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The concept of semi-algebraic sets in the context of real closed fields. Semi-algebraic sets are a generalization of algebraic sets and have properties desirable for dealing with decidability and completeness issues. The document defines semi-algebraic sets and proves that their complements and intersections form a boolean algebra of subsets of rn. It also discusses the connection between semi-algebraic sets and logic, and mentions an application to hilbert's 17th problem.
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Algebraic Geometry Lecture 29 – Semi-algebraic geometry
Lee Butler
Algebraic sets are great, but from a logician’s point of view they have a few shortcomings. Specifically, if V is an algebraic set in kn^ then kn^ \ V isn’t an algebraic set, and if we project V down to kn−^1 then in general the result won’t be an algebraic set either. But these are the properties one wants when one is dealing with questions of decidability, completeness, and other things you’ve probably never heard of. And they’re also the properties that semi-algebraic sets do have. The natural setting for semi-algebraic geometry is not algebraically closed fields, but real closed fields.
Definition 1.1. We call a field formally real if −1 is not a sum of squares in the field. A formally real field R is called real closed if no proper algebraic extension of R is formally real.
From now on we’ll fix a real closed field R. You can always think of R = R if you want, or if you keep accidentally writing R instead of R. We’ll define the semi-algebraic sets algebraically and then deal with the logic, since it’s a little easier than doing it the other way around.
Definition 1.2. A subset E ⊆ Rn^ of affine n-space over R is a semi-algebraic set if E is a finite union of sets of the form
{x ∈ Rn^ : f (x) = 0, g 1 (x) > 0 ,... , gk(x) > 0 }
with f, g 1 ,... , gk ∈ R[X 1 ,... , Xn].
Why, you may cry, do we only have one equality and many inequalities, that’s inequality against equality, surely. Well if our basic sets were of the form
{x ∈ Rn^ : f 1 (x) = 0,... , f`(x) = 0, g 1 (x) > 0 ,... , gk(x) > 0 }
then we could replace each of them by
{x ∈ Rn^ : f 12 (x) +... + f (^) `^2 (x) = 0, g 1 (x) > 0 ,... , gk(x) > 0 }
and get back the same sets, since R is a formally real field. We’ll call these sets basic since proofs can often boil down to proving things about them.
Definition 1.3. A boolean algebra of subsets of a set X is a nonempty collection C of subsets of X such that if A, B ∈ C then A ∪ B ∈ C and X \ A ∈ C.
Note in particular that if C is a boolean algebra of subsets of X then ∅, X ∈ C and for any A, B ∈ C we will have A ∩ B ∈ C. (Exercise!)
Lemma 1.4. The set of semi-algebraic sets of Rn^ forms a boolean algebra of the subsets of Rn.
Proof. Obviously if A and B are finite unions of basic sets then A ∪ B will be a finite union of basic sets, at worst the sets forming A and the sets forming B. So we just need to deal with the complement. We’ll show that the intersection of two basic sets is a basic set, and that the complement of a basic set is semi-algebraic, and the rest of the proof is an exercise in set theory. First let A = {x ∈ Rn^ : f (x) = 0, g 1 (x) > 0 ,... , gk(x) > 0 } 1
2
and B = {x ∈ Rn^ : p(x) = 0, q 1 (x) > 0 ,... , q`(x) > 0 }.
Then
A ∩ B = {x ∈ Rn^ : f 2 (x) + p^2 (x) = 0, g 1 (x) > 0 ,... , gk(x) > 0 , q 1 (x) > 0 ,... , q`(x) > 0 }.
So the intersection of basic sets is basic. Now we’ll show that the complement of a basic set is semi-algebraic. Let A be the basic set as above. Then
Rn^ \ A = {x ∈ Rn^ : f (x) 6 = 0 or g 1 (x) 6 0 or... or gk(x) 6 0 }
= {x ∈ Rn^ : f (x) > 0 } ∪ {x ∈ Rn^ : −f (x) > 0 } ∪
( (^) k ⋃
i=
{x ∈ Rn^ : gi(x) = 0}
( (^) k ⋃
i=
{x ∈ Rn^ : −g(x) > 0 }
and this is a finite union of basic sets, hence semi-algebraic.
One can show that sets of the form {x ∈ Rn^ : g(x) > 0 } form a base for a topology on Rn, and so finite unions of sets of this form are called open semi-algebraic sets. However, unlike algebraic geometry where the Zariski topology is of major interest, here we don’t really care about it, instead it’s the boolean algebra that’s important. That’s because semi-algebraic sets have close ties to logic, and through logic they can solve some rather nifty problems.
Here we’ll settle for solving a fairly nondescript problem using this approach, we’re just going to solve Hilbert’s 17th problem!^1 In fact we’ll solve a more general version of his question, which originally was:
Given a multivariate polynomial that takes only non-negative values over the reals, can it be represented as a sum of squares of rational functions?
First we need some field theory and then we’ll get stuck into the logic.
Recall that a (strict) linear order on a set X is a binary relation < such that for every x, y, z ∈ X,
(1) ¬(x < x); (2) x < y and y < z implies x < z; (3) either x < y, x = y, or y < x.
An ordered field is then a field with a linear order that also satisfies
(1) if x < y then x + z < y + z; (2) if x < y and z > 0 then xz < yz.
(^1) !!