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We prove convergence of the 2- and 4-point fermionic observables of the FK-Ising model on simply connected domains discretised by a planar isoradial lattice in massive (near-critical) scaling limit. The former is alternatively known as a…

Probability · Mathematics 2022-09-21 S. C. Park

Scale invariance is a central organizing principle in physics, underlying phenomena that range from critical behaviour in statistical mechanics to transport and chaos in nonlinear dynamical systems. Here we present a unified and physically…

Statistical Mechanics · Physics 2026-02-23 Edson D. Leonel , Diego F. M. Oliveira

If we have a system of binary variables and we measure the pairwise correlations among these variables, then the least structured or maximum entropy model for their joint distribution is an Ising model with pairwise interactions among the…

Disordered Systems and Neural Networks · Physics 2014-09-12 Michele Castellana , William Bialek

We study the accuracy and predictive power of conformal perturbation theory by a comparison with lattice results in the neighborhood of the finite-temperature deconfinement transition of SU(2) Yang-Mills theory, assuming that the infrared…

High Energy Physics - Lattice · Physics 2019-09-05 Michele Caselle , Nicodemo Magnoli , Alessandro Nada , Marco Panero , Marcello Scanavino

A solid is typically deemed amorphous when there are no Bragg peaks in its diffraction pattern. We discuss a two dimensional configuration of Ising spins with an autocorrelation function which vanishes at all nonzero distances, so that its…

Disordered Systems and Neural Networks · Physics 2015-06-15 Gil Wolff , Dov Levine

The correlation function of the two dimensional Ising model with the nearest neighbours interaction on the finite size lattice with the periodical boundary conditions is derived. The expressions similar to the form factor expansion are…

High Energy Physics - Theory · Physics 2007-05-23 A. I. Bugrij

Motivated in part by quantum criticality in dissipative Kondo systems, we revisit the finite-size scaling of a classical Ising chain with 1/r^{2-epsilon} interactions. For 1/2<epsilon<1, the scaling of the dynamical spin susceptibility is…

Strongly Correlated Electrons · Physics 2009-04-24 Stefan Kirchner , Qimiao Si , Kevin Ingersent

We give an explicit example of a model in D=4-epsilon space-time dimensions that is scale but not conformally invariant, is unitary, and has finite correlators. The invariance is associated with a limit cycle renormalization group (RG)…

High Energy Physics - Theory · Physics 2015-09-14 Jean-François Fortin , Benjamín Grinstein , Andreas Stergiou

We investigate the critical behaviour of the two-dimensional Ising model defined on a curved surface with a constant negative curvature. Finite-size scaling analysis reveals that the critical exponents for the zero-field magnetic…

Statistical Mechanics · Physics 2009-11-11 Hiroyuki Shima , Yasunori Sakaniwa

Conformal prediction uses past experience to determine precise levels of confidence in new predictions. Given an error probability $\epsilon$, together with a method that makes a prediction $\hat{y}$ of a label $y$, it produces a set of…

Machine Learning · Computer Science 2019-04-23 Glenn Shafer , Vladimir Vovk

Building on an analogy with conformal invariance, local scale transformations consistent with dynamical scaling are constructed. Two types of local scale invariance are found which act as dynamical space-time symmetries of certain non-local…

Statistical Mechanics · Physics 2007-05-23 Malte Henkel

We consider Ising model on edge-dual of uncorrelated random networks with arbitrary degree distribution. These networks have a finite clustering in the thermodynamic limit. High and low temperature expansions of Ising model on the edge-dual…

Disordered Systems and Neural Networks · Physics 2009-11-10 A. Ramezanpour

Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in learning the presumably sparse network structure of the…

Machine Learning · Computer Science 2019-07-09 Frank Nussbaum , Joachim Giesen

We consider discrete random fractal surfaces with negative Hurst exponent $H<0$. A random colouring of the lattice is provided by activating the sites at which the surface height is greater than a given level $h$. The set of activated sites…

Statistical Mechanics · Physics 2020-10-14 Nina Javerzat , Sebastian Grijalva , Alberto Rosso , Raoul Santachiara

Using combinatorial optimisation techniques we study the critical properties of the two- and the three-dimensional Ising model with uniformly distributed random antiferromagnetic couplings $(1 \le J_i \le 2)$ in the presence of a…

Disordered Systems and Neural Networks · Physics 2022-06-08 Jean-Christian Anglès d'Auriac , Ferenc Iglói

Conformal field theory predicts finite-size scaling amplitudes of correlation lengths universally related to critical exponents on sphere-like, semi-finite systems $S^{d-1}\times\mathbb{R}$ of arbitrary dimensionality $d$. Numerical studies…

Statistical Mechanics · Physics 2009-10-31 Martin Weigel , Wolfhard Janke

Statistical mechanics describes interaction between particles of a physical system. Particle properties of the system can be modelled with a random field on a lattice and studied at different distance scales using renormalization group…

Probability · Mathematics 2015-04-29 Farida Kachapova , Ilias Kachapov

In this paper, we consider the set of interfaces between + and - spins arising for the critical planar Ising model on a domain with + boundary conditions, and show that it converges towards CLE(3). Our proof relies on the study of the…

Probability · Mathematics 2018-07-24 Stéphane Benoist , Clément Hongler

We present a novel theory of the very early universe which addresses the traditional horizon and flatness problems of big bang cosmology and predicts a scale invariant spectrum of perturbations. Unlike inflation, this scenario requires no…

High Energy Physics - Theory · Physics 2012-04-24 Kurt Hinterbichler , Justin Khoury

Conformal prediction is a popular, modern technique for providing valid predictive inference for arbitrary machine learning models. Its validity relies on the assumptions of exchangeability of the data, and symmetry of the given model…

Methodology · Statistics 2023-03-20 Rina Foygel Barber , Emmanuel J. Candes , Aaditya Ramdas , Ryan J. Tibshirani
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