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Related papers: Data Driven Learning of Mori-Zwanzig Operators for…

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In this work, we apply, for the first time to spatially inhomogeneous flows, a recently developed data-driven learning algorithm of Mori-Zwanzig (MZ) operators, which is based on a generalized Koopman's description of dynamical systems. The…

A theoretical framework which unifies the conventional Mori-Zwanzig formalism and the approximate Koopman learning is presented. In this framework, the Mori-Zwanzig formalism, developed in statistical mechanics to tackle the hard problem of…

Statistical Mechanics · Physics 2021-07-27 Yen Ting Lin , Yifeng Tian , Marian Anghel , Daniel Livescu

We develop a new formulation of deep learning based on the Mori-Zwanzig (MZ) formalism of irreversible statistical mechanics. The new formulation is built upon the well-known duality between deep neural networks and discrete dynamical…

Machine Learning · Computer Science 2023-05-23 Daniele Venturi , Xiantao Li

Understanding, predicting and controlling laminar-turbulent boundary-layer transition is crucial for the next generation aircraft design. However, in real flight experiments, or wind tunnel tests, often only sparse sensor measurements can…

The dynamics of Lagrangian particles in turbulence play a crucial role in mixing, transport, and dispersion in complex flows. Their trajectories exhibit highly non-trivial statistical behavior, motivating the development of surrogate models…

The development of reduced models for complex multiscale problems remains one of the principal challenges in computational physics. The optimal prediction framework of Chorin et al., which is a reformulation of the Mori-Zwanzig (M-Z)…

Fluid Dynamics · Physics 2017-09-13 Eric J. Parish , Karthik Duraisamy

We propose to adopt statistical regression as the projection operator to enable data-driven learning of the operators in the Mori--Zwanzig formalism. We present a principled method to extract the Markov and memory operators for any…

Dynamical Systems · Mathematics 2023-04-24 Yen Ting Lin , Yifeng Tian , Danny Perez , Daniel Livescu

Reduced Order Models (ROMs) of complex, nonlinear dynamical systems often require closure, which is the process of representing the contribution of the unresolved physics on the resolved physics. The Mori-Zwanzig (M-Z) procedure allows one…

Numerical Analysis · Mathematics 2017-09-26 Ayoub Gouasmi , Eric Parish , Karthik Duraisamy

In many time-dependent problems of practical interest the parameters and/or initial conditions entering the equations describing the evolution of the various quantities exhibit uncertainty. One way to address the problem of how this…

Numerical Analysis · Mathematics 2018-03-09 Jing Li , Panos Stinis

The Mori-Zwanzig projection operator formalism is one of the central tools of nonequilibrium statistical mechanics, allowing to derive macroscopic equations of motion from the microscopic dynamics through a systematic coarse-graining…

Statistical Mechanics · Physics 2020-06-18 Michael te Vrugt , Raphael Wittkowski

Built upon the hypoelliptic analysis of the effective Mori-Zwanzig (EMZ) equation for observables of stochastic dynamical systems, we show that the obtained semigroup estimates for the EMZ equation can be used to drive prior estimates of…

Mathematical Physics · Physics 2021-06-21 Yuanran Zhu , Huan Lei

We develop rigorous estimates and provably convergent approximations for the memory integral in the Mori-Zwanzig (MZ) formulation. The new theory is built upon rigorous mathematical foundations and is presented for both state-space and…

Numerical Analysis · Mathematics 2018-10-17 Yuanran Zhu , Jason M. Dominy , Daniele Venturi

We present a general numerical approach for constructing governing equations for unknown dynamical systems when only data on a subset of the state variables are available. The unknown equations for these observed variables are thus a…

Machine Learning · Statistics 2020-04-21 Xiaohan Fu , Lo-Bin Chang , Dongbin Xiu

Model reduction methods aim to describe complex dynamic phenomena using only relevant dynamical variables, decreasing computational cost, and potentially highlighting key dynamical mechanisms. In the absence of special dynamical features…

Numerical Analysis · Mathematics 2020-12-14 Kevin K. Lin , Fei Lu

This work uses the Mori-Zwanzig (M-Z) formalism, a concept originating from non-equilibrium statistical mechanics, as a basis for the development of coarse-grained models of turbulence. The mechanics of the generalized Langevin equation…

Fluid Dynamics · Physics 2017-02-01 Eric J. Parish , Karthik Duraisamy

The well-known Mori-Zwanzig theory tells us that model reduction leads to memory effect. For a long time, modeling the memory effect accurately and efficiently has been an important but nearly impossible task in developing a good reduced…

Machine Learning · Computer Science 2018-08-14 Chao Ma , Jianchun Wang , Weinan E

We describe a paradigm for multiscale modeling that combines the Mori-Zwanzig (MZ) formalism of Statistical Mechanics with the Variational Multiscale (VMS) method. The MZ-VMS approach leverages both VMS scale-separation projectors as well…

Numerical Analysis · Mathematics 2017-12-29 Eric J. Parish , Karthik Duraisamy

Explaining the emergence of stochastic irreversible macroscopic dynamics from time-reversible deterministic microscopic dynamics is one of the key problems in philosophy of physics. The Mori-Zwanzig projection operator formalism, which is…

Statistical Mechanics · Physics 2022-07-04 Michael te Vrugt

We introduce the Mori-Zwanzig Mode Decomposition (MZMD), a novel data-driven technique for efficient modal analysis of and reduced-order modeling of large-scale spatio-temporal dynamical systems. MZMD represents an extension of Dynamic Mode…

Fluid Dynamics · Physics 2025-05-09 Michael Woodward , Yen Ting Lin , Yifeng Tian , Christoph Hader , Hermann Fasel , Daniel Livescu

Mathematical approaches from dynamical systems theory are used in a range of fields. This includes biology where they are used to describe processes such as protein-protein interaction and gene regulatory networks. As such networks increase…

Numerical Analysis · Mathematics 2020-11-05 Edgar Herrera-Delgado , James Briscoe , Peter Sollich
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