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Higher-order spectra (or polyspectra), defined as the Fourier Transform of a stationary process' autocumulants, are useful in the analysis of nonlinear and non Gaussian processes. Polyspectral means are weighted averages over Fourier…

Statistics Theory · Mathematics 2024-10-23 Dhrubajyoti Ghosh , Tucker McElroy , Soumendra Lahiri

We introduce a novel spectral element method based on the ultraspherical spectral method and the hierarchical Poincar\'{e}-Steklov scheme for solving second-order linear partial differential equations on polygonal domains with unstructured…

Numerical Analysis · Mathematics 2021-05-19 Daniel Fortunato , Nicholas Hale , Alex Townsend

We solve principal component regression (PCR), up to a multiplicative accuracy $1+\gamma$, by reducing the problem to $\tilde{O}(\gamma^{-1})$ black-box calls of ridge regression. Therefore, our algorithm does not require any explicit…

Machine Learning · Statistics 2017-04-26 Zeyuan Allen-Zhu , Yuanzhi Li

We develop the theoretical procedures for shifting the frequency of a single soliton and of a sequence of solitons of the nonlinear Schr\"odinger equation. The procedures are based on simple transformations of the soliton pattern in the…

Pattern Formation and Solitons · Physics 2020-03-03 Quan M. Nguyen , Toan T. Huynh

We address the problem of the best uniform approximation by linear combinations of a finite system of functions. If the system is Chebyshev and the problem is unconstrained, then the classical Remez algorithm provides a fast and precise…

Numerical Analysis · Mathematics 2025-07-08 Vladimir Yu. Protasov , Rinat Kamalov

A rapid transformation is derived between spherical harmonic expansions and their analogues in a bivariate Fourier series. The change of basis is described in two steps: firstly, expansions in normalized associated Legendre functions of all…

Numerical Analysis · Mathematics 2017-11-07 Richard Mikael Slevinsky

We propose an optimization algorithm to compute the optimal sensor locations in experimental design in the formulation of Bayesian inverse problems, where the parameter-to-observable mapping is described through an integral equation and its…

Computation · Statistics 2019-12-30 Jing Yu , Mihai Anitescu

We propose a Petrov--Galerkin spectral method for ODEs with variable coefficients. When the variable coefficients are smooth, the new method yields a strictly banded linear system, which can be efficiently constructed and solved in linear…

Numerical Analysis · Mathematics 2025-02-18 Ouyuan Qin , Lu Cheng , Kuan Xu

In this paper, a new framework for continuous-time maximum a posteriori estimation based on the Chebyshev polynomial optimization (ChevOpt) is proposed, which transforms the nonlinear continuous-time state estimation into a problem of…

Robotics · Computer Science 2022-07-13 Maoran Zhu , Yuanxin Wu

A large class of machine learning techniques requires the solution of optimization problems involving spectral functions of parametric matrices, e.g. log-determinant and nuclear norm. Unfortunately, computing the gradient of a spectral…

Machine Learning · Computer Science 2018-10-31 Insu Han , Haim Avron , Jinwoo Shin

We introduce a versatile numerical method for modeling light diffraction in periodically patterned photonic structures containing quadratically nonlinear non-centrosymmetric optical materials. Our approach extends the generalized source…

Optics · Physics 2015-06-23 Martin Weismann , Dominic F. G. Gallagher , Nicolae C. Panoiu

Fast Fourier transform algorithms are an arsenal of effective tools for solving various problems of analysis and high-speed processing of signals of various natures. Almost all of these algorithms are designed to process sequences of…

Data Structures and Algorithms · Computer Science 2025-04-11 Aleksandr Cariow

We introduce a general purpose algorithm for rapidly computing certain types of oscillatory integrals which frequently arise in problems connected to wave propagation and general hyperbolic equations. The problem is to evaluate numerically…

Numerical Analysis · Mathematics 2007-05-23 Emmanuel Candes , Laurent Demanet , Lexing Ying

Bayesian inference, while foundational to probabilistic reasoning, is often hampered by the computational intractability of posterior distributions, particularly through the challenging evidence integral. Conventional approaches like Markov…

Machine Learning · Computer Science 2025-11-11 Di Zhang

We propose a Fourier pseudo-spectral scheme for the space-fractional nonlinear Schr\"odinger equation. The proposed scheme has the following features: it is linearly implicit, it preserves two invariants of the equation, its unique…

Numerical Analysis · Mathematics 2019-09-04 Yuto Miyatake , Tai Nakagawa , Tomohiro Sogabe , Shao-Liang Zhang

Landauer-B\"uttiker formula describes the electronic quantum transports in nanostructures and molecules. It will be numerically demanding for simulations of complex or large size systems due to, for example, matrix inversion calculations.…

Mesoscale and Nanoscale Physics · Physics 2020-07-22 Yan Yu , Yan-Yang Zhang , Lei Liu , Si-Si Wang , Ji-Huan Guan , Yang Xia , Shu-Shen Li

The $N$th power of a polynomial matrix of fixed size and degree can be computed by binary powering as fast as multiplying two polynomials of linear degree in~$N$. When Fast Fourier Transform (FFT) is available, the resulting complexity is…

Symbolic Computation · Computer Science 2023-05-29 Alin Bostan , Vincent Neiger , Sergey Yurkevich

In this work, we present the \emph{twiddless fast Fourier transform (TFFT)}, a novel algorithm for computing the $N$-point discrete Fourier transform (DFT). The TFFT's divide strategy builds on recent results that decimate an $N$-point…

Computational Complexity · Computer Science 2025-12-23 Saulo Queiroz

Pseudospectral numerical schemes for solving the Dirac equation in general static curved space are derived using a pseudodifferential representation of the Dirac equation along with a simple Fourier-basis technique. Owing to the presence of…

Numerical Analysis · Mathematics 2020-04-22 Xavier Antoine , François Fillion-Gourdeau , Emmanuel Lorin , Steve McLean

The discrete Chebyshev polynomials $t_n(x,N)$ are orthogonal with respect to a distribution, which is a step function with jumps one unit at the points $x=0,1,\cdots, N-1$, $N$ being a fixed positive integer. By using a double integral…

Complex Variables · Mathematics 2013-03-19 J. H. Pan , Roderick Wong