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We consider the least-squares approximation of a matrix C in the set of doubly stochastic matrices with the same sparsity pattern as C. Our approach is based on applying the well-known Alternating Direction Method of Multipliers (ADMM) to a…

Optimization and Control · Mathematics 2019-10-14 Nikitas Rontsis , Paul J. Goulart

The quasilinearization method (QLM) of solving nonlinear differential equations is applied to the quantum mechanics by casting the Schr\"{o}dinger equation in the nonlinear Riccati form. The method, whose mathematical basis in physics was…

Computational Physics · Physics 2007-05-23 R. Krivec , V. B. Mandelzweig

We present and experimentally realize a quantum algorithm for efficiently solving the following problem: given an $N\times N$ matrix $\mathcal{M}$, an $N$-dimensional vector $\textbf{\emph{b}}$, and an initial vector $\textbf{\emph{x}}(0)$,…

Recently developed quantum algorithms address computational challenges in numerical analysis by performing linear algebra in Hilbert space. Such algorithms can produce a quantum state proportional to the solution of a $d$-dimensional system…

Quantum Physics · Physics 2021-10-19 Andrew M. Childs , Jin-Peng Liu

The theory of Chebyshev (uniform) approximation for univariate polynomial and piecewise polynomial functions has been studied for decades. The optimality conditions are based on the notion of alternating sequence. However, the extension the…

Numerical Analysis · Mathematics 2017-09-01 Nadezda Sukhorukova , Julien Ugon , David Yost

When solving differential equations by a spectral method, it is often convenient to shift from Chebyshev polynomials $T_{n}(x)$ with coefficients $a_{n}$ to modified basis functions that incorporate the boundary conditions. For homogeneous…

Numerical Analysis · Mathematics 2022-05-31 Xiaolong Zhang , John P. Boyd

We investigate the limitations of quantum computers for solving nonlinear dynamical systems. In particular, we tighten the worst-case bounds of the quantum Carleman linearisation (QCL) algorithm [Liu et al., PNAS 118, 2021] answering one of…

Quantum Physics · Physics 2024-10-30 Dylan Lewis , Stephan Eidenbenz , Balasubramanya Nadiga , Yiğit Subaşı

In arXiv:2305.03945 [math.NA], a first-order optimization algorithm has been introduced to solve time-implicit schemes of reaction-diffusion equations. In this research, we conduct theoretical studies on this first-order algorithm equipped…

Numerical Analysis · Mathematics 2025-04-01 Shu Liu , Xinzhe Zuo , Stanley Osher , Wuchen Li

This article introduces a novel framework for developing quantum algorithms for the Lattice Boltzmann Method (LBM) applied to the advection-diffusion equation. We formulate the collision-streaming evolution of the LBM as a compact…

Mathematical Physics · Physics 2026-02-11 Yuan He , Yuan Yu , Yue Yu

This paper introduces an efficient algorithm for computing the best approximation of a given matrix onto the intersection of linear equalities, inequalities and the doubly nonnegative cone (the cone of all positive semidefinite matrices…

Optimization and Control · Mathematics 2018-03-20 Ying Cui , Defeng Sun , Kim-Chuan Toh

In this paper, the problem of approximate symmetries of a class of non-linear reaction-diffusion equations called Kolmogorov-Petrovsky-Piskounov (KPP) equation is comprehensively analyzed. In order to compute the approximate symmetries, we…

Mathematical Physics · Physics 2014-08-01 Mehdi Nadjafikhah , Abolhassan Mahdavi

We carry Chebyshev-polynomial expansion of the inverse localization length of Hermitian and non-Hermitian random chains as function of energy. For Hermitian models, the expansion produces numerically this energy-dependent function in one…

Disordered Systems and Neural Networks · Physics 2016-12-21 Naomichi Hatano , Joshua Feinberg

The general conditions under which the quadratic, uniform and monotonic convergence in the quasilinearization method of solving nonlinear ordinary differential equations could be proved are formulated and elaborated. The generalization of…

Computational Physics · Physics 2009-11-07 V. B. Mandelzweig , F. Tabakin

Civan and Sliepcevich [1, 2] suggested that special matrix solver should be developed to further reduce the computing effort in applying the differential quadrature (DQ) method for the Poisson and convection-diffusion equations. Therefore,…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 W. Chen , Tingxiu Zhong

In partial differential equations-based (PDE-based) inverse problems with many measurements, many large-scale discretized PDEs must be solved for each evaluation of the misfit or objective function. In the nonlinear case, evaluating the…

Numerical Analysis · Mathematics 2018-07-18 Selin Aslan , Eric de Sturler , Misha E. Kilmer

In this paper, we introduce a method for multivariate function approximation using function evaluations, Chebyshev polynomials, and tensor-based compression techniques via the Tucker format. We develop novel randomized techniques to…

Numerical Analysis · Mathematics 2021-07-29 Arvind K. Saibaba , Rachel Minster , Misha E. Kilmer

In this paper, we give a detailed account of the algorithm outlined in [1] for Feynman integral reduction and $\varepsilon$-factorised differential equations. The algorithm consists of two steps. In the first step, we use a new geometric…

In this paper, the boundary element method is combined with Chebyshev operational matrix technique to solve two-dimensional multi-order time-fractional partial differential equations; nonlinear and linear in respect to spatial and temporal…

Analysis of PDEs · Mathematics 2020-03-31 Moein Khalighi , Mohammad Amirian Matlob , Alaeddin Malek

We present a novel approach to solve the advection-diffusion equation under arbitrary transporting fields using a quantum-inspired 'Schrodingerisation' technique for Hamiltonian simulation. Although numerous methods exist for solving…

Quantum Physics · Physics 2025-08-26 Niladri Gomes , Gautam Sharma , Jay Pathak

In this study linear and nonlinear higher order singularly perturbed problems are examined by a numerical approach, the differential quadrature method. Here, the main idea is using Chebyshev polynomials to acquire the weighting coefficient…

Numerical Analysis · Mathematics 2017-05-29 Gülsemay Yıgıt , Mustafa Bayram
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