README.md

SemialgebraicSets

Build Status

Extension of MultivariatePolynomials to semialgebraic sets, i.e. sets defined by inequalities and equalities between polynomials. The following example shows how to build an algebraic set/algebraic variety

julia> using SemialgebraicSets, TypedPolynomials

julia> @polyvar x y z;

julia> @set x*y^2 == x*z - y && x*y == z^2 && x == y*z^4
Algebraic Set defined by 3 equalities
 y - x*z + x*y^2 = 0
 -z^2 + x*y = 0
 x - y*z^4 = 0

julia> algebraic_set([x*y^2 - x*z - y, x*y - z^2, x - y*z^4])
Algebraic Set defined by 3 equalities
 -y - x*z + x*y^2 = 0
 -z^2 + x*y = 0
 x - y*z^4 = 0

The following example shows how to build an basic semialgebraic set.

julia> using SemialgebraicSets, TypedPolynomials

julia> @polyvar x y;

julia> @set x^2 + y^2 <= 1 # Euclidean ball
Basic semialgebraic Set defined by no equality
1 inequality
 1 - y^2 - x^2 ≥ 0


julia> basic_semialgebraic_set(FullSpace(), [1 - x^2 - y^2])
Basic semialgebraic Set defined by no equality
1 inequality
 1 - y^2 - x^2 ≥ 0

julia> @set y^2 == x^3 - x && x <= 0 # Cutting the algebraic variety https://en.wikipedia.org/wiki/Algebraic_variety#/media/File:Elliptic_curve2.png
Basic semialgebraic Set defined by 1 equality
 x + y^2 - x^3 = 0
1 inequality
 -x ≥ 0


julia> basic_semialgebraic_set(algebraic_set([y^2- x^3 - x]), [-x])
Basic semialgebraic Set defined by 1 equality
 -x + y^2 - x^3 = 0
1 inequality
 -x ≥ 0

Solving systems of algebraic equations

Once the algebraic set has been created, you can check whether it is zero-dimensional and if it is the case, you can get the finite number of elements of the set simply by iterating over it, or by using collect to transform it into an array containing the solutions.

V = @set y == x^2 && z == x^3
is_zero_dimensional(V) # should return false
V = @set x^2 + x == 6 && y == x+1
is_zero_dimensional(V) # should return true
collect(V) # should return [[2, 3], [-3, -2]]

The code sample above solves the system of algbraic equations by first computing a Gröbner basis for the system, then the multiplication matrices and then a Schur decomposition of a random combination of these matrices. Additionally, SemialgebraicSets defines an interface that can be implemented by other solvers for these systems as shown in the following subsections.

Solve with HomotopyContinuation.jl

You can solve the system with homotopy continuation as follows:

julia> using HomotopyContinuation

julia> solver = SemialgebraicSetsHCSolver(; compile = false)
SemialgebraicSetsHCSolver(; compile = false)

julia> @polyvar x y
(x, y)

julia> V = @set x^2 + x == 6 && y == x+1 solver
Algebraic Set defined by 2 equalities
 x^2 + x - 6.0 = 0
 -x + y - 1.0 = 0

julia> collect(V)
2-element Vector{Vector{Float64}}:
 [2.0, 3.0]
 [-3.0, -2.0]

Solve with MacaulayLab

You can solve the system with MacaulayLab as follows. First install MacaulayLab.jl and then run the following:

julia> using DynamicPolynomial, MacaulayLab, SemialgebraicSets

julia> solver = MacaulayLab.Solver()
MacaulayLab.Solver()

julia> V = @set x^2 + x == 6 && y == x + 1 solver
Algebraic Set defined by 2 equalities
 x^2 + x - 6.0 = 0
 -x + y - 1.0 = 0

julia> collect(V)
2-element Vector{Vector{Float64}}:
 [2.0000000000000004, 2.999999999999999]
 [-3.0000000000000004, -2.0000000000000004]