AbstractAlgebra.jl

Introduction

AbstractAlgebra.jl is a computer algebra package for the Julia programming language, maintained by William Hart, Tommy Hofmann, Claus Fieker and Fredrik Johansson and other interested contributors.

• Source code

AbstractAlgebra.jl grew out of the Nemo project after a number of requests from the community for the pure Julia part of Nemo to be split off into a separate project. See the Nemo repository for more details about Nemo.

• Nemo repository

Features

The features of AbstractAlgebra.jl include:

• Use of Julia multiprecision integers and rationals
• Finite fields (prime order, naive implementation only)
• Number fields (naive implementation only)
• Univariate polynomials
• Multivariate polynomials
• Relative and absolute power series
• Laurent series
• Fraction fields
• Residue rings, including $\mathbb{Z}/n\mathbb{Z}$
• Matrices and linear algebra

All implementations are fully recursive and generic, so that one can build matrices over polynomial rings, over a finite field, for example.

AbstractAlgebra.jl also provides a set of abstract types for Groups, Rings, Fields, Modules and elements thereof, which allow external types to be made part of the AbstractAlgebra.jl type hierarchy.

Installation

To use AbstractAlgebra we require Julia 1.6 or higher. Please see https://julialang.org/downloads/ for instructions on how to obtain Julia for your system.

At the Julia prompt simply type

julia> using Pkg; Pkg.add("AbstractAlgebra")

Quick start

Here are some examples of using AbstractAlgebra.jl.

This example makes use of multivariate polynomials.

using AbstractAlgebra

R, (x, y, z) = polynomial_ring(ZZ, [:x, :y, :z])

f = x + y + z + 1

p = f^20;

@time q = p*(p+1);

Here is an example using generic recursive ring constructions.

using AbstractAlgebra

R = GF(7)

S, y = polynomial_ring(R, :y)

T, = residue_ring(S, y^3 + 3y + 1)

U, z = polynomial_ring(T, :z)

f = (3y^2 + y + 2)*z^2 + (2*y^2 + 1)*z + 4y + 3;

g = (7y^2 - y + 7)*z^2 + (3y^2 + 1)*z + 2y + 1;

s = f^4;

t = (s + g)^4;

@time resultant(s, t)

Here is an example using matrices.

using AbstractAlgebra

R, x = polynomial_ring(ZZ, :x)

S = matrix_space(R, 10, 10)

M = rand(S, 0:3, -10:10);

@time det(M)

And here is an example with power series.

using AbstractAlgebra

R, x = QQ[:x]

S, t = power_series_ring(R, 30, :t)

u = t + O(t^100)

@time divexact((u*exp(x*u)), (exp(u)-1));