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Continuous One-dimensional models supporting extended states are studied. These delocalized statesoccur at well defined values of the energy and are consequences of simple statistical correlation rules. We explicitly study alloys of…

Disordered Systems and Neural Networks · Physics 2009-10-30 M. Hilke , J. C. Flores

We examine probability distributions for thermodynamic quantities in finite-sized random systems close to criticality. Guided by available exact results, a general ansatz is proposed for replicated free energies, which leads to scaling…

Disordered Systems and Neural Networks · Physics 2009-10-31 Thorsten Emig , Mehran Kardar

We study the problem of a random walk on a lattice in which bonds connecting nearest neighbor sites open and close randomly in time, a situation often encountered in fluctuating media. We present a simple renormalization group technique to…

adap-org · Physics 2009-10-22 C. D. Levermore , W. Nadler , D. L. Stein

We critically examine the magnitude of theoretical uncertainties in perturbative calculations of first-order phase transitions, using the Standard Model effective field theory as our guide. In the usual daisy-resummed approach, we find…

High Energy Physics - Phenomenology · Physics 2021-04-14 Djuna Croon , Oliver Gould , Philipp Schicho , Tuomas V. I. Tenkanen , Graham White

We revisit the problem of an elastic line (e.g. a vortex line in a superconductor) subject to both columnar disorder and point disorder in dimension $d=1+1$. Upon applying a transverse field, a delocalization transition is expected, beyond…

Statistical Mechanics · Physics 2022-01-12 Alexandre Krajenbrink , Pierre Le Doussal , Neil O'Connell

Power-law probability distributions are widely used to model extreme statistical events in complex systems, with applications to a vast array of natural phenomena ranging from earthquakes to stock market crashes to pandemics. We show that…

Quantum Physics · Physics 2026-04-08 Wai-Keong Mok

The normal distribution and its perturbation has left an immense mark on the statistical literature. Hence, several generalized forms were developed to model different skewness, kurtosis, and body shapes. However, it is not easy to…

Methodology · Statistics 2019-12-10 Matthias Wagener , Mohammad Arashi

Higher order parametric level correlations in disordered systems with broken time-reversal symmetry are studied by mapping the problem onto a model of coupled Hermitian random matrices. Closed analytical expression is derived for parametric…

Disordered Systems and Neural Networks · Physics 2009-10-31 E. Kanzieper , V. Freilikher

In this review paper, we explain how to apply Renormalization Group ideas to the analysis of the long-time asymptotics of solutions of partial differential equations. We illustrate the method on several examples of nonlinear parabolic…

chao-dyn · Physics 2009-10-22 J. Bricmont , A. Kupiainen

In the present work, we investigate the case of Directed Polymer in a Random Environment (DPRE), when the increments of the random walk are heavy-tailed with tail-exponent equal to zero ($\mathbf{P}[|X_1|\geq n]$ decays slower than any…

Probability · Mathematics 2020-04-01 Roberto Viveros

Renewal processes with heavy-tailed power law distributed sojourn times are commonly encountered in physical modelling and so typical fluctuations of observables of interest have been investigated in detail. To describe rare events the rate…

Statistical Mechanics · Physics 2018-10-26 Wanli Wang , Johannes H. P. Schulz , Weihua Deng , Eli Barkai

We study the dynamics of the one dimensional disordered trap model presenting a broad distribution of trapping times $p(\tau) \sim 1/\tau^{1+\mu}$, when an external force is applied from the very beginning at $t=0$, or only after a waiting…

Condensed Matter · Physics 2009-11-10 Cecile Monthus

Far from equilibrium, neural systems self-organize across multiple scales. Exploiting multiscale self-organization in neuroscience and artificial intelligence requires a computational framework for modeling the effective non-equilibrium…

Neurons and Cognition · Quantitative Biology 2025-10-09 Nathan X. Kodama

The interpretation of redshift surveys requires modeling the relationship between large-scale fluctuations in the observed number density of tracers, $\delta_\mathrm{h}$, and the underlying matter density, $\delta$. Bias models often…

Cosmology and Nongalactic Astrophysics · Physics 2020-01-08 Kim F. Werner , Cristiano Porciani

In many scientific applications, the target probability distribution cannot be evaluated in closed form or sampled from directly. Instead, it can often be decomposed into multiple components, some of which are accessible only through…

Methodology · Statistics 2026-03-10 Roxana Darvishi , David C. Stenning , Ted von Hippel , Owen G. Ward

This paper discusses an approach for incorporating prior physical knowledge into the neural network to improve data efficiency and the generalization of predictive models. If the dynamics of a system approximately follows a given…

Neural and Evolutionary Computing · Computer Science 2020-05-29 Andrei Ivanov , Uwe Iben , Anna Golovkina

We define a hyperbolic renormalizations suitable for maps of small determinant, with uniform bounds for large periods. The techniques involve an improvement of the celebrated Palis-Takens renormalization and normal forms (fibered…

Dynamical Systems · Mathematics 2014-04-09 Pierre Berger

An asymmetric variant of the contact process where the activity spreads with different and independent random rates to the left and to the right is introduced. A real space renormalization scheme is formulated for model by means of which it…

Disordered Systems and Neural Networks · Physics 2013-03-14 Róbert Juhász

In this paper we investigate renormalisation group flows of supersymmetric minimal models generated by the boundary perturbing field (\hat G_{-1/2}\phi_{1,3}). Performing the Truncated Conformal Space Approach analysis the emerging pattern…

High Energy Physics - Theory · Physics 2008-11-26 M. Kormos

We investigate the one-dimensional polaron problem and calculate the ground state energy and the effective mass. We use a real-time renormalization group method and compare our results with first and second order perturbation theory, with…

Statistical Mechanics · Physics 2009-10-31 Markus Keil , Herbert Schoeller