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In approximation theory, it is standard to approximate functions by polynomials expressed in the Chebyshev basis. Evaluating a polynomial $f$ of degree n given in the Chebyshev basis can be done in $O(n)$ arithmetic operations using the…

Symbolic Computation · Computer Science 2019-12-13 Viviane Ledoux , Guillaume Moroz

This paper concerns the design of a multidimensional Chebyshev interpolation based method for a differential game theory problem. In continuous game theory problems, it might be difficult to find analytical solutions, so numerical methods…

Numerical Analysis · Mathematics 2023-07-11 Carmelo de Castro , Víctor Gatón , Beatriz Gómez

We present a new algorithm for finding isolated zeros of a system of real-valued functions in a bounded interval in $\mathbb{R}^n$. It uses the Chebyshev proxy method combined with a mixture of subdivision, reduction methods, and…

We present two new quantum algorithms for reaction-diffusion equations that employ the truncated Chebyshev polynomial approximation. This method is employed to numerically solve the ordinary differential equation emerging from the…

Quantum Physics · Physics 2025-10-24 Manish Kumar

Matrix evolution equations occur in many applications, such as dynamical Lyapunov/Sylvester systems or Riccati equations in optimization and stochastic control, machine learning or data assimilation. In many such problems, the dominant…

Numerical Analysis · Mathematics 2026-02-12 Nayef Shkeir , Tobias Grafke

Perturbation theory is a powerful tool for studying large-scale structure formation in the universe and calculating observables such as the power spectrum or bispectrum. However, beyond linear order, typically this is done by assuming a…

Cosmology and Nongalactic Astrophysics · Physics 2023-08-09 Nicholas Choustikov , Zvonimir Vlah , Anthony Challinor

We develop a distributed Block Chebyshev-Davidson algorithm to solve large-scale leading eigenvalue problems for spectral analysis in spectral clustering. First, the efficiency of the Chebyshev-Davidson algorithm relies on the prior…

Machine Learning · Computer Science 2024-01-08 Qiyuan Pang , Haizhao Yang

This paper presents for the first time a robust exact line-search method based on a full pseudospectral (PS) numerical scheme employing orthogonal polynomials. The proposed method takes on an adaptive search procedure and combines the…

Optimization and Control · Mathematics 2023-03-06 Kareem T. Elgindy

This contribution is dedicated to the exploration of exponential operator splitting methods for the time integration of evolution equations. It entails the review of previous achievements as well as the depiction of novel results. The…

Numerical Analysis · Mathematics 2024-10-18 Sergio Blanes , Fernando Casas , Cesareo Gonzalez , Mechthild Thalhammer

A piecewise Chebyshevian spline space is good for design when it possesses a B-spline basis and this property is preserved under knot insertion. The interest in such kind of spaces is justified by the fact that, similarly as for polynomial…

Numerical Analysis · Mathematics 2021-11-12 Carolina Vittoria Beccari , Giulio Casciola , Lucia Romani

In this paper, we present exact exponential algorithms for computing branchwidth that are fast both in theory and in practice. The running times of these algorithms are single-exponential in the number of vertices. Our basic algorithm is…

Data Structures and Algorithms · Computer Science 2026-05-19 Taiki Kaneda , Yasuaki Kobayashi , Hisao Tamaki

We study the problem of approximately recovering a probability distribution given noisy measurements of its Chebyshev polynomial moments. This problem arises broadly across algorithms, statistics, and machine learning. By leveraging a…

Data Structures and Algorithms · Computer Science 2026-05-20 Cameron Musco , Christopher Musco , Lucas Rosenblatt , Apoorv Vikram Singh

The Chebyshev expansion offers a numerically efficient and easy-implement algorithm for evaluating dynamic correlation functions using matrix product states (MPS). In this approach, each recursively generated Chebyshev vector is…

Strongly Correlated Electrons · Physics 2018-02-14 H. D. Xie , R. Z. Huang , X. J. Han , X. Yan , H. H. Zhao , Z. Y. Xie , H. J. Liao , T. Xiang

Three numerical algorithms are proposed to solve the time-dependent elastodynamic equations in elastic solids. All algorithms are based on approximating the solution of the equations, which can be written as a matrix exponential. By…

Geophysics · Physics 2007-05-23 J. S. Kole

Quantum computing shows promise for addressing computationally intensive problems but is constrained by the exponential resource requirements of general quantum state tomography (QST), which fully characterizes quantum states through…

Quantum Physics · Physics 2025-09-12 Hao Su , Shiying Xiong , Yue Yang

This paper presents a novel approach to rigorously solving initial value problems for semilinear parabolic partial differential equations (PDEs) using fully spectral Fourier-Chebyshev expansions. By reformulating the PDE as a system of…

Analysis of PDEs · Mathematics 2025-03-03 Matthieu Cadiot , Jean-Philippe Lessard

We propose algorithms for efficient time integration of large systems of oscillatory second order ordinary differential equations (ODEs) whose solution can be expressed in terms of trigonometric matrix functions. Our algorithms are based on…

Numerical Analysis · Mathematics 2023-04-07 M. A. Botchev , L. A. Knizhnerman , M. Schweitzer

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

Algorithms and underlying mathematics are presented for numerical computation with periodic functions via approximations to machine precision by trigonometric polynomials, including the solution of linear and nonlinear periodic ordinary…

Numerical Analysis · Mathematics 2015-11-03 Grady B. Wright , Mohsin Javed , Hadrien Montanelli , Lloyd N. Trefethen

This paper explores a new class of constrained difference programming problems, where the objective and constraints are formulated as differences of functions, without requiring their convexity. To investigate such problems, novel variants…

Optimization and Control · Mathematics 2026-04-21 Boris S. Mordukhovich , Yixia Song , Shangzhi Zeng , Jin Zhang