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.
Information units and logarithm-base convention
Definition
Write for the natural logarithm of The natural logarithm as the inverse of the exponential function. Unless a base is displayed, every information quantity on this page uses and is measured in nats. For a base and , define The denominator is positive: , is strictly increasing, and by Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm. A base- entropy or divergence is obtained by replacing each in the finite formulas below by ; use and assign to a positive numerator over a zero denominator. The case measures bits; gives nats.
Remarks
All entropies, mutual informations, and conditional mutual informations in this finite-alphabet page are finite. A finite KL divergence can be only when the numerator law has positive mass where the reference law has zero mass. The unit-conversion theorem proves that every base- version is the natural-log value divided by ; no expression subtracts two infinite quantities.
Depends on
Used by
- Huffman expected length is within one bit of entropy Corollary
- Ideal-real arithmetic coding is within two bits per block Corollary
- The finite-register rational coder is within two bits per block Corollary
- Base-two entropy of a finite source Definition
- Conditional mutual information by a same-marginal product law Definition
- Deterministic fixed-length binary block code and block error Definition
- Deterministic Gács–Körner common part and Wyner common information Definition
- Finite conditional entropy Definition
- Finite conditional mutual information Definition
- Finite fixed-length multiterminal lossless code Definition
- Finite mutual information Definition
- Finite-alphabet IID multisource Definition
- Finite-alphabet lossy source coding with decoder-only side information Definition
- Finite-alphabet multiterminal lossy source code Definition
- Ideal-real arithmetic interval coding for a fixed block Definition
- Information density and typical sets for a finite source Definition
- Measure-theoretic mutual information Definition
- Self-information and surprisal variance for a finite law Definition
- A finite deterministic copy has mutual information equal to entropy Example
- Binary entropy and its extremizers Example
- Binary symmetric source: Slepian–Wolf corners and common part Example
- Capacity regimes of the qubit erasure channel Example
- Changing a conditional kernel on a null fiber leaves information unchanged Example
- Coarsening the conditioning variable can increase conditional mutual information Example
- Huffman tree for a dyadic three-symbol source Example
- Finite DMC resolvability by random codebooks Lemma
- Finite joint-typicality packing bound for independent random bins Lemma
- Finite log-sum inequality with support and equality cases Lemma
- Finite random-codebook covering and selected-codeword law Lemma
- Finite-alphabet IID information AEP with a variance bound Lemma
- Information-density concentration for a fixed finite DMC input law Lemma
- Nonnegativity of finite relative entropy with a positive reference Lemma
- Finite information quantities convert by the logarithm base Theorem
- Fixed-length lossless source coding at the entropy rate Theorem
- Ideal-real interval coding is prefix-free and lossless Theorem
- Shannon bounds for finite binary codes Theorem
- The rational finite-register arithmetic code is prefix-free and lossless Theorem
Dependency tree · two levels
14 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
- Robert M. Gray, Entropy and Information Theory, corrected first edition (standard reference, not scraped)
- Yury Polyanskiy and Yihong Wu, Information Theory: From Coding to Learning, author prepublication (standard reference, not scraped)