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Evaluating accessible conformational space is computationally expensive and thermal motions are partly neglected in computer models of molecular interactions. This produces error into the estimates of binding strength. We introduce a method…

Quantitative Methods · Quantitative Biology 2016-12-13 Riku Hakulinen , Santeri Puranen

Message passing equations yield a sharp percolation transition in finite graphs, as an artifact of the locally treelike approximation. For an arbitrary finite, connected, undirected graph we construct an infinite tree having the same local…

Disordered Systems and Neural Networks · Physics 2017-05-03 Gábor Timár , Rui A. da Costa , Sergey N. Dorogovtsev , José F. F. Mendes

We investigate relations between loop and tree amplitudes in quantum field theory that involve putting on-shell some loop propagators. This generalizes the so-called Feynman tree theorem which is satisfied at 1-loop. Exploiting retarded…

High Energy Physics - Phenomenology · Physics 2011-05-23 Simon Caron-Huot

We consider a general interacting particle system with interactions on a random graph, and study the large population limit of this system. When the sequence of underlying graphs converges to a graphon, we show convergence of the…

Probability · Mathematics 2024-10-16 Carla Crucianelli , Ludovic Tangpi

We study high-dimensional sparse estimation under three natural constraints: communication constraints, local privacy constraints, and linear measurements (compressive sensing). Without sparsity assumptions, it has been established that…

Data Structures and Algorithms · Computer Science 2022-03-15 Jayadev Acharya , Clément L. Canonne , Ziteng Sun , Himanshu Tyagi

We study locally interacting processes in discrete time, often called probabilistic cellular automata, indexed by locally finite graphs. For infinite regular trees and certain generalized Galton-Watson trees, we show that the marginal…

Probability · Mathematics 2025-10-28 Daniel Lacker , Kavita Ramanan , Ruoyu Wu

Recently, researchers have demonstrated that loopy belief propagation - the use of Pearls polytree algorithm IN a Bayesian network WITH loops OF error- correcting codes.The most dramatic instance OF this IS the near Shannon - limit…

Artificial Intelligence · Computer Science 2013-01-30 Kevin Murphy , Yair Weiss , Michael I. Jordan

We study tree approximations to classical two-body partition functions on sparse and loopy graphs via the Brydges-Kennedy-Abdessalam-Rivasseau forest expansion. We show that for sparse graphs (with large cycles), the partition function…

Combinatorics · Mathematics 2024-02-08 Francesco Caravelli

We study spin-1/2 fermions in spin dependent potentials under the \emph{spin model approximation}, in which interatomic collisions that change the total occupation of single-particle modes are ignored. The spin model approximation maps the…

Quantum Gases · Physics 2020-09-02 Michael L. Wall

We extend random matrix theory to consider randomly interacting spin systems with spatial locality. We develop several methods by which arbitrary correlators may be systematically evaluated in a limit where the local Hilbert space dimension…

Statistical Mechanics · Physics 2020-01-08 Siddhardh C. Morampudi , Chris R. Laumann

Whether a system is to be considered complex or not depends on how one searches for correlations. We propose a general scheme for calculation of entropies in lattice systems that has high flexibility in how correlations are successively…

Statistical Mechanics · Physics 2015-06-18 Torbjørn Helvik , Kristian Lindgren

We have developed an efficient simulation algorithm for strongly interacting relativistic fermions in two-dimensional field theories based on a formulation as a loop gas. The loop models describing the dynamics of the fermions can be mapped…

High Energy Physics - Lattice · Physics 2009-11-05 Urs Wenger

We propose an experimentally realizable quantum spin model that exhibits fast scrambling, based on non-local interactions which couple sites whose separation is a power of 2. By controlling the relative strengths of deterministic,…

Many iterative and non-iterative methods have been developed for inverse problems associated with Ising models. Aiming to derive an accurate non-iterative method for the inverse problems, we employ the tree-reweighted approximation. Using…

Machine Learning · Statistics 2018-05-30 Takashi Sano

The models in statistical physics such as an Ising model offer a convenient way to characterize stationary activity of neural populations. Such stationary activity of neurons may be expected for recordings from in vitro slices or…

Neurons and Cognition · Quantitative Biology 2017-05-05 Christian Donner , Klaus Obermayer , Hideaki Shimazaki

We derive exact equations that determine the spectra of undirected and directed sparsely connected regular graphs containing loops of arbitrary length. The implications of our results to the structural and dynamical properties of networks…

Statistical Mechanics · Physics 2011-12-07 F. L. Metz , I. Neri , D. Bollé

Belief Propagation (BP) is one of the most popular methods for inference in probabilistic graphical models. BP is guaranteed to return the correct answer for tree structures, but can be incorrect or non-convergent for loopy graphical…

Artificial Intelligence · Computer Science 2012-06-22 Siamak Ravanbakhsh , Chun-Nam Yu , Russell Greiner

A variant of coupled-cluster theory is described here, wherein the degrees of freedom are fluctuations of fragments between internally correlated states. The effects of intra-fragment correlation on the inter-fragment interaction are…

Chemical Physics · Physics 2019-05-24 Yuhong Liu , Anthony D. Dutoi

Consider an interacting particle system indexed by the vertices of a (possibly random) locally finite graph whose vertices and edges are equipped with marks representing parameters of the model such as the environment and initial…

Probability · Mathematics 2024-07-31 Ankan Ganguly , Kavita Ramanan

We introduce Tree-AMP, standing for Tree Approximate Message Passing, a python package for compositional inference in high-dimensional tree-structured models. The package provides a unifying framework to study several approximate message…

Machine Learning · Statistics 2023-04-19 Antoine Baker , Benjamin Aubin , Florent Krzakala , Lenka Zdeborová