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We study the wave function localization properties in a d-dimensional model of randomly spaced particles with isotropic hopping potential depending solely on Euclidean interparticle distances. Due to the generality of this model usually…

Disordered Systems and Neural Networks · Physics 2020-04-01 A. G. Kutlin , I. M. Khaymovich

From benign overfitting in overparameterized models to rich power-law scalings in performance, simple ridge regression displays surprising behaviors sometimes thought to be limited to deep neural networks. This balance of phenomenological…

Machine Learning · Statistics 2026-05-08 Alexander Atanasov , Jacob A. Zavatone-Veth , Cengiz Pehlevan

Recurrent Neural Networks (RNNs) are widely used for modelling neural activity, yet the mathematical interplay of core procedures is used to analyze them (temporal rescaling, discretization, and linearization) remain uncharacterized. This…

Neural and Evolutionary Computing · Computer Science 2025-04-08 Mariano Caruso , Cecilia Jarne

We present a linear stability analysis of stationary states (or fixed points) in large dynamical systems defined on random directed graphs with a prescribed distribution of indegrees and outdegrees. We obtain two remarkable results for such…

Statistical Mechanics · Physics 2024-05-22 Izaak Neri , Fernando Lucas Metz

This paper studies countable systems of linearly and hierarchically interacting diffusions taking values in the positive quadrant. These systems arise in population dynamics for two types of individuals migrating between and interacting…

Probability · Mathematics 2007-09-09 Don A. Dawson , Andreas Greven , Frank den Hollander , Rongfeng Sun , Jan M. Swart

We study random two-dimensional spanning forests in the plane that can be viewed both in the discrete case and in their appropriately taken scaling limits as a uniformly chosen spanning tree with some Poissonian deletion of edges or points.…

Probability · Mathematics 2020-08-04 Stéphane Benoist , Laure Dumaz , Wendelin Werner

Non-perturbative renormalisation of a general class of scalar field theories is performed at the Hartree level truncation of the 2PI effective action in the broken symmetry regime. Renormalised equations are explicitly constructed for the…

High Energy Physics - Phenomenology · Physics 2008-11-26 G. Fejos , A. Patkos , Zs. Szep

In this paper, we present a new framework to obtain tail inequalities for sums of random matrices. Compared with existing works, our tail inequalities have the following characteristics: 1) high feasibility--they can be used to study the…

Machine Learning · Computer Science 2019-10-10 Chao Zhang , Min-Hsiu Hsieh , Dacheng Tao

By analyzing the real space nonequilibrium dynamics of polymers, we elucidate the physics of driven translocation and propose its dynamical scaling scenario analogous to that in the surface growth phenomena. We provide a detailed account of…

Soft Condensed Matter · Physics 2011-11-28 Takuya Saito , Takahiro Sakaue

In part I and II of this series of papers all elements have been introduced to extend, to two loops, the set of renormalization procedures which are needed in describing the properties of a spontaneously broken gauge theory. In this paper,…

High Energy Physics - Phenomenology · Physics 2008-11-26 S. Actis , G. Passarino

Motivated by the empirical observation of power-law distributions in the credits (e.g., ``likes'') of viral posts in social media, we introduce a high-dimensional tail index regression model and propose methods for estimation and inference…

Machine Learning · Statistics 2026-01-19 Yuya Sasaki , Jing Tao , Yulong Wang

Variational inference with normalizing flows (NFs) is an increasingly popular alternative to MCMC methods. In particular, NFs based on coupling layers (Real NVPs) are frequently used due to their good empirical performance. In theory,…

Machine Learning · Statistics 2024-02-27 Daniel Andrade

The density of states of Dirac fermions with a random mass on a two-dimensional lattice is considered. We give the explicit asymptotic form of the single-electron density of states as a function of both energy and (average) Dirac mass, in…

Mesoscale and Nanoscale Physics · Physics 2017-09-27 Simon Villain-Guillot , Giancarlo Jug , Klaus Ziegler

We explore training deep neural network models in conjunction with physics simulations via partial differential equations (PDEs), using the simulated degrees of freedom as latent space for a neural network. In contrast to previous work,…

Machine Learning · Computer Science 2023-10-04 Chloe Paliard , Nils Thuerey , Kiwon Um

A commonly used perturbative method for computing large-scale clustering of tracers of mass density, like galaxies, is to model the tracer density field as a Taylor series in the local smoothed mass density fluctuations, possibly adding a…

Astrophysics · Physics 2014-10-13 Patrick McDonald

We study the time evolution of perturbations in spatially extended chaotic systems in the presence of quenched disorder. We find that initially random perturbations tend to exponentially localize in space around static pinning centers that…

Statistical Mechanics · Physics 2009-11-13 Ivan G. Szendro , Juan M. Lopez , Miguel A. Rodriguez

Using the density matrix renormalization group, we study the possibility of real space checkerboard patterns arising as the ground states of the t-J model. We find that checkerboards with a commensurate (pi,pi) background are not low energy…

Strongly Correlated Electrons · Physics 2009-11-10 Steven R. White , D. J. Scalapino

In these lecture notes, which are based on the mini-course given at 2013 Prague School on Mathematical Statistical Physics, we discuss ballistic phase of quenched and annealed stretched polymers in random environment on ${\mathbb Z}^d$ with…

Probability · Mathematics 2014-12-02 Dmitry Ioffe

We develop a formalism for mapping the exact dynamics of an ensemble of disordered quantum systems onto the dynamics of a single particle propagating along a semi-infinite lattice, with parameters determined by the probability distribution…

Quantum Physics · Physics 2026-03-17 Hallmann Óskar Gestsson , Charlie Nation , Alexandra Olaya-Castro

We present a minimal dynamical model for randomly branched isotropic polymers, and we study this model in the framework of renormalized field theory. For the swollen phase, we show that our model provides a route to understand the well…

Statistical Mechanics · Physics 2015-05-27 Hans-Karl Janssen , Olaf Stenull
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