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A definite quadratic form has a uniform signed bound on the Euclidean unit sphere
Statement
Let and let be a positive definite quadratic form on . Then some satisfies whenever . For a negative definite , some satisfies on the same sphere.
Facts & Assumptions
Given: A definite quadratic form on with .
The Euclidean norm is continuous, and a continuous map has closed preimages of closed sets (The finite and reverse triangle inequalities for a norm; and for every norm on satisfies and is Lipschitz, hence continuous, for , For a map of metric spaces the following agree: - continuity everywhere, preimages of open sets are open, preimages of closed sets are closed, sequential continuity, and ).
Heine--Borel says that a closed bounded Euclidean subset is compact (Heine-Borel in : with the Euclidean metric a subset of is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line).
A continuous real function on a nonempty compact metric space attains its extrema (A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value).
Proof
The unit sphere is nonempty because it contains , closed by [L1], and bounded since it lies in the radius-two ball about zero.
It is compact by [L2].
The finite coordinate formula for makes it continuous; [L3] therefore gives a point where attains its minimum and maximum on the sphere.
In the positive definite case the attained minimum is positive, and in the negative definite case the attained maximum is negative, by the definition of definiteness.
Taking to be the positive minimum or the negative maximum gives the asserted uniform signed bounds.
Depends on
- Positive definite, negative definite, semidefinite, and indefinite quadratic forms
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- Laws of finite sums and finite products
- Triangle inequality for finite sums
- The finite and reverse triangle inequalities for a norm; and for $n \ge 1$ every norm $N$ on $\mathbb{R}^n$ satisfies $N(x) \le C\lVert x\rVert_1$ and is Lipschitz, hence continuous, for $d_2$
- For a map of metric spaces the following agree: $\varepsilon$-$\delta$ continuity everywhere, preimages of open sets are open, preimages of closed sets are closed, sequential continuity, and $f(\overline{A}) \subseteq \overline{f(A)}$
- The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement
- Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space
- The standard list $e : n \to F^{n}$ with $e_i(i) = 1_F$ and $e_i(j) = 0_F$ for $j \ne i$ is an ordered basis of $F^{n}$; hence $\dim_F F^{n} = n$, and $F^{0}$ is the zero space with basis $\varnothing$ and dimension $0$
- Heine-Borel in $\mathbb{R}^n$: with the Euclidean metric a subset of $\mathbb{R}^n$ is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line
- A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value
Used by
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 185 results over 26 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- Analysis, Convexity, and Optimization (standard reference, not scraped)