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Efficient and stable algorithms for the calculation of spectral quantities and correlation functions are some of the key tools in computational condensed matter physics. In this article we review basic properties and recent developments of…

Other Condensed Matter · Physics 2007-05-23 Alexander Weisse , Gerhard Wellein , Andreas Alvermann , Holger Fehske

In his monograph Chebyshev and Fourier Spectral Methods, John Boyd claimed that, regarding Fourier spectral methods for solving differential equations, ``[t]he virtues of the Fast Fourier Transform will continue to improve as the relentless…

Numerical Analysis · Mathematics 2023-02-03 Craig Gross , Mark Iwen

In this paper we exploit the umbral calculus framework to reformulate the so-called discrete Cauchy-Kovalevskaya extension in the scope of hypercomplex variables. The key idea is to consider not only formal power series representation for…

Complex Variables · Mathematics 2018-12-18 Nelson Faustino

We present a novel and unifying framework for constructing spectral approximations to fractional integral operators. These spectral approximations are based on transplanted Chebyshev polynomials, which are obtained by composing Chebyshev…

Numerical Analysis · Mathematics 2026-04-30 Xiaolin Liu , Kuan Xu

Emerging tensor network techniques for solutions of Partial Differential Equations (PDEs), known for their ability to break the curse of dimensionality, deliver new mathematical methods for ultrafast numerical solutions of high-dimensional…

Numerical Analysis · Mathematics 2024-02-29 Dibyendu Adak , Duc P. Truong , Gianmarco Manzini , Kim Ø. Rasmussen , Boian S. Alexandrov

We apply the ultraspherical spectral method to solving time-dependent PDEs by proposing two approaches to discretization based on the method of lines and show that these approaches produce approximately same results. We analyze the…

Numerical Analysis · Mathematics 2023-06-23 Lu Cheng , Kuan Xu

Chebyshev expansion coefficients can be computed efficiently by using the FFT, and for smooth functions the resulting approximation is close to optimal, with computations that are numerically stable. Given sufficiently accurate function…

Numerical Analysis · Mathematics 2015-03-30 Haiyong Wang , Daan Huybrechs

Computation of the trace of a matrix function plays an important role in many scientific computing applications, including applications in machine learning, computational physics (e.g., lattice quantum chromodynamics), network analysis and…

Data Structures and Algorithms · Computer Science 2017-03-10 Insu Han , Dmitry Malioutov , Haim Avron , Jinwoo Shin

A framework for Chebyshev spectral collocation methods for the numerical solution of functional and delay differential equations (FDEs and DDEs) is described. The framework combines interpolation via the barycentric resampling matrix with a…

Numerical Analysis · Mathematics 2024-08-15 Nicholas Hale

Classical approximation bases such as Chebyshev polynomials provide principled and interpretable representations, but their multivariate tensor-product constructions scale exponentially with dimension and impose axis-aligned structure that…

Machine Learning · Computer Science 2026-04-07 Milo Coombs

We study some convergence issues for a recent approach to the problem of transparent boundary conditions for the Helmholtz equation in unbounded domains. The approach is based on the minimization on an integral functional which arises from…

Numerical Analysis · Mathematics 2014-06-23 Giulio Ciraolo , Francesco Gargano , Vincenzo Sciacca

We derive a stronger uniqueness result if a function with compact support and its truncated Hilbert transform are known on the same interval by using the Sokhotski-Plemelj formulas. To find a function from its truncated Hilbert transform,…

Machine Learning · Computer Science 2020-02-13 Jason You

We explore the applicability of a stochastic time-evolution algorithm based on probabilistic angle interpolation. To simplify the pre-processing of the algorithm, we take the continuous-time limit, thereby explicitly eliminating Trotter…

Quantum Physics · Physics 2026-04-06 Tomoya Hayata , Yuta Kikuchi

This paper proposes a Chebyshev polynomial expansion framework for the recovery of a continuous angular power spectrum (APS) from channel covariance. By exploiting the orthogonality of Chebyshev polynomials in a transformed domain, we…

Information Theory · Computer Science 2026-01-01 Shengsong Luo , Ruilin Wu , Chongbin Xu , Junjie Ma , Xiaojun Yuan , Xin Wang

In this letter, we present a fast and well-conditioned spectral method based on the Chebyshev polynomials for computing the continuous part of the nonlinear Fourier spectrum. The algorithm achieves a complexity of $O(N_{\text{iter.}}N\log…

Computational Physics · Physics 2019-09-10 Vishal Vaibhav

Approximation theory plays a central role in numerical analysis, undergoing continuous evolution through a spectrum of methodologies. Notably, Lebesgue, Weierstrass, Fourier, and Chebyshev approximations stand out among these methods.…

Numerical Analysis · Mathematics 2024-04-30 S Akansha

This paper is devoted to the error analysis of a time-spectral algorithm for fractional diffusion problems of order $\alpha$ ($0 < \alpha < 1$). The solution regularity in the Sobolev space is revisited, and new regularity results in the…

Numerical Analysis · Mathematics 2021-06-08 Hao Luo , Xiaoping Xie

Problems of finite-temperature quantum statistical mechanics can be formulated in terms of imaginary (Euclidean) -time Green's functions and self-energies. In the context of realistic Hamiltonians, the large energy scale of the Hamiltonian…

Statistical Mechanics · Physics 2018-08-17 Emanuel Gull , Sergei Iskakov , Igor Krivenko , Alexander A. Rusakov , Dominika Zgid

Response functions are a key quantity to describe the near-equilibrium dynamics of strongly-interacting many-body systems. Recent techniques that attempt to overcome the challenges of calculating these \emph{ab initio} have employed…

Quantum Physics · Physics 2025-01-22 Doga Murat Kurkcuoglu , Alessandro Roggero , Gabriel N. Perdue , Rajan Gupta

The existing research on spectral algorithms, applied within a Reproducing Kernel Hilbert Space (RKHS), has primarily focused on general kernel functions, often neglecting the inherent structure of the input feature space. Our paper…

Machine Learning · Statistics 2024-03-08 Weichun Xia , Lei Shi