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A disordered spin glass model where both static and dynamical properties depend on macroscopic magnetizations is presented. These magnetizations interact via random couplings and, therefore, the typical quenched realization of the system…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Pasquini , M. Serva

We propose a general framework for solving statistical mechanics of systems with finite size. The approach extends the celebrated variational mean-field approaches using autoregressive neural networks, which support direct sampling and…

Statistical Mechanics · Physics 2019-06-10 Dian Wu , Lei Wang , Pan Zhang

We study inverse problems of reconstructing static and dynamic discrete structures from tomographic data (with a special focus on the `classical' task of reconstructing finite point sets in $\mathbb{R}^d$). The main emphasis is on recent…

Data Structures and Algorithms · Computer Science 2018-11-08 Andreas Alpers , Peter Gritzmann

We introduce a variational method for the approximation of ground states of strongly interacting spin systems in arbitrary geometries and spatial dimensions. The approach is based on weighted graph states and superpositions thereof. These…

Quantum Physics · Physics 2007-05-23 S. Anders , M. B. Plenio , W. Dür , F. Verstraete , H. -J. Briegel

In this paper we review recent work on novel computing paradigms using coupled oscillatory dynamical systems. We explore systems of relaxation oscillators based on linear state transitioning devices, which switch between two discrete states…

Emerging Technologies · Computer Science 2016-08-22 Abhinav Parihar , Nikhil Shukla , Matthew Jerry , Suman Datta , Arijit Raychowdhury

Variational autoencoders employ an encoding neural network to generate a probabilistic representation of a data set within a low-dimensional space of latent variables followed by a decoding stage that maps the latent variables back to the…

Statistical Mechanics · Physics 2022-04-13 David Yevick

We study large networks of parametric oscillators as heuristic solvers of random Ising models. In these networks, known as coherent Ising machines, the model to be solved is encoded in the coupling between the oscillators, and a solution is…

Statistical Mechanics · Physics 2021-04-12 Marcello Calvanese Strinati , Leon Bello , Emanuele G. Dalla Torre , Avi Pe'er

Computation with the Ising model is central to future computing technologies like quantum annealing, adiabatic quantum computing, and thermodynamic classical computing. Traditionally, computed values have been equated with ground states.…

Disordered Systems and Neural Networks · Physics 2025-11-04 Andrew G. Moore

We investigate an oscillator linearly coupled with a one-dimensional Ising system. The coupling gives rise to drastic changes both in the oscillator statics and dynamics. Firstly, there appears a second order phase transition, with the…

Statistical Mechanics · Physics 2015-05-27 A. Prados , L. L. Bonilla , A. Carpio

We propose a quantum optical implementation of a class of dissipative spin systems, including the XXZ and Ising model, with ultra-cold atoms in optical lattices. Employing the motional degree of freedom of the atoms and detuned Raman…

Quantum Physics · Physics 2013-02-18 Heike Schwager , J. Ignacio Cirac , Géza Giedke

To investigate novel aspects of pattern formation in spin systems, we use a mapping between reactive concentrations in a reaction-diffusion system and spin orientations in a dynamic multiple-spin Ising model. While pattern formation in…

Adaptation and Self-Organizing Systems · Physics 2019-10-15 Mélody Merle , Laura Messio , Julien Mozziconacci

Many important challenges in science and technology can be cast as optimization problems. When viewed in a statistical physics framework, these can be tackled by simulated annealing, where a gradual cooling procedure helps search for…

Disordered Systems and Neural Networks · Physics 2024-01-17 Mohamed Hibat-Allah , Estelle M. Inack , Roeland Wiersema , Roger G. Melko , Juan Carrasquilla

In this paper, a method for Automatic Image Registration (AIR) through histogram is proposed. Automatic image registration is one of the crucial steps in the analysis of remotely sensed data. A new acquired image must be transformed, using…

Computer Vision and Pattern Recognition · Computer Science 2014-02-25 V. Karthikeyan

We study the 2-dimensional Ising model at critical temperature on a simply connected subset $\Omega_{\delta}$ of the square grid $\delta\mathbb{Z}^{2}$. The scaling limit of the critical Ising model is conjectured to be described by…

Mathematical Physics · Physics 2018-11-26 Reza Gheissari , Clément Hongler , S. C. Park

The aim of this paper is to establish a nonlinear variational approach to the reconstruction of moving density images from indirect dynamic measurements. Our approach is to model the dynamics as a hyperelastic deformation of an initial…

Numerical Analysis · Mathematics 2015-12-01 Martin Burger , Jan Modersitzki , Sebastian Suhr

Reducing acquisition time is a crucial challenge for many imaging techniques. Compressed Sensing (CS) theory offers an appealing framework to address this issue since it provides theoretical guarantees on the reconstruction of sparse…

Applications · Statistics 2014-07-17 Nicolas Chauffert , Philippe Ciuciu , Jonas Kahn , Pierre Weiss

We introduce a new variational approach to the stationary state of kinetic Ising-like models. The approach is based on the cluster expansion of the entropy term appearing in a functional which is minimized by the system history. We rederive…

Statistical Mechanics · Physics 2013-07-26 Alessandro Pelizzola

In this paper we study the inference of the kinetic Ising model on sparse graphs by the decimation method. The decimation method, which was first proposed in [Phys. Rev. Lett. 112, 070603] for the static inverse Ising problem, tries to…

Disordered Systems and Neural Networks · Physics 2016-06-30 Aurélien Decelle , Pan Zhang

Continuous-domain visual signals are usually captured as discrete (digital) images. This operation is not invertible in general, in the sense that the continuous-domain signal cannot be exactly reconstructed based on the discrete image,…

Information Theory · Computer Science 2016-01-20 Mitra Fatemi , Arash Amini , Loic Baboulaz , Martin Vetterli

A coherent Ising machine (CIM) is a network of optical parametric oscillators (OPOs), in which the "strongest" collective mode of oscillation at well above threshold corresponds to an optimum solution of a given Ising problem. When a pump…

Quantum Physics · Physics 2020-10-28 Y. Yamamoto , T. Leleu , S. Ganguli , H. Mabuchi