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This thesis is an attempt to provide a new outlook on complex systems, as well as some physical answers for certain models, taking a computational approach. We have focused on disordered systems, addressing two traditional problems in three…

Disordered Systems and Neural Networks · Physics 2011-11-02 D. Yllanes

We develop a multiscale approach to estimate high-dimensional probability distributions from a dataset of physical fields or configurations observed in experiments or simulations. In this way we can estimate energy functions (or…

Statistical Mechanics · Physics 2024-12-24 Tanguy Marchand , Misaki Ozawa , Giulio Biroli , Stéphane Mallat

Rerandomization is an experimental design technique that repeatedly randomizes treatment assignments until covariates are balanced between treatment groups. Rerandomization in the design stage of an experiment can lead to many asymptotic…

Methodology · Statistics 2026-04-10 Antônio Carlos Herling Ribeiro Junior

Domain walls in magnets, vortex lattices in superconductors, contact lines at depinning, and many other systems can be modelled as an elastic system subject to quenched disorder. Its field theory possesses a well-controlled perturbative…

Disordered Systems and Neural Networks · Physics 2022-08-16 Kay Joerg Wiese

In this thesis I discuss analytical approaches to disordered systems using field theory. Disordered systems are characterized by a random energy landscape due to heterogeneities, which remains fixed on the time scales of the phenomena…

Disordered Systems and Neural Networks · Physics 2013-12-30 Alexander Dobrinevski

We investigate the 3-dimensional Edwards-Anderson spin glass model at low temperature on simple cubic lattices of sizes up to L=12. Our findings show a strong continuity among T>0 physical features and those found previously at T=0, leading…

Disordered Systems and Neural Networks · Physics 2009-11-07 E. Marinari , O. C. Martin , F. Zuliani

While model order reduction is a promising approach in dealing with multi-scale time-dependent systems that are too large or too expensive to simulate for long times, the resulting reduced order models can suffer from instabilities. We have…

Fluid Dynamics · Physics 2022-06-08 Jacob Price , Brek Meuris , Madelyn Shapiro , Panos Stinis

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

The renormalization group (RG) constitutes a fundamental framework in modern theoretical physics. It allows the study of many systems showing states with large-scale correlations and their classification in a relatively small set of…

Statistical Mechanics · Physics 2024-09-04 Guido Caldarelli , Andrea Gabrielli , Tommaso Gili , Pablo Villegas

To study the localization of random heteropolymers at an interface separating two selective solvents within the model of Garel, Huse, Leibler and Orland, Europhys. Lett. {\bf 8} 9 (1989), we propose an approach based on a disorder-dependent…

Condensed Matter · Physics 2015-06-25 Cecile Monthus

Renormalisation group (RG) methods provide one of the most important techniques for analysing the physics of many-body systems, both analytically and numerically. By iterating an RG map, which "course-grains" the description of a many-body…

Quantum Physics · Physics 2022-12-26 James D. Watson , Emilio Onorati , Toby S. Cubitt

Using a new approximate strong-randomness renormalization group (RG), we study the many-body localized (MBL) phase and phase transition in one-dimensional quantum systems with short-range interactions and quenched disorder. Our RG is built…

Statistical Mechanics · Physics 2019-06-25 Alan Morningstar , David A. Huse

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

In systems characterized by a rough potential energy landscape, local energetic minima and saddles define a network of metastable states whose topology strongly influences the dynamics. Changes in temperature, causing the merging and…

Soft Condensed Matter · Physics 2009-07-24 Marco Baiesi , Lorenzo Bongini , Lapo Casetti , Lorenzo Tattini

In this article, we review basic facts about disordered systems, especially the existence of many metastable states and and the resulting failure of dimensional reduction. Besides techniques based on the Gaussian variational method and…

Condensed Matter · Physics 2007-05-23 Kay Joerg Wiese

This paper develops a new approach to the estimation of the degree of boundedness or stability of multidimensional nonlinear systems with time-dependent nonperiodic coefficients-an essential task in various engineering and natural science…

Dynamical Systems · Mathematics 2022-06-16 Mark A. Pinsky

The Renormalization Group (RG) is a set of methods that have been instrumental in tackling problems involving an infinite number of degrees of freedom. What all these methods have in common -- which is what explains their success -- is that…

Statistical Mechanics · Physics 2020-04-30 Pedro Pessoa , Ariel Caticha

The ability of entanglement renormalization (ER) to generate a proper real-space renormalization group (RG) flow in extended quantum systems is analysed in the setting of harmonic lattice systems in D=1 and D=2 spatial dimensions. A…

Quantum Physics · Physics 2010-03-05 G. Evenbly , G. Vidal

A key problem in making precise perturbative QCD predictions is to set the proper renormalization scale of the running coupling. The conventional scale-setting procedure assigns an arbitrary range and an arbitrary systematic error to…

High Energy Physics - Phenomenology · Physics 2013-07-15 Xing-Gang Wu , Stanley J. Brodsky , Matin Mojaza

We propose a novel framework for approximating the statistical properties of turbulent flows by combining variational methods for the search of unstable periodic orbits with resolvent analysis for dimensionality reduction. Traditional…

Chaotic Dynamics · Physics 2025-01-22 Thomas Burton , Sean Symon , Ati Sharma , Davide Lasagna