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Geodesic coalescence, or the tendency of geodesics to merge together, is a hallmark phenomenon observed in a variety of planar random geometries involving a random distortion of the Euclidean metric. As a result of this, the union of…

Probability · Mathematics 2024-04-03 Manan Bhatia

We study the KPZ equation with a $1+1-$dimensional spacetime white noise, started at equilibrium, and give a different proof of the main result of \cite{bqs}, i.e., the variance of the solution at time $t$ is of order $t^{2/3}$. Instead of…

Probability · Mathematics 2022-10-27 Yu Gu , Tomasz Komorowski

Stochastic gradient descent (SGD) is one of the most popular algorithms in modern machine learning. The noise encountered in these applications is different from that in many theoretical analyses of stochastic gradient algorithms. In this…

Machine Learning · Statistics 2021-09-16 Stephan Wojtowytsch

The ability of overparameterized deep networks to interpolate noisy data, while at the same time showing good generalization performance, has been recently characterized in terms of the double descent curve for the test error. Common…

Machine Learning · Computer Science 2023-04-11 Matteo Gamba , Erik Englesson , Mårten Björkman , Hossein Azizpour

Discretization of phase space usually nullifies chaos in dynamical systems. We show that if randomness is associated with discretization dynamical chaos may survive and be indistinguishable from that of the original chaotic system, when an…

Chaotic Dynamics · Physics 2009-11-10 M. Falcioni , A. Vulpiani , G. Mantica , S. Pigolotti

We show that the presence of a localized drive in an otherwise diffusive system results in steady-state density and current profiles that decay algebraically to their global average value, away from the drive in two or higher dimensions. An…

Statistical Mechanics · Physics 2014-11-18 Tridib Sadhu , Satya N. Majumdar , David Mukamel

In this paper, we derive several criteria for (weak) synchronization by noise without the global swift transitivity property. Our sufficient conditions for (weak) synchronization are necessary and can be applied to scenarios involving…

Dynamical Systems · Mathematics 2025-12-23 Xianming Liu , Xu Sun

Given two unidirectionally coupled nonlinear systems, we speak of generalized synchronization when the responder \textquotedblleft follows\textquotedblright\ the driver. Mathematically, this situation is implemented by a map from the driver…

Chaotic Dynamics · Physics 2025-02-13 José M. Amigó , Roberto Dale , Juan C. King , Klaus Lehnertz

Disordered solids respond to quasistatic shear with intermittent avalanches of plastic activity, an example of the crackling noise observed in many nonequilibrium critical systems. The temporal power spectrum of activity within disordered…

Soft Condensed Matter · Physics 2021-04-21 Joel T. Clemmer , K. Michael Salerno , Mark O. Robbins

We analyze the dynamics of a two-level system subject to driving by large-amplitude external fields, focusing on the resonance properties in the case of driving around the region of avoided level crossing. In particular, we consider three…

Quantum Physics · Physics 2009-07-17 S. Ashhab , J. R. Johansson , A. M. Zagoskin , Franco Nori

Numerical analysis of conserved field dynamics has been generally performed with pseudo spectral methods. Finite differences integration, the common procedure for non-conserved field dynamics, indeed struggles to implement a conservative…

Statistical Mechanics · Physics 2024-01-29 Andrea Cavagna , Javier Cristín , Irene Giardina , Mario Veca

The loss surface of deep neural networks has recently attracted interest in the optimization and machine learning communities as a prime example of high-dimensional non-convex problem. Some insights were recently gained using spin glass…

Machine Learning · Statistics 2017-06-05 C. Daniel Freeman , Joan Bruna

Score diffusion methods can learn probability densities from samples. The score of the noise-corrupted density is estimated using a deep neural network, which is then used to iteratively transport a Gaussian white noise density to a target…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Zahra Kadkhodaie , Stéphane Mallat , Eero P. Simoncelli

We study the limiting dynamics of a large class of noisy gradient descent systems in the overparameterized regime. In this regime the set of global minimizers of the loss is large, and when initialized in a neighbourhood of this zero-loss…

Machine Learning · Computer Science 2024-04-19 Anna Shalova , André Schlichting , Mark Peletier

We consider the dynamics of strongly localized systems subject to dephasing noise with arbitrary correlation time. Although noise inevitably induces delocalization, transport in the noise-induced delocalized phase is subdiffusive in a…

Disordered Systems and Neural Networks · Physics 2017-07-28 Sarang Gopalakrishnan , K. Ranjibul Islam , Michael Knap

Synchronization is shown to occur in spatially extended systems under the effect of additive spatio-temporal noise. In analogy to low dimensional systems, synchronized states are observable only if the maximum Lyapunov exponent $\Lambda$ is…

chao-dyn · Physics 2016-11-23 L. Baroni , R. Livi , A. Torcini

We study overdamped stochastic dynamics confined by hard reflecting boundaries and show that the combination of boundary geometry and an anisotropic diffusion tensor generically generates directed motion. At the level of individual…

Statistical Mechanics · Physics 2026-01-14 Meitar Goldfarb , Stanislav Burov

The dynamic scaling of curved interfaces presents features that are strikingly different from those of the planar ones. Spherical surfaces above one dimension are flat because the noise is irrelevant in such cases. Kinetic roughening is…

Statistical Mechanics · Physics 2009-11-13 Carlos Escudero

Diffuse scattering of light from disordered assemblies is traditionally viewed as an uncontrollable broadband scattering background resulting in whitish hues. Here, we demonstrate that correlated disorder enables precise engineering of…

The model of directed polymer in a random environment is a fundamental model of interaction between a simple random walk and ambient disorder. This interaction gives rise to complex phenomena and transitions from a central limit theory to…

Probability · Mathematics 2024-09-13 Nikos Zygouras