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Related papers: Renormalising SPDEs in regularity structures

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We derive a noise term to account for fluctuation corrections based on the particle system approximation for the n-species Shigesada-Kawasaki-Teramoto (SKT) system. For the resulting system of stochastic partial differential equations…

Probability · Mathematics 2025-01-31 Florian Huber

We study how to solve semidefinite programming relaxations for large scale polynomial optimization. When interior-point methods are used, typically only small or moderately large problems could be solved. This paper studies regularization…

Optimization and Control · Mathematics 2011-12-06 Jiawang Nie , Li Wang

We systematically study a numerical procedure that reveals the asymptotically self-similar dynamics of solutions of partial differential equations (PDEs). This procedure, based on the renormalization group (RG) theory for PDEs, appeared…

Numerical Analysis · Mathematics 2018-07-12 Gastão A. Braga , Federico C. Furtado , Vincenzo Isaia , Long Lee

Recovering a low-complexity signal from its noisy observations by regularization methods is a cornerstone of inverse problems and compressed sensing. Stable recovery ensures that the original signal can be approximated linearly by optimal…

Optimization and Control · Mathematics 2025-05-30 Tran T. A. Nghia , Huy N. Pham , Nghia V. Vo

This paper is the fifth in a series devoted to the development of a rigorous renormalisation group method applicable to lattice field theories containing boson and/or fermion fields, and comprises the core of the method. In the…

Mathematical Physics · Physics 2015-06-19 David C. Brydges , Gordon Slade

A perturbative renormalization group method is used to obtain steady-state density profiles of a particle non-conserving asymmetric simple exclusion process. This method allows us to obtain a globally valid solution for the density profile…

Statistical Mechanics · Physics 2017-04-05 Sutapa Mukherji

We prove existence and uniqueness of strong solutions for a class of semilinear stochastic evolution equations driven by general Hilbert space-valued semimartingales, with drift equal to the sum of a linear maximal monotone operator in…

Probability · Mathematics 2019-11-01 Carlo Marinelli , Luca Scarpa

The non-perturbative renormalization-group approach is extended to lattice models, considering as an example a $\phi^4$ theory defined on a $d$-dimensional hypercubic lattice. Within a simple approximation for the effective action, we solve…

Statistical Mechanics · Physics 2009-03-02 N. Dupuis , K. Sengupta

In this survey, we provide an in-depth exposition of our recent results on the well-posedness theory for stochastic evolution equations, employing maximal regularity techniques. The core of our approach is an abstract notion of critical…

Probability · Mathematics 2025-08-28 Antonio Agresti , Mark Veraar

Dropout-based regularization methods can be regarded as injecting random noise with pre-defined magnitude to different parts of the neural network during training. It was recently shown that Bayesian dropout procedure not only improves…

Machine Learning · Statistics 2017-11-07 Kirill Neklyudov , Dmitry Molchanov , Arsenii Ashukha , Dmitry Vetrov

We establish the renormalization group equation for the running action in the context of a one quantum particle system. This equation is deduced by integrating each fourier mode after the other in the path integral formalism. It is free of…

Quantum Physics · Physics 2009-11-06 P. Gosselin , H. mohrbach

The Kardar-Parisi-Zhang (KPZ) equation is a stochastic partial differential equation which is ill-posed because the nonlinearity is marginally defined with respect to the roughness of the forcing noise. However, its Cole-Hopf solution,…

Probability · Mathematics 2014-07-29 Tadahisa Funaki , Jeremy Quastel

We develop a theoretical approach to ``spontaneous stochasticity'' in classical dynamical systems that are nearly singular and weakly perturbed by noise. This phenomenon is associated to a breakdown in uniqueness of solutions for fixed…

Statistical Mechanics · Physics 2020-11-04 Gregory L. Eyink , Dmytro Bandak

This paper addresses the problem of uniqueness in learning physical laws for systems of partial differential equations (PDEs). Contrary to most existing approaches, it considers a framework of structured model learning, where existing,…

Optimization and Control · Mathematics 2026-02-17 Martin Holler , Erion Morina

In this paper we establish global well-posedness and instantaneous regularization results for the primitive equations with transport noise of H\"{o}lder regularity $ \gamma>\frac{1}{2}$. It is known that if $\gamma<1$, then the noise is too…

Analysis of PDEs · Mathematics 2024-01-11 Antonio Agresti

We prove a concise and easily verifiable criterion on the existence and global stability of stationary solutions for random dynamical systems (RDSs). As a consequence, we can show that the $\omega$-limit sets of all pullback trajectories of…

Dynamical Systems · Mathematics 2025-08-13 Xiang Lv

Upon its inception the theory of regularity structures allowed for the treatment for many semilinear perturbations of the stochastic heat equation driven by space-time white noise. When the driving noise is non-Gaussian the machinery of…

Probability · Mathematics 2017-07-25 Ajay Chandra , Hao Shen

This article is dedicated to the study of an SPDE of the form $$Lu(t,x)=\sigma(u(t,x))\dot{Z}(t,x) \quad t>0, x \in \cO$$ with zero initial conditions and Dirichlet boundary conditions, where $\sigma$ is a Lipschitz function, $L$ is a…

Probability · Mathematics 2014-03-11 Raluca Balan

Existence, uniqueness and non-explosion of the mild solution are proved for a class of semi-linear functional SPDEs with multiplicative noise and Dini continuous drifts. In the finite-dimensional and bounded time delay setting, the…

Probability · Mathematics 2015-05-27 X. Huang , F. -Y. Wang

We consider a fully discrete scheme for nonlinear stochastic partial differential equations with non-globally Lipschitz coefficients driven by multiplicative noise in a multi-dimensional setting. Our method uses a polynomial based spectral…

Numerical Analysis · Mathematics 2021-12-23 Can Huang , Jie Shen
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