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Krivine–Stengle Positivstellensatz

Krivine–Stengle Positivstellensatz is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Krivine–Stengle Positivstellensatz rather than just read about it. In short: In real algebraic geometry, Krivine–Stengle Positivstellensatz (German for "positive-locus-theorem") characterizes polynomials that are positive on a semialgebraic set, which is defined by systems of inequalities of polynomials with real coefficients, or more generally, coefficients from any real closed field. It can be thought of as a real analogue of Hilbert's Nullstellensatz (which concern complex zeros of polyno…

Key takeaways

  • Krivine–Stengle Positivstellensatz belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Krivine–Stengle Positivstellensatz to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Krivine–Stengle Positivstellensatz from memory before moving on to harder problems.

Reference excerpt

In real algebraic geometry, Krivine–Stengle Positivstellensatz (German for "positive-locus-theorem") characterizes polynomials that are positive on a semialgebraic set, which is defined by systems of inequalities of polynomials with real coefficients, or more generally, coefficients from any real closed field. It can be thought of as a real analogue of Hilbert's Nullstellensatz (which concern complex zeros of polynomial ideals), and this analogy is at the origin of its name. It was proved by French mathematician Jean-Louis Krivine and then rediscovered by the Canadian Gilbert Stengle.

Statement

Let R be a real closed field, and F = {f1, f2, ..., fm} and G = {g1, g2, ..., gr} finite sets of polynomials over R in n variables. Let W be the semialgebraic set

W = { x ∈ R n ∣ ∀ f ∈ F , f ( x ) ≥ 0 ; ∀ g ∈ G , g ( x ) = 0 } , {\displaystyle W=\{x\in R^{n}\mid \forall f\in F,\,f(x)\geq 0;\,\forall g\in G,\,g(x)=0\},}

and define the preorder (in the sense of a prepositive cone) associated with W as the set

P ( F , G ) = { ∑ α ∈ { 0 , 1 } m σ α f 1 α 1 ⋯ f m α m + ∑ ℓ = 1 r φ ℓ g ℓ : σ α ∈ Σ 2 [ X 1 , … , X n ] ; φ ℓ ∈ R [ X 1 , … , X n ] } {\displaystyle P(F,G)=\left\{\sum _{\alpha \in \{0,1\}^{m}}\sigma _{\alpha }f_{1}^{\alpha _{1}}\cdots f_{m}^{\alpha _{m}}+\sum _{\ell =1}^{r}\varphi _{\ell }g_{\ell }:\sigma _{\alpha }\in \Sigma ^{2}[X_{1},\ldots ,X_{n}];\ \varphi _{\ell }\in R[X_{1},\ldots ,X_{n}]\right\}}

where Σ2[X1,...,Xn] is the set of sum-of-squares polynomials. In other words, P(F, G) = C + I, where C is the cone generated by F (i.e., the subsemiring of R[X1,...,Xn] generated by F and arbitrary squares) and I is the ideal generated by G. Let p ∈ R[X1,...,Xn] be a polynomial. Krivine–Stengle Positivstellensatz states that

(i) ∀ x ∈ W p ( x ) ≥ 0 {\displaystyle \forall x\in W\;p(x)\geq 0} if and only if ∃ q 1 , q 2 ∈ P ( F , G ) {\displaystyle \exists q_{1},q_{2}\in P(F,G)} and s ∈ Z {\displaystyle s\in \mathbb {Z} } such that q 1 p = p 2 s + q 2 {\displaystyle q_{1}p=p^{2s}+q_{2}} . (ii) ∀ x ∈ W p ( x ) > 0 {\displaystyle \forall x\in W\;p(x)>0} if and only if ∃ q 1 , q 2 ∈ P ( F , G ) {\displaystyle \exists q_{1},q_{2}\in P(F,G)} such that q 1 p = 1 + q 2 {\displaystyle q_{1}p=1+q_{2}} . The weak Positivstellensatz is the following variant of the Positivstellensatz. Let R be a real closed field, and F, G, and H finite subsets of R[X1,...,Xn]. Let C be the cone generated by F, and I the ideal generated by G. Then

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Krivine–Stengle Positivstellensatz

Start with the simplest possible case. Write down what Krivine–Stengle Positivstellensatz claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Krivine–Stengle Positivstellensatz before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Krivine–Stengle Positivstellensatz ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Krivine–Stengle Positivstellensatz

In research
Krivine–Stengle Positivstellensatz appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Krivine–Stengle Positivstellensatz in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Krivine–Stengle Positivstellensatz is common in secondary-school and first-year university syllabi. It links to neighbouring topics Algebraic varieties, German words and phrases, Real algebraic geometry, so understanding it makes those chapters shorter.
In everyday life
Look for Krivine–Stengle Positivstellensatz outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Krivine–Stengle Positivstellensatz in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Krivine–Stengle Positivstellensatz means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Krivine–Stengle Positivstellensatz out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Krivine–Stengle Positivstellensatz in simple terms?

In real algebraic geometry, Krivine–Stengle Positivstellensatz (German for "positive-locus-theorem") characterizes polynomials that are positive on a semialgebraic set, which is defined by systems of inequalities of polynomials with real coefficients, or more generally, coefficients from any real c…

Why does Krivine–Stengle Positivstellensatz matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Krivine–Stengle Positivstellensatz?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Krivine–Stengle Positivstellensatz.

Tags

  • Algebraic varieties
  • German words and phrases
  • Real algebraic geometry
  • Theorems in algebraic geometry

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