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This paper considers fast algorithms for operations on linearized polynomials. We propose a new multiplication algorithm for skew polynomials (a generalization of linearized polynomials) which has sub-quadratic complexity in the polynomial…

Symbolic Computation · Computer Science 2017-07-12 Sven Puchinger , Antonia Wachter-Zeh

We construct a family of root-finding algorithms which exploit the branched covering structure of a polynomial of degree $d$ with a path-lifting algorithm for finding individual roots. In particular, the family includes an algorithm that…

Dynamical Systems · Mathematics 2025-10-20 Myong-Hi Kim , Scott Sutherland

An input- and output-sensitive GCD algorithm for multi-variate polynomials over finite fields is proposed by combining the modular method with the Ben-Or/Tiwari sparse interpolation. The bit complexity of the algorithm is given and is…

Symbolic Computation · Computer Science 2022-07-29 Qiao-Long Huang , Xiao-Shan Gao

In calculating integral or discrete transforms, use has been made of fast algorithms for multiplying vectors by matrices whose elements are specified as values of special (Chebyshev, Legendre, Laguerre, etc.) functions. The currently…

Numerical Analysis · Mathematics 2022-08-11 Andrew V. Terekhov

In the paper it is shown that there exist infinite classes of fast DFT algorithms having multiplicative complexity lower than O(NlogN), i.e. smaller than their arithmetical complexity. The derivation starts with nesting of Discrete Fourier…

Signal Processing · Electrical Eng. & Systems 2023-03-07 Ryszard Stasinski

In this work a rationalized algorithm for calculating the quotient of two complex numbers is presented which reduces the number of underlying real multiplications. The performing of a complex number division using the naive method takes 4…

Data Structures and Algorithms · Computer Science 2016-08-31 Aleksandr Cariow

In this paper, an exact algorithm in polynomial time is developed to solve unrestricted binary quadratic programs. The computational complexity is $O\left( n^{\frac{15}{2}}\right) $, although very conservative, it is sufficient to prove…

Data Structures and Algorithms · Computer Science 2021-02-02 Juan Ignacio Mulero-Martínez

Symbolic Mathematical tasks such as integration often require multiple well-defined steps and understanding of sub-tasks to reach a solution. To understand Transformers' abilities in such tasks in a fine-grained manner, we deviate from…

Artificial Intelligence · Computer Science 2021-04-30 Vishesh Agarwal , Somak Aditya , Navin Goyal

A method is described which allows to evaluate efficiently a polynomial in a (possibly trivial) extension of the finite field of its coefficients. Its complexity is shown to be lower than that of standard techniques when the degree of the…

Information Theory · Computer Science 2011-02-24 Davide Schipani , Michele Elia , Joachim Rosenthal

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

The article contents suggestions on how to perform the Fast Fourier Transform over Large Finite Fields. The technique is to use the fact that the multiplicative groups of specific prime fields are surprisingly composite.

Number Theory · Mathematics 2011-01-18 Petur Birgir Petersen

We propose an algorithm for quickly evaluating polynomials. It pre-conditions a complex polynomial $P$ of degree $d$ in time $O(d\log d)$, with a low multiplicative constant independent of the precision. Subsequent evaluations of $P$…

Numerical Analysis · Mathematics 2022-11-15 Ramona Anton , Nicolae Mihalache , François Vigneron

This paper shows that it is possible to improve the computational cost, the memory requirements and the accuracy of Quick Fourier Transform (QFT) algorithm for power-of-two FFT (Fast Fourier Transform) just introducing a slight modification…

Data Structures and Algorithms · Computer Science 2013-01-07 Lorenzo Pasquini

We show that assuming the availability of the processor with variable precision arithmetic, we can compute matrix-by-matrix multiplications in $O(N^2log_2N)$ computational complexity. We replace the standard matrix-by-matrix multiplications…

Data Structures and Algorithms · Computer Science 2025-08-19 Maciej Paszyński

Assuming a conjectural upper bound for the least prime in an arithmetic progression, we show that n-bit integers may be multiplied in O(n log n 4^(log^* n)) bit operations.

Symbolic Computation · Computer Science 2017-10-17 David Harvey , Joris van der Hoeven

We associate to each Boolean function a polynomial whose evaluations represents the distances from all possible Boolean affine functions. Both determining the coefficients of this polynomial from the truth table of the Boolean function and…

Information Theory · Computer Science 2014-04-11 Emanuele Bellini

The integer complexity $f(n)$ of a positive integer $n$ is defined as the minimum number of 1's needed to represent $n$, using additions, multiplications and parentheses. We present two simple and faster algorithms for computing the integer…

Data Structures and Algorithms · Computer Science 2023-09-14 Qizheng He

In this paper, we study the arithmetics of skew polynomial rings over finite fields, mostly from an algorithmic point of view. We give various algorithms for fast multiplication, division and extended Euclidean division. We give a precise…

Number Theory · Mathematics 2012-12-17 Xavier Caruso , Jérémy Le Borgne

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

Many large arithmetic computations rely on tables of all primes less than $n$. For example, the fastest algorithms for computing $n!$ takes time $O(M(n\log n) + P(n))$, where $M(n)$ is the time to multiply two $n$-bit numbers, and $P(n)$ is…

Computational Complexity · Computer Science 2015-04-22 Martin Farach-Colton , Meng-Tsung Tsai