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Metric space

On this page
  1. Mathematical statement
  2. Representative formula (exact TeX)
  3. Assumptions
  4. Symbol scope
  5. Intuition, definition, and misconceptions
  6. Adopted derivation guide
  7. Prerequisites
  8. Verification boundary
  9. Next obligation
  10. Same-source structured data

This English edition is an AI candidate and does not yet have an OCME Atlas (GPT-6) Twin closure receipt.

A metric space has a carrier set and a distance function that is nonnegative, zero exactly at equal points, symmetric and satisfies the triangle inequality.

mko-metric-space · definition · v0.10.0

Mathematical statement

A metric d:X×X→R on a set X satisfies nonnegativity and separation, symmetry and the triangle inequality. A complete finite distance table permits cell-by-cell and triple-by-triple auditing of a specified candidate.

Representative formula (exact TeX)

d(x,y)

Assumptions

  • Exercises use a finite carrier labeled 0 to n−1 and a complete integer distance table.
  • Finite-table acceptance proves only the specified model; exhaustive finite checks do not extend to arbitrary infinite metric spaces.

Symbol scope

  • d — distance-function candidate
  • x — finite-carrier point
  • y — finite-carrier point

Intuition, definition, and misconceptions

Diagonal entries must be zero and off-diagonal entries must not be zero; together these express separation.

Symmetry requires d(i,j)=d(j,i).

The triangle inequality must be checked for every i,j,k as d(i,k)≤d(i,j)+d(j,k).

Do not call a table a metric after checking only nonnegativity and symmetry or omit off-diagonal zeros and triangle inequalities.

Adopted derivation guide

Metric space: auditing a finite distance table cell by cell and triple by triple

The original MKO is retained. The guide has its own append-only revision and verification boundaries, not a new Lean proof.

Prerequisites

Verification boundary

Only complete finite tables are checked; no arbitrary function space or infinite carrier is covered.

not_formalized

This does not mean the content is false; it means no replayable computational or formal evidence is registered yet.

Next obligation

Add open balls, metric convergence, Cauchy sequences and completeness.

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