The Mori-Zwanzig Approach to Dimension Reduction and Uncertainty Quantification

Abstract

The Mori-Zwanzig (MZ) formulation is a technique originally developed in statistical mechanics to formally integrate out phase variables in nonlinear dynamical systems by means of a projection operator. One of the main features of such formulation is that it allows us to systematically derive exact equations of motion for quantities of interest (macroscopic observables), based on microscopic equations of motion. Such equations can be found in a variety of applications, including molecular dynamics, fluid dynamics, and solid-state physics. Computing the solution to the MZ equation is a challenging task. One of the main difficulties is the approximation of the memory integral (convolution term), and the fluctuation term (noise), which encode the interaction between the so-called orthogonal dynamics and the dynamics of the quantity of interest. The orthogonal dynamics is essentially a high-dimensional nonlinear flow that satisfies a hard-to-solve integro-differential equation. Such flow has, in general, the same order of magnitude and dynamical properties as the quantity of interest, i.e., there is no general scale separation between the so-called resolved and the unresolved variables of the system. As a consequence, approximating the MZ memory integral and the fluctuation term in these cases is a daunting task, because of the strong coupling between the orthogonal dynamics and the dynamics of the macroscopic observables. In this project, we developed an in-depth mathematical analysis of the MZ formulation for both deterministic and stochastic dynamical systems, and established an effective computational framework that allows us to perform numerical simulations of the MZ equation.

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Document Details

Document Type
Technical Report
Publication Date
Jan 03, 2020
Accession Number
AD1105871

Entities

People

  • Daniele Venturi

Organizations

  • University of California, Santa Cruz

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Bessel Functions
  • Complex Variables
  • Computational Science
  • Data Science
  • Differential Equations
  • Equations Of Motion
  • Formulas (Mathematics)
  • Information Science
  • Mathematical Analysis
  • Molecular Dynamics
  • Monte Carlo Method
  • Random Variables
  • Statistical Algorithms
  • Stochastic Processes
  • Theorems
  • Wave Equations
  • Wave Propagation

Fields of Study

  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Theoretical Analysis.