the results to systems of classical and quantum particles with stable interactions.

Mathematical Physics · Physics 2009-05-08 Suren Poghosyan , Daniel Ueltschi

We present a novel approach to spin-adapted coupled cluster theory. This approach is based on the entanglement of an open-shell molecule with electrons in a non-interacting bath; together they form a closed-shell state. For the total…

Chemical Physics · Physics 2023-05-22 Sarai Dery Folkestad , Bendik Støa Sannes , Henrik Koch

If we have a system of binary variables and we measure the pairwise correlations among these variables, then the least structured or maximum entropy model for their joint distribution is an Ising model with pairwise interactions among the…

Disordered Systems and Neural Networks · Physics 2014-09-12 Michele Castellana , William Bialek

We study the stochastic dynamics of Ising spin models with random bonds, interacting on finitely connected Poissonnian random graphs. We use the dynamical replica method to derive closed dynamical equations for the joint spin-field…

Disordered Systems and Neural Networks · Physics 2009-11-13 A. Mozeika , A. C. C. Coolen

The cluster analysis of very large objects is an important problem, which spans several theoretical as well as applied branches of mathematics and computer science. Here we suggest a novel approach: under assumption of local convergence of…

Combinatorics · Mathematics 2015-10-28 Jaroslav Nesetril , Patrice Ossona de Mendez

We provide a sufficient condition for the uniqueness in distribution of Gibbs point processes with non-negative pairwise interaction, together with convergent expansions of the log-Laplace functional, factorial moment densities and…

Probability · Mathematics 2020-01-14 Sabine Jansen

There have been rapid developments in model-based clustering of graphs, also known as block modelling, over the last ten years or so. We review different approaches and extensions proposed for different aspects in this area, such as the…

Machine Learning · Statistics 2020-01-01 Clement Lee , Darren J Wilkinson