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Related papers: Bethe states of random factor graphs

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We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its Bethe approximation. We show that there exists a regime of…

Machine Learning · Computer Science 2012-02-20 Uri Heinemann , Amir Globerson

We derive the classical Gibbs measure on $\mathbb{T}^2$ associated with the fractional Bessel interaction potential $\widehat{v}_\beta(k)=\langle k\rangle^{-\beta}$ from a renormalized grand-canonical quantum Bose gas with the same…

Mathematical Physics · Physics 2026-04-24 Phan Thành Nam , Rongchan Zhu , Xiangchan Zhu

In some applied scenarios, the availability of complete data is restricted, often due to privacy concerns; only aggregated, robust and inefficient statistics derived from the data are made accessible. These robust statistics are not…

Methodology · Statistics 2024-02-23 Antoine Luciano , Christian P. Robert , Robin J. Ryder

A key insight from statistical physics about spin systems on random graphs is the central role played by Gibbs measures on trees. We determine the local weak limit of the hardcore model on random regular graphs asymptotically until just…

Probability · Mathematics 2014-05-26 Nayantara Bhatnagar , Allan Sly , Prasad Tetali

Measurement based (MB) quantum computation allows for universal quantum computing by measuring individual qubits prepared in entangled multipartite states, known as graph states. Unless corrected for, the randomness of the measurements…

Quantum Physics · Physics 2018-02-28 Rawad Mezher , Joe Ghalbouni , Joseph Dgheim , Damian Markham

We consider Gibbs distributions, which are families of probability distributions over a discrete space $\Omega$ with probability mass function of the form $\mu^\Omega_\beta(\omega) \propto e^{\beta H(\omega)}$ for $\beta$ in an interval…

Data Structures and Algorithms · Computer Science 2025-04-04 David G. Harris , Vladimir Kolmogorov

We consider polynomial long-range Ising models in one dimension, with ferromagnetic pair interactions decaying with power $2-\alpha$ (for $0 \leq \alpha < 1$), and prepared with randomly chosen boundary conditions. We show that at low…

Mathematical Physics · Physics 2024-05-17 Eric O. Endo , Aernout C. D. van Enter , Arnaud Le Ny

We first present an empirical study of the Belief Propagation (BP) algorithm, when run on the random field Ising model defined on random regular graphs in the zero temperature limit. We introduce the notion of maximal solutions for the BP…

Disordered Systems and Neural Networks · Physics 2018-02-01 Gabriele Perugini , Federico Ricci-Tersenghi

The concept of metastate measures on the states of a random spin system was introduced to be able to treat the large-volume asymptotics for complex quenched random systems, like spin glasses, which may exhibit chaotic volume dependence in…

Probability · Mathematics 2018-12-19 Codina Cotar , Benedikt Jahnel , Christof Külske

Consider a classical system, which is in the state described by probability distribution $p$ or $q$, and embed these classical informations into quantum system by a physical map $\Gamma$, $\rho=\Gamma(p)$ and $\sigma=\Gamma(q)$.…

Quantum Physics · Physics 2025-07-03 Keiji Matsumoto

A scheme to provide various mean-field-type approximation algorithms is presented by employing the Bethe free energy formalism to a family of replicated systems in conjunction with analytical continuation with respect to the number of…

Disordered Systems and Neural Networks · Physics 2009-11-11 Yoshiyuki Kabashima

When belief propagation (BP) converges, it does so to a stationary point of the Bethe free energy $F$, and is often strikingly accurate. However, it may converge only to a local optimum or may not converge at all. An algorithm was recently…

Machine Learning · Computer Science 2014-01-03 Adrian Weller , Tony Jebara

This paper considers a non-standard problem of generating samples from a low-temperature Gibbs distribution with \emph{constrained} support, when some of the coordinates of the mode lie on the boundary. These coordinates are referred to as…

Statistics Theory · Mathematics 2026-02-27 Ruixiao Wang , Xiaohong Chen , Sinho Chewi

A statistical system is classically defined on a set of microstates $E$ by a global energy function $H : E \to \mathbb{R}$, yielding Gibbs probability measures (softmins) $\rho^\beta(H)$ for every inverse temperature $\beta = T^{-1}$. Gibbs…

Statistical Mechanics · Physics 2022-07-05 Olivier Peltre

We consider the problem of computing the overlaps between the Bethe states of the XXZ spin-1/2 chain and generic states. We derive recursive formulas for the overlaps between some simple product states and off-shell Bethe states within the…

Statistical Mechanics · Physics 2016-04-28 Lorenzo Piroli , Pasquale Calabrese

We present a combinatorial characterization of the Bethe entropy function of a factor graph, such a characterization being in contrast to the original, analytical, definition of this function. We achieve this combinatorial characterization…

Information Theory · Computer Science 2013-11-05 Pascal O. Vontobel

We consider homogeneous factor models on uniformly sparse graph sequences converging locally to a (unimodular) random tree $T$, and study the existence of the free energy density $\phi$, the limit of the log-partition function divided by…

Probability · Mathematics 2013-12-17 Amir Dembo , Andrea Montanari , Nike Sun

The algebraic Bethe Ansatz is a prosperous and well-established method for solving one-dimensional quantum models exactly. The solution of the complex eigenvalue problem is thereby reduced to the solution of a set of algebraic equations.…

Strongly Correlated Electrons · Physics 2012-07-23 Valentin Murg , Vladimir E. Korepin , Frank Verstraete

We construct Gibbs perturbations of the Gamma process on $\mathbbm{R}^d$, which may be used in applications to model systems of densely distributed particles. First we propose a definition of Gibbs measures over the cone of discrete Radon…

Mathematical Physics · Physics 2012-07-13 Dennis Hagedorn , Yuri Kondratiev , Tanja Pasurek , Michael Röckner

Many real-world networks of interest are embedded in physical space. We present a new random graph model aiming to reflect the interplay between the geometries of the graph and of the underlying space. The model favors configurations with…

Probability · Mathematics 2017-06-14 Jean-Christophe Mourrat , Daniel Valesin