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The classical division algorithm for polynomials requires $O(n^2)$ operations for inputs of size $n$. Using reversal technique and Newton iteration, it can be improved to $O({M}(n))$, where ${M}$ is a multiplication time. But the method…

Symbolic Computation · Computer Science 2011-12-20 Zhengjun Cao , Hanyue Cao

Fast algorithms for arithmetic on real or complex polynomials are well-known and have proven to be not only asymptotically efficient but also very practical. Based on Fast Fourier Transform (FFT), they for instance multiply two polynomials…

Symbolic Computation · Computer Science 2007-05-23 Martin Ziegler

Multiplication of n-digit integers by long multiplication requires O(n^2) operations and can be time-consuming. In 1970 A. Schoenhage and V. Strassen published an algorithm capable of performing the task with only O(n log(n)) arithmetic…

Numerical Analysis · Computer Science 2010-06-03 Thomas Steinke , Raazesh Sainudiin

A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time of at most a polynomial factor. This may not…

Quantum Physics · Physics 2017-02-20 Peter W. Shor

Fast linear transforms are ubiquitous in machine learning, including the discrete Fourier transform, discrete cosine transform, and other structured transformations such as convolutions. All of these transforms can be represented by dense…

Machine Learning · Computer Science 2021-01-01 Tri Dao , Albert Gu , Matthew Eichhorn , Atri Rudra , Christopher Ré

We explore a new form of DFT, which we call the Polynomial Transform. It functions over finite fields, and a size $n$ transform takes $O(n)$ operations. In the multitape Turing machine model, it allows us to multiply two $n$ bit numbers in…

Data Structures and Algorithms · Computer Science 2019-12-11 Matt Groff

The Fourier Transform is one of the most important linear transformations used in science and engineering. Cooley and Tukey's Fast Fourier Transform (FFT) from 1964 is a method for computing this transformation in time $O(n\log n)$. From a…

Computational Complexity · Computer Science 2018-11-09 Nir Ailon

It is well known that, using fast algorithms for polynomial multiplication and division, evaluation of a polynomial $F \in \mathbb{C}[x]$ of degree $n$ at $n$ complex-valued points can be done with $\tilde{O}(n)$ exact field operations in…

Numerical Analysis · Computer Science 2016-05-30 Alexander Kobel , Michael Sagraloff

This paper deals with simultaneously fast and in-place algorithms for formulae where the result has to be linearly accumulated: some output variables are also input variables, linked by a linear dependency. Fundamental examples include the…

Symbolic Computation · Computer Science 2025-11-07 Jean-Guillaume Dumas , Bruno Grenet

Matrix multiplication is a fundamental kernel in high performance computing. Many algorithms for fast matrix multiplication can only be applied to enormous matrices ($n>10^{100}$) and thus cannot be used in practice. Of all algorithms…

Data Structures and Algorithms · Computer Science 2025-08-05 Oded Schwartz , Eyal Zwecher

Let n be any odd natural number other than a perfect square, in this article it is demonstrated that this new factorization algorithm is much more efficient than the implementation technique [2,3 p.1470], described in this article, of the…

General Mathematics · Mathematics 2025-08-27 Savino Detto

A polynomial transform is the multiplication of an input vector $x\in\C^n$ by a matrix $\PT_{b,\alpha}\in\C^{n\times n},$ whose $(k,\ell)$-th element is defined as $p_\ell(\alpha_k)$ for polynomials $p_\ell(x)\in\C[x]$ from a list…

Information Theory · Computer Science 2011-07-14 Aliaksei Sandryhaila , Jelena Kovacevic , Markus Pueschel

The technique for hardware multiplication based upon Fourier transformation has been introduced. The technique has the highest efficiency on multiplication units with up to 8 bit range. Each multiplication unit is realized on base of the…

Hardware Architecture · Computer Science 2016-11-17 Danila Gorodecky

The problem of efficient multiplication of large numbers has been a long-standing challenge in classical computation and has been extensively studied for centuries. It appears that the existing classical algorithms are close to their…

Polynomial factorization over $ZZ$ is of great historical and practical importance. Currently, the standard technique is to factor the polynomial over finite fields first and then to lift to integers. Factorization over finite fields can be…

Symbolic Computation · Computer Science 2024-10-22 Shahriar Iravanian

The works presented in this habilitation concern the algorithmics of polynomials. This is a central topic in computer algebra, with numerous applications both within and outside the field - cryptography, error-correcting codes, etc. For…

Symbolic Computation · Computer Science 2026-03-09 Bruno Grenet

We present a FFT-based algorithm for the computation of a polynomial's coefficients from its roots, and apply it to obtain the coefficients of interpolation polynomials, to invert Vandermondians and to evaluate the symmetric functions of a…

Numerical Analysis · Mathematics 2016-08-05 Hans-Rudolf Thomann

The Fast Fourier Transform (FFT) is an algorithm of paramount importance in signal processing as it allows to apply the Fourier transform in O(n log n) instead of O(n 2) arithmetic operations. Graph Signal Processing (GSP) is a recent…

Numerical Analysis · Computer Science 2017-06-19 Luc Le Magoarou , Rémi Gribonval , Nicolas Tremblay

Let $k\ge 1$ be an integer, and let $P= (f_1(x), \ldots, f_k(x) )$ be $k$ admissible linear polynomials over the integers, or \textit{the pattern}. We present two algorithms that find all integers $x$ where $\max{ \{f_i(x) \} } \le n$ and…

Number Theory · Mathematics 2021-05-31 Jonathan P. Sorenson , Jonathan Webster

The nonlinear Fourier transform (NFT) has recently gained significant attention in fiber optic communications and other engineering fields. Although several numerical algorithms for computing the NFT have been published, the design of…

Signal Processing · Electrical Eng. & Systems 2019-10-17 Shrinivas Chimmalgi , Peter J. Prins , Sander Wahls