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In this paper, we propose a new technique for two-dimensional phase unwrapping. The unwrapped phase is found as the solution of an inverse problem that consists in the minimization of an energy functional. The latter includes a weighted…

In this work we explain how to properly use mean-field methods to solve the inverse Ising problem when the phase space is clustered, that is many states are present. The clustering of the phase space can occur for many reasons, e.g. when a…

Disordered Systems and Neural Networks · Physics 2016-07-20 Aurélien Decelle , Federico Ricci-Tersenghi

Some types of medical and topographic imaging device produce images in which the pixel values are "phase-wrapped", i.e. measured modulus a known scalar. Phase unwrapping can be viewed as the problem of inferring the number of shifts between…

Computer Vision and Pattern Recognition · Computer Science 2013-01-14 Kannan Achan , Brendan J. Frey , Ralf Koetter

Correlation functions in one-dimensional complex scalar field theory provide a toy model for phase fluctuations, sign problems, and signal-to-noise problems in lattice field theory. Phase unwrapping techniques from signal processing are…

High Energy Physics - Lattice · Physics 2018-11-12 William Detmold , Gurtej Kanwar , Michael L. Wagman

Finding an energy minimum in the Ising model is an exemplar objective, associated with many combinatorial optimization problems, that is computationally hard in general, but occurs in all areas of modern science. There are several numerical…

Quantum Physics · Physics 2019-07-17 A. Yavorsky , L. A. Markovich , E. A. Polyakov , A. N. Rubtsov

Phase unwrapping is the process of recovering a continuous phase signal from an original signal wrapped in the ($-\pi$,$\pi$] interval. It is a critical step of coherent signal processing, with applications such as synthetic aperture radar,…

Signal Processing · Electrical Eng. & Systems 2019-06-03 Ian Herszterg , Marcus Poggi , Thibaut Vidal

Surface-consistent deconvolution is a standard processing technique in land data to uniformize the wavelet across all sources and receivers. The required wavelet estimation step is generally done in the homomorphic domain since this is a…

Information Theory · Computer Science 2012-09-18 Roberto H. Herrera , Mirko van der Baan

A mean field feedback artificial neural network algorithm is developed and explored for the set covering problem. A convenient encoding of the inequality constraints is achieved by means of a multilinear penalty function. An approximate…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Mattias Ohlsson , Carsten Peterson , Bo Söderberg

Sign problems in path integrals arise when different field configurations contribute with different signs or phases. Phase unwrapping describes a family of signal processing techniques in which phase differences between elements of a time…

High Energy Physics - Lattice · Physics 2018-10-31 William Detmold , Gurtej Kanwar , Michael L. Wagman

The large amounts of data from molecular biology and neuroscience have lead to a renewed interest in the inverse Ising problem: how to reconstruct parameters of the Ising model (couplings between spins and external fields) from a number of…

Disordered Systems and Neural Networks · Physics 2012-08-13 H. Chau Nguyen , Johannes Berg

Phase unwrapping remains a critical and challenging problem in InSAR processing, particularly in scenarios involving complex deformation patterns. In earthquake-related deformation, shallow sources can generate surface-breaking faults and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yijia Song , Juliet Biggs , Alin Achim , Robert Popescu , Simon Orrego , Nantheera Anantrasirichai

Mean-Field is an efficient way to approximate a posterior distribution in complex graphical models and constitutes the most popular class of Bayesian variational approximation methods. In most applications, the mean field distribution…

Machine Learning · Computer Science 2015-02-23 Pierre Baqué , Jean-Hubert Hours , François Fleuret , Pascal Fua

Phase unwrapping is a key problem in many coherent imaging systems, such as synthetic aperture radar (SAR) interferometry. A general formulation for redundant integration of finite differences for phase unwrapping (Costantini et al., 2010)…

Other Computer Science · Computer Science 2018-05-04 Ravi Lanka

Mean-field theory is an approximation replacing an extended system by a few variables. For depinning of elastic manifolds, these are the position of its center of mass $u$, and the statistics of the forces $F(u)$. There are two proposals to…

Statistical Mechanics · Physics 2022-01-19 Cathelijne ter Burg , Kay Joerg Wiese

The driven transport of plastic systems in various disordered backgrounds is studied within mean field theory. Plasticity is modeled using non-convex interparticle potentials that allow for phase slips. This theory most naturally describes…

Disordered Systems and Neural Networks · Physics 2009-11-10 Karl Saunders , J. M. Schwarz , M. Cristina Marchetti , A. Alan Middleton

Amorphization during severe plastic deformation has been observed in various crystalline materials, yet its underlying mechanisms remain poorly understood. This study introduces a novel phase-field model at the mesoscale, integrating…

Materials Science · Physics 2025-10-10 Yuntong Huang , Shuyang Dai , Chuqi Chen , Yang Xiang

Interferometry can measure the shape or the material density of a system that could not be measured otherwise by recording the difference between the phase change of a signal and a reference phase. This difference is always between $-\pi$…

Plasma Physics · Physics 2022-10-20 Pierre-Alexandre Gourdain , Aidan Bachmann

The 2D phase unwrapping problem seeks to recover a phase image from its observation modulo 2$\pi$, and is a crucial step in a variety of imaging applications. In particular, it is one of the most time-consuming steps in the interferometric…

Optimization and Control · Mathematics 2024-01-19 Benjamin Dubois-Taine , Roland Akiki , Alexandre d'Aspremont

We study a modified mean-field approximation for the Ising Model in arbitrary dimension. Instead of taking a "central" spin, or a small "drop" of fluctuating spins coupled to the effective field of their nearest neighbors as in the…

High Energy Physics - Lattice · Physics 2009-06-09 Cayetano Di Bartolo , Lorenzo Leal

The presence of a bias field, encoding some information about the target state, can enhance the performance of quantum optimization methods. Here we investigate the effect of such a bias field on the outcome of quantum annealing sampling,…

Quantum Physics · Physics 2022-10-19 Tobias Graß
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