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A flux of ideal fluid coupled to perturbation is investigated by nonperturbative methods of the quantum field theory. Asymptotic behavior of the flux coupled to perturbation turns out to be similiar to that of superfluids.

Fluid Dynamics · Physics 2016-09-08 Dmitri Volchenkov , Ricardo Lima

We introduce a class of unconditionally energy stable, high order accurate schemes for gradient flows in a very general setting. The new schemes are a high order analogue of the minimizing movements approach for generating a time discrete…

Numerical Analysis · Mathematics 2020-02-11 Alexander Zaitzeff , Selim Esedoglu , Krishna Garikipati

Existing analyses of optimization in deep learning are either continuous, focusing on (variants of) gradient flow, or discrete, directly treating (variants of) gradient descent. Gradient flow is amenable to theoretical analysis, but is…

Machine Learning · Computer Science 2021-12-30 Omer Elkabetz , Nadav Cohen

We derive a perturbative approach to study, in the large inertia limit, the dynamics of solid particles in a smooth, incompressible and finite-time correlated random velocity field. We carry on an expansion in powers of the inverse square…

Statistical Mechanics · Physics 2009-11-13 Piero Olla , Maria Raffaella Vuolo

This is a brief introduction to the statistical theory of fluid turbulence, with an emphasis on the field-theoretic treatment of renormalized viscosity and energy fluxes.

Chaotic Dynamics · Physics 2020-11-18 Mahendra K. Verma

We consider linear hyperbolic balance law that describe gas flow. Stochastic influences are introduced by series of orthogonal functions. A deterministic stabilization concept, which makes deviations at steady states decay exponentially…

Optimization and Control · Mathematics 2021-02-25 Stephan Gerster

The standard lattice perturbation theory leads to the asymptotic series because of the incorrect interchange of the summation and integration. However, changing the initial approximation of the perturbation theory, one can generate the…

High Energy Physics - Lattice · Physics 2015-11-20 Vladimir V. Belokurov , Aleksandr S. Ivanov , Vasily K. Sazonov , Eugeny T. Shavgulidze

In these lectures we give a brief introduction to perturbative and non-perturbative string theory. The outline is the following: 1. Introduction to perturbative string theory 1.1 From point particle to extended objects 1.2 Free closed and…

High Energy Physics - Theory · Physics 2016-09-06 Ignatios Antoniadis , Guillaume Ovarlez

We consider the stochastically driven one dimensional nonlinear oscillator $\ddot{x}+2\Gamma\dot{x}+\omega^2_0 x+\lambda x^3 = f(t)$ where f(t) is a Gaussian noise which, for the bulk of the work, is delta correlated (white noise). We…

Statistical Mechanics · Physics 2022-08-04 Akshay Pal , Jayanta Kumar Bhattacharjee

We consider policy gradient methods for stochastic optimal control problem in continuous time. In particular, we analyze the gradient flow for the control, viewed as a continuous time limit of the policy gradient method. We prove the global…

Optimization and Control · Mathematics 2025-04-15 Mo Zhou , Jianfeng Lu

By means of a novel variational approach and using dual maps techniques and general ideas of dynamical system theory we derive exact results about several models of transport flows, for which we also obtain a complete description of their…

Chaotic Dynamics · Physics 2007-05-23 Michael Blank

In this study, a new set of fifth-order Stokes wave solutions, incorporating the effects of a linear shear current, is derived by utilizing the perturbation method originally proposed for pure waves that was recently published. The present…

Fluid Dynamics · Physics 2023-08-08 Haiqi Fang , Philip L. -F. Liu , Lian Tang , Pengzhi Lin

A calculational approach in fluid turbulence is presented. Use is made of the attracting nature of the fluid-dynamic dynamical system. An approach is offered that effectively propagates the statistics in time. Loss of sensitivity to an…

Fluid Dynamics · Physics 2010-05-18 Edsel A. Ammons

Stochastic normalizing flows are a class of deep generative models that combine normalizing flows with Monte Carlo updates and can be used in lattice field theory to sample from Boltzmann distributions. In this proceeding, we outline the…

High Energy Physics - Lattice · Physics 2022-10-10 Michele Caselle , Elia Cellini , Alessandro Nada , Marco Panero

Fluctuation effects at first order phase transitions driven by changes of other-than-temperature factors like pressure, concentration, or external fields are investigated by perturbation theory. The results for the fluctuation contributions…

Statistical Mechanics · Physics 2017-01-10 Dimo I. Uzunov

We study well-posedness of sweeping processes with stochastic perturbations generated by a fractional Brownian motion and convergence of associated numerical schemes. To this end, we first prove new existence, uniqueness and approximation…

Classical Analysis and ODEs · Mathematics 2015-05-07 Adrian Falkowski , Leszek Slominski

An approach for the description of stochastic systems is derived. Some of the variables in the system are studied forward in time, others backward in time. The approach is based on a perturbation expansion in the strength of the coupling…

Statistical Mechanics · Physics 2021-08-04 Piero Olla

This report is actually the in-class project of MATH489 FA2022, Dynamics and Differential Equations in University of Illinois Urbana-Champaign. The report is mainly about gradient flow of a Morse-type functions (Morse functions, Morse--Bott…

Dynamical Systems · Mathematics 2023-11-17 Leyang Zhang

We study the phenomenon of turbulence from the point of view of statistical physics. We discuss what makes the turbulent states different from the thermodynamic equilibrium and give the turbulent analog of the partition function. Then,…

High Energy Physics - Theory · Physics 2016-09-06 V. Gurarie

The particle-in-cell numerical method of plasma physics balances a trade-off between computational cost and intrinsic noise. Inference on data produced by these simulations generally consists of binning the data to recover the particle…

Plasma Physics · Physics 2022-02-03 John Donaghy , Kai Germaschewski