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In this paper we use a Variational Quantum Algorithm to solve Initial Value Problems with the Implicit Crank-Nicolson and the Method of Lines (MoL) evolution schemes. The unknown functions use a spectral decomposition with the Fourier…

Quantum Physics · Physics 2024-10-17 Francisco Guzman-Cajica , Francisco S. Guzman

For the computation of the generalized singular value decomposition (GSVD) of a large matrix pair $(A,B)$ of full column rank, the GSVD is commonly formulated as two mathematically equivalent generalized eigenvalue problems, so that a…

Numerical Analysis · Mathematics 2021-04-13 Jinzhi Huang , Zhongxiao Jia

We present a rigorous convergence result for the smooth solutions to a singular semilinear hyperbolic approximation, a vector BGK model, to the solutions to the incompressible Navier-Stokes equations in Sobolev spaces. Our proof is based on…

Analysis of PDEs · Mathematics 2019-12-10 Roberta Bianchini , Roberto Natalini

We here aim at proving the global existence and uniqueness of solutions to the inhomogeneous incompressible Navier-Stokes system in the case where the initial density is discontinuous and the initial velocity has critical regularity.…

Analysis of PDEs · Mathematics 2023-01-04 Raphaël Danchin , Shan Wang

The solution of matrices with $2\times 2$ block structure arises in numerous areas of computational mathematics, such as PDE discretizations based on mixed-finite element methods, constrained optimization problems, or the implicit or steady…

Numerical Analysis · Mathematics 2023-07-07 Ben S. Southworth , Abdullah A. Sivas , Sander Rhebergen

This work analyzes singular-value spectra of weight matrices in pretrained transformer models to understand how information is stored at both ends of the spectrum. Using Random Matrix Theory (RMT) as a zero information hypothesis, we…

Machine Learning · Computer Science 2025-11-07 Max Staats , Matthias Thamm , Bernd Rosenow

We present in this paper construction and analysis of a block-centered finite difference method for the spatial discretization of the scalar auxiliary variable Crank-Nicolson scheme (SAV/CN-BCFD) for gradient flows, and show rigorously that…

Numerical Analysis · Mathematics 2018-12-06 Xiaoli Li , Jie Shen , Hongxing Rui

The problems of numerical modeling of viscous incompressible fluid flows are widely considered in computational fluid dynamics. Stationary solutions of boundary value problems for the Navier-Stokes equations exist at large Reynolds numbers,…

Numerical Analysis · Mathematics 2024-10-30 D. V. Lomasov , P. N. Vabishchevich

In this paper, we study the initial-value problem for two first order systems in non-conservative form. The first system arises in elastodynamics and belongs to the class of strictly hyperbolic, genuinely nonlinear systems. The second…

Analysis of PDEs · Mathematics 2013-03-04 Anupam Pal Choudhury

The objective of this work is to investigate the challenges encountered in Scale-Resolving Simulations (SRS's) of turbulent wake flows driven by spatially-developing coherent structures. SRS's of practical interest are expressly intended…

Fluid Dynamics · Physics 2018-01-16 F. S. Pereira , L. Eca , G. Vaz , S. S. Girimaji

This paper studies the rank-$1$ tensor completion problem for cubic tensors. First of all, we show that this problem is equivalent to a special rank-$1$ matrix recovery problem. When the tensor is strongly rank-$1$ completable, we show that…

Optimization and Control · Mathematics 2024-10-23 Jinling Zhou , Jiawang Nie , Zheng Peng , Guangming Zhou

The oriented singular value decomposition (O-SVD) proposed by Zeng and Ng provides a hybrid approach to the t-product based third-order tensor singular value decomposition with the transform matrix being a factor matrix of the higher order…

Numerical Analysis · Mathematics 2023-02-28 Minghui Ding , Yimin Wei , Pengpeng Xie

We construct a class of spatially polynomial velocity fields that are exact solutions of the planar unsteady Navier-Stokes equation. These solutions can be used as simple benchmarks for testing numerical methods or verifying the feasibility…

Fluid Dynamics · Physics 2020-05-20 Tiemo Pedergnana , David Oettinger , Gabriel Provencher-Langlois , George Haller

In this paper we propose a new scaling method to study the Schur complements of $SDD_{1}$ matrices. Its core is related to the non-negative property of the inverse $M$-matrix, while numerically improving the Quotient formula. Based on the…

Numerical Analysis · Mathematics 2025-04-22 Yang Hu , Jianzhou Liu , Wenlong Zeng

The hierarchy of exact equations is given that relates two-spatial-point velocity structure functions of arbitrary order with other statistics. Because no assumption is used, the exact statistical equations can apply to any flow for which…

Fluid Dynamics · Physics 2019-06-19 Reginald J. Hill

Analyzing complex experimental data with multiple parameters is challenging. We propose using Singular Value Decomposition (SVD) as an effective solution. This method, demonstrated through real experimental data analysis, surpasses…

Data Analysis, Statistics and Probability · Physics 2024-07-24 Judith F. Stein , Aviad Frydman , Richard Berkovits

Recent empirical evidence suggests that the Weston-Watkins support vector machine is among the best performing multiclass extensions of the binary SVM. Current state-of-the-art solvers repeatedly solve a particular subproblem approximately…

Machine Learning · Statistics 2021-06-08 Yutong Wang , Clayton D. Scott

We present a cost-reduced approach for the distinguishable cluster approximation to coupled cluster with singles, doubles and iterative triples (DC-CCSDT) based on a tensor decomposition of the triples amplitudes. The triples amplitudes and…

Chemical Physics · Physics 2025-03-07 Charlotte Rickert , Denis Usvyat , Daniel Kats

To increase the reliability of simulations by particle methods for incompressible viscous flow problems, convergence studies and improvements of accuracy are considered for a fully explicit particle method for incompressible Navier--Stokes…

Numerical Analysis · Computer Science 2019-07-03 Y. Imoto , S. Tsuzuki , D. Nishiura

We evaluate performance of associative memory in a neural network by based on the singular value decomposition (SVD) of image data stored in the network. We consider the situation in which the original image and its highly coarse-grained…

Statistical Mechanics · Physics 2017-03-08 Tatsuya Kumamoto , Mao Suzuki , Hiroaki Matsueda
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