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Positive diagonal maps preserve closed convex sets
Statement
Let d>=1, let C be a nonempty closed convex subset of R^d, and let D=diag(d_1,...,d_d) with every d_j>0. Then DC={Dx:x in C} is nonempty, closed, and convex.
Facts & Assumptions
Given: d>=1, C and D as in the Statement.
A convex subset of contains every line segment between two of its points: convexity means every segment between two points of C lies in C.
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: C is closed exactly when its complement is open; an open set contains a positive-radius ball around each of its points.
Open ball, closed ball and sphere in a metric space: B(x,r)={y:||y-x||_2<r}.
The Euclidean inner product on : ||z||2^2=sum{j=1}^d z_j^2.
Finite sums and finite products, by recursion: finite sums are well-defined and obey their finite-sum algebra.
Square roots exist: a unique with ; the positives are : a nonnegative real has a unique nonnegative square root.
Laws of finite sums and finite products: finite sums are additive, obey scaling and splitting, preserve nonnegativity, are monotone termwise, and each nonnegative term is at most the sum.
Squares of nonzero elements are positive: a nonzero square is positive; a zero square is zero.
Inverses of positives are positive, and reciprocation reverses order: the inverse of a positive real is positive; Integer powers defines the negative powers used here.
Squaring is monotone on the nonnegatives: if , then exactly when .
Ordered field: positive elements are closed under addition, so together with recursive Finite sums and finite products, by recursion every nonempty finite sum of positive terms is positive; Sign rules for products and monotonicity of multiplication says multiplication by a positive element preserves order.
Proof
Given: The objects in the Statement.
Choose x_0 in C. Then Dx_0 in DC, so DC is nonempty. If x,y in C and t in [0,1], then by linearity D((1-t)x+ty)=(1-t)Dx+tDy; [F1] puts the left side in DC, so DC is convex.
Fix . Since each , the definition of negative integer powers gives . The square is positive by [F8], so by [F9]. Thus by [F11], and exists by [F6] and is positive. The inverse image is not in . Since is closed, [F2] supplies with disjoint from . For every , Indeed each is nonnegative, is at most its finite sum by [F7], and multiplication by preserves that inequality; summing uses [F7]. Both norms and are nonnegative, so [F10] yields .
If ||w-z||_2<r/M, then step 1.2 gives ||D^{-1}w-x||_2<r, hence D^{-1}w notin C and w notin DC. Therefore B(z,r/M) lies in the complement of DC. Every point outside DC has such a ball, so [F2] makes DC closed; step 1.1 already proved DC nonempty and convex.
Depends on
- A convex subset of $\mathbb{R}^m$ contains every line segment between two of its points
- 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
- Metric space: $d(x,y) = 0$ iff $x = y$, symmetry, and the triangle inequality; pseudometric and ultrametric
- Open ball, closed ball and sphere in a metric space
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- Finite sums and finite products, by recursion
- Integer powers $a^m$
- Square roots exist: a unique $\sqrt{a} \ge 0$ with $(\sqrt{a})^2 = a$; the positives are $\{x^2 : x \neq 0\}$
- Ordered field
- Laws of finite sums and finite products
- Squares of nonzero elements are positive
- Squaring is monotone on the nonnegatives
- Inverses of positives are positive, and reciprocation reverses order
- Sign rules for products and monotonicity of multiplication
Used by
Dependency tree · two levels
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Sources
- Sébastien Bubeck, Convex Optimization: Algorithms and Complexity, complete monograph (standard reference, not scraped)