# Using inequalities in a polynomial system in Groebner.jl

Groebner.jl is useful for solving a system of polynomial equations. This is about a method of transforming an inequality into an equation, so it could be used with Groebner.jl.

Suppose, for example, I have this simple equation: {\left(x-2\right) \cdot \left(x+3\right)} = 0. It has two solutions, 2 and -3. Now suppose we had this equation in a system together with the inequality 0 \le x. Now there’s only a single solution, 2, because -3 is negative.

To make the above system usable in Groebner.jl, the inequality must be turned into a set of equations. Luckily, I thought, this should be easy: 0 \le x should be equivalent with x = {y^2}, where y is a newly introduced variable, because a square is never negative. Supposing both x and y are real, that is.

This is why I hoped that if I input the equations {\left(x-2\right) \cdot \left(x+3\right)} = 0 and x = {y^2} into Groebner.groebner, I would get a system containing the equation {x-2}=0 as output. This is, however, not the case - Groebner.jl doesn’t seem to be able to eliminate the negative solution. I guess perhaps Groebner.jl doesn’t know that I intend for the variables to be real?

I’m wondering why is that, is it a limitation inherent in the algorithm, and is there another way to solve inequalities with Groebner.jl.

REPL example:

julia> using DynamicPolynomials, Groebner

julia> @polyvar x y
(x, y)

julia> groebner([(x - 2)*(x + 3), x - y^2])
2-element Vector{Polynomial{DynamicPolynomials.Commutative{DynamicPolynomials.CreationOrder}, Graded{LexOrder}, Int64}}:
-x + y²
-6 + x + x²


EDIT: here’s another example, I would expect the output here to be 0 = 1 (“inconsistent system”):

julia> groebner([(x + 2)*(x + 3), x - y^2])
2-element Vector{Polynomial{DynamicPolynomials.Commutative{DynamicPolynomials.CreationOrder}, Graded{LexOrder}, Int64}}:
-x + y²
6 + 5x + x²


@sumiya11 hope you can give some insight

As I know, groebner basis is not used to get numerical results of system of polynomials. In order to get numerical results, real or complex, I suggest HomotopyContinuation.jl

using HomotopyContinuation

@var x y

F = System([(x - 2)*(x + 3), x - y^2])

R = solve(F)

results(R; only_real=true)

2-element Vector{PathResult}:
PathResult:
• return_code → :success
• solution → ComplexF64[2.0 + 0.0im, 1.4142135623730951 + 4.81482486096809e-35im]
• accuracy → 1.066e-16
• residual → 4.4409e-16
• condition_jacobian → 2.1496
• steps → 28 / 0
• extended_precision → false
• path_number → 1

PathResult:
• return_code → :success
• solution → ComplexF64[2.0 + 0.0im, -1.4142135623730951 - 4.81482486096809e-35im]
• accuracy → 1.066e-16
• residual → 4.4409e-16
• condition_jacobian → 1.1471
• steps → 28 / 0
• extended_precision → false
• path_number → 2

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Yeah, but notice that all the manipulations in my post are purely symbolic, I think. It’s just that I picked the simplest possible example to illustrate my point. Thanks regardless, I didn’t know about HomotopyContinuation.jl and it seems interesting.

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Hi @nsajko ,

As far as I know it is not possible to use inequalities together with Gröbner bases to eliminate certain solutions in the way you describe.

If the end goal is obtaining a numerical solution, then in addition to HomotopyContinuation.jl you can perhaps consider AlgebraicSolving.jl.
On the other hand, if the goal is to simplify existing polynomial relations using inequalities, I think Gröbner bases won’t help much.

A subtle detail is that a Gröbner basis contains 1 iff the system has no solutions in \mathbb{C}, and your example has some solutions in \mathbb{C}.

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