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.
The Prüfer decoding procedure is well defined and produces a labelled tree
Statement
Let be finite with , and let be a word on the label set . The following procedure is well defined and produces a tree on :
At stage , choose the least unused label absent from the remaining word , join it to , and mark it used. After all symbols are processed, join the two unused labels.
Facts & Assumptions
Given: A word on a finite set of cardinality (The cardinality of a finite set).
A word with positions cannot contain more than distinct labels. Thus among available labels at least two are absent; every nonempty set of natural labels has a least element (The pigeonhole principle on , The well-ordering principle).
A tree is a connected acyclic graph (Trees, forests, leaves and isolated vertices).
Induction applies to the decoding stages (The principle of mathematical induction).
Proof
Before any word entry is processed, the graph has singleton components indexed by , each containing exactly one unused label.
Assume that after stages the built edges form a forest and every component contains exactly one unused label.
There are unused labels and entries in the remaining word. Hence at least two unused labels are absent from that word, so the least such label exists. Every label used at an earlier stage was absent from the then-remaining word and hence from its current suffix, so is unused; because occurs in the remaining word, .
The label lies in a component different from the component containing : by the induction hypothesis each component contains exactly one unused label, and . Adding and marking used joins those components without a cycle and leaves exactly one unused label in the new component. Thus the invariant holds after stage .
Induction gives the invariant after all word stages. Exactly two unused labels and two components remain; joining those labels makes the graph connected without creating a cycle.
The output uses all labels in and is connected and acyclic, hence is a labelled tree on .
Depends on
- The Prüfer code of a tree on a finite set of natural labels
- Trees, forests, leaves and isolated vertices
- Adding an edge between two nonadjacent vertices of a tree creates exactly one cycle
- The pigeonhole principle on $\mathbb{N}$
- The well-ordering principle
- The principle of mathematical induction
- The cardinality $\lvert A\rvert$ of a finite set
Used by
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 46 results over 25 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
- ISI Bangalore discrete mathematics notes, Trees and Cayley’s theorem (standard reference, not scraped)