Weighted Composition Operators for Learning Nonlinear Dynamics. [PDF]
Russo BP +3 more
europepmc +1 more source
An Augmented Lagrangian Preconditioner for Navier–Stokes Equations With Runge–Kutta in Time
ABSTRACT We consider an implicit Runge–Kutta method for the numerical time integration of the nonstationary incompressible Navier–Stokes equations. This yields a sequence of nonlinear problems to be solved for the stages of the Runge–Kutta method. The resulting nonlinear system of differential equations is discretized using a finite element method.
Santolo Leveque +2 more
wiley +1 more source
Operator-Valued Twisted Araki-Woods Algebras. [PDF]
Kumar RR, Wirth M.
europepmc +1 more source
Row‐Aware Randomized SVD With Applications
ABSTRACT The randomized singular value decomposition proposed in [28] has certainly become one of the most well‐established randomization‐based algorithms in numerical linear algebra. The key ingredient of the entire procedure is the computation of a subspace which is close to the column space of the target matrix A∈ℝm×n$$ \mathbf{A}\in {\mathbb{R}}^{m\
Davide Palitta, Sascha Portaro
wiley +1 more source
Howe Duality and Dynamical Weyl Group. [PDF]
Dalipi R, Felder G, Gurenkova A.
europepmc +1 more source
Gram Decay and Intrinsic Dimensions of Krylov Subspaces
ABSTRACT Krylov subspace methods solve large sparse linear systems Ax=b$$ Ax=b $$ by building a sequence of polynomial approximations to A−1b$$ {A}^{-1}b $$ from successive matrix‐vector products. In finite precision, the number of numerically independent directions that can be extracted from this sequence is bounded by the intrinsic information ...
Stephen J. Thomas
wiley +1 more source
Energy-dissipative adaptive-step L1 discretisation for the Caputo time-fractional incompressible magnetohydrodynamic system. [PDF]
Abidin MZ.
europepmc +1 more source
Building a Digital Twin for Material Testing: Model Reduction and Data Assimilation
ABSTRACT The rapid advancement of industrial technologies, data collection, and handling methods has paved the way for the widespread adoption of digital twins (DTs) in engineering, enabling seamless integration between physical systems and their virtual counterparts.
Rubén Aylwin +5 more
wiley +1 more source
Topological data analysis and topological deep learning beyond persistent homology: a review. [PDF]
Su Z +7 more
europepmc +1 more source
Nonlinear Model Order Reduction on Polynomial Manifolds for Computational Homogenisation Problems
ABSTRACT Model order reduction (MOR) techniques utilising nonlinear approximation spaces can search for solutions to computational homogenisation problems on low‐dimensional approximation spaces. In combination with hyperreduction techniques, this allows for computations on representative volume elements (RVEs) to be accelerated by multiple orders of ...
Erik Faust, Lisa Scheunemann
wiley +1 more source

