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We apply a probabilistic approach to study the computational complexity of analog computers which solve linear programming problems. We analyze numerically various ensembles of linear programming problems and obtain, for each of these…

Other Condensed Matter · Physics 2009-11-11 Yaniv Avizrats , Joshua Feinberg , Shmuel Fishman

We explore how minimal neural networks can invert the renormalization group (RG) coarse-graining procedure in the two-dimensional Ising model, effectively ``dreaming up'' microscopic configurations from coarse-grained states. This task -…

Statistical Mechanics · Physics 2026-05-08 Adam Rançon , Ulysse Rançon , Tomislav Ivek , Ivan Balog

The desirability of evaluating the effective potential in field theories near a phase transition has been recognized in a number of different areas. We show that recent Monte Carlo simulations for the probability distribution for the order…

Statistical Mechanics · Physics 2011-05-12 Joseph Rudnick , William Lay , David Jasnow

We propose a new picture of the renormalization group (RG) approach in the presence of disorder, which considers the RG trajectories of each random sample (realization) separately instead of the usual renormalization of the averaged free…

Statistical Mechanics · Physics 2009-10-31 Karim Bernardet , Ferenc Pazmandi , G. G. Batrouni

The Functional Renormalisation Group approach is applied the imbalanced many-fermion systems. The system is found to exhibit the first order phase transition from the superfluid to normal phase when the density (chemical potential) mismatch…

Quantum Gases · Physics 2015-10-20 Boris Krippa

We discuss the order parameter correlation function in the vicinity of continuous phase transitions using a two-parameter scaling form G(k) = k_c^{-2} g(k\xi,k/k_c), where k is the wave-vector, \xi is the correlation length, and the…

Statistical Mechanics · Physics 2008-02-28 Nils Hasselmann , Andreas Sinner , Peter Kopietz

The phenomenological renormalization group (PRG) has been applied to the study of scaleinvariant phenomena in neuronal data, providing evidence for critical phenomena in the brain. However, it remains unclear how reliably these observed…

Disordered Systems and Neural Networks · Physics 2025-06-18 Kaio F. R. Nascimento , Daniel M. Castro , Gustavo G. Cambrainha , Mauro Copelli

The infinite disorder fixed point of the random transverse-field Ising model is expected to control the critical behavior of a large class of random quantum and stochastic systems having an order parameter with discrete symmetry. Here we…

Disordered Systems and Neural Networks · Physics 2015-05-19 Istvan A. Kovacs , Ferenc Igloi

We provide a theoretical analysis by means of the nonperturbative functional renormalization group (NP-FRG) of the corrections to scaling in the critical behavior of the random-field Ising model (RFIM) near the dimension $d_{DR}\approx 5.1$…

Disordered Systems and Neural Networks · Physics 2021-01-04 Ivan Balog , Gilles Tarjus , Matthieu Tissier

Evaluation of likelihood functions for cosmological large scale structure data sets (including CMB, galaxy redshift surveys, etc.) naturally involves marginalization, i.e., integration, over an unknown underlying random signal field.…

Cosmology and Nongalactic Astrophysics · Physics 2019-08-14 Patrick McDonald

We analyse the critical properties of a weakly diluted (random) Ising model with the long-range interaction decaying with distance $x$ as $\sim x^{-d-\sigma}$ in a $d$-dimensional space. It is known to belong to a new long-range random…

Statistical Mechanics · Physics 2025-12-30 D. Shapoval , M. Dudka

The probability distribution of the order parameter is exploited in order to obtain the criticality of magnetic systems. Monte Carlo simulations have been employed by using single spin flip Metropolis algorithm aided by finite-size scaling…

Statistical Mechanics · Physics 2015-06-24 P. H. L. Martins , J. A. Plascak

According to the available publications, the field theoretical renormalization group (RG) approach in the two-dimensional case gives the critical exponents that differ from the known exact values. This fact was attempted to explain by the…

Statistical Mechanics · Physics 2009-11-13 A. A. Pogorelov , I. M. Suslov

In this paper we address the complexity of solving linear programming problems with a set of differential equations that converge to a fixed point that represents the optimal solution. Assuming a probabilistic model, where the inputs are…

Computational Complexity · Computer Science 2007-05-23 Asa Ben-Hur , Joshua Feinberg , Shmuel Fishman , Hava T. Siegelmann

We develop a systematic multi-local expansion of the Polchinski-Wilson exact renormalization group (ERG) equation. Integrating out explicitly the non local interactions, we reduce the ERG equation obeyed by the full interaction functional…

Condensed Matter · Physics 2009-10-31 Pascal Chauve , Pierre Le Doussal

We study by the perturbative Functional Renormalization Group (FRG) the Random Field and Random Anisotropy O(N) models near $d=4$, the lower critical dimension of ferromagnetism. The long-distance physics is controlled by zero-temperature…

Statistical Mechanics · Physics 2009-11-11 Matthieu Tissier , Gilles Tarjus

We present a renormalization group (RG) procedure which works naturally on a wide class of interacting one-dimension models based on perturbed (possibly strongly) continuum conformal and integrable models. This procedure integrates Kenneth…

Strongly Correlated Electrons · Physics 2016-07-05 Robert M. Konik , Yury Adamov

A functional risk curve gives the probability of an undesirable event as a function of the value of a critical parameter of a considered physical system. In several applicative situations, this curve is built using phenomenological…

Statistics Theory · Mathematics 2017-07-26 Bertrand Iooss , Loïc Le Gratiet

We have developed a very efficient numerical algorithm of the strong disorder renormalization group method to study the critical behaviour of the random transverse-field Ising model, which is a prototype of random quantum magnets. With this…

Disordered Systems and Neural Networks · Physics 2011-09-21 István A. Kovács , Ferenc Iglói

Conformal field theory (CFT) is an extremely powerful tool for explicitly computing critical exponents and correlation functions of statistical mechanics systems at a second order phase transition, or of condensed matter systems at a…

Mathematical Physics · Physics 2021-02-23 Alessandro Giuliani