How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Vector addition and scalar multiplication are continuous in a normed space
Statement
Let be a normed space over or . Then
and
are continuous for the product topology on the domain and the norm topology on the target.
Facts & Assumptions
Given: Scalars and vectors .
The scalar field on this page is either with its usual absolute value or with its modulus, and the same norm estimates are valid in both cases (Real and complex scalar conventions for normed spaces).
The norm is -Lipschitz for its metric, so in particular for all vectors and (The reverse triangle inequality in a normed space).
Proof
For addition, by [L2].
For scalar multiplication, , so by the triangle inequality and absolute homogeneity from [L1] and [L2].
Given , step 1.1 shows that if and , then lies in the -ball around ; this is continuity of addition at .
For scalar multiplication at , first require and then choose so that ; step 1.2 then gives whenever and .
Since the point was arbitrary, step 2.1 proves continuity of addition everywhere, and step 2.2 proves continuity of scalar multiplication everywhere.
Depends on
- Real and complex scalar conventions for normed spaces
- The reverse triangle inequality in a normed space
- Continuity of a map of topological spaces at a point and globally
- The product set $\prod_{i \in I} X_i$ of functions choosing a point in each factor, the projections, the box topology, and the product topology as the initial topology of the projections; the empty product is a one-point space
- The absolute value makes $\mathbb{R}$ a metric space: $d(x,y) = |x-y|$ is a metric, its open balls are the intervals $(x-r, x+r)$, and it is unbounded
- $\mathbb C$ is the real coordinate plane, with coordinate arithmetic
Used by
Dependency tree · two levels
32 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Theo Buhler and Dietmar A. Salamon, Functional Analysis (standard reference, not scraped)
- Andrew Lin and Casey Rodriguez, MIT 18.102 Introduction to Functional Analysis (standard reference, not scraped)