Norm-induced metric
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On the same real normed vector space, taking the norm of a vector difference defines a metric whose axioms follow universally from the norm axioms.
mko-norm-induced-metric · definition · v0.10.0
Mathematical statement
If (V,norm) is a certified real normed vector space, d(x,y)=norm(x−y) is nonnegative, separates points, is symmetric and satisfies the triangle inequality. This slice uses exact coordinate calculations only for the named l1 and linfinity norms on R^n.
Representative formula (exact TeX)
D(x,y)
Assumptions
- Both points belong to the same finite-dimensional real coordinate space and use the same named norm.
- Induction of the metric follows from the universal formula and norm axioms, not a finite sample of point distances.
Symbol scope
d— norm-induced metricV— real normed vector spacex— first vectory— second vector
Intuition, definition, and misconceptions
Separation follows because norm(x−y)=0 iff x−y=0.
Symmetry follows from norm(−(y−x))=norm(y−x).
The triangle inequality follows from x−z=(x−y)+(y−z) and the norm triangle inequality.
Checking finitely many pairs of distances does not establish that an arbitrary metric is induced by some norm.
Adopted derivation guide
Norm-induced metric: proving from the norm axioms that d(x,y)=‖x−y‖ is a metric, with exact l1 and l∞ computations in ℝ³The original MKO is retained. The guide has its own append-only revision and verification boundaries, not a new Lean proof.
Prerequisites
- Real normed vector space — The induced formula relies on a certified norm.
- Metric space — The conclusion is the metric axioms.
- Plane vectors in a fixed basis — The formula uses a vector difference in the same space.
- Function mapping — The distance must be a total function from V×V to the nonnegative reals.
Verification boundary
Only the induced formula for the same certified norm is handled; not every metric is claimed to be norm-induced, and completeness, an inner product, compactness or finite dimensionality is not inferred from the induced-metric property.
not_formalized
This does not mean the content is false; it means no replayable computational or formal evidence is registered yet.
Next obligation
Together with complete metric spaces, support real Banach spaces.
Same-source structured data
This page and the interactive view use the same object and existing language edition; this adds no proof or human review.
Canonical MKO JSON · Plain Markdown