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Relative entropy D(p∥q)D(p\|q)D(p∥q) (Definitions 10.5.1–10.5.2)

Definition
WildeQIT_relEntropy

by aadarwal · Sep 7, 2026 · Mathlib 0df444a (Lean v4.33.1)

classical-informationentropyinformation-theorywilde-qit

Definition 10.5.1 (Support). Let X\mathcal{X}X be a finite set. The support of a function f:X→Rf:\mathcal{X}\to\mathbb{R}f:X→R is the subset of X\mathcal{X}X on which fff is non-zero: supp⁡(f)≡{x:f(x)≠0}\operatorname{supp}(f)\equiv\{x : f(x)\neq 0\}supp(f)≡{x:f(x)=0}.

Definition 10.5.2 (Relative entropy). Let ppp be a probability distribution on the alphabet X\mathcal{X}X and let q:X→[0,∞)q:\mathcal{X}\to[0,\infty)q:X→[0,∞). The relative entropy D(p∥q)D(p\|q)D(p∥q) is

D(p∥q)≡{∑xp(x) log⁡(p(x)/q(x))if supp⁡(p)⊆supp⁡(q),+∞otherwise,D(p\|q) \equiv \begin{cases} \displaystyle\sum_{x} p(x)\,\log\bigl(p(x)/q(x)\bigr) & \text{if } \operatorname{supp}(p)\subseteq\operatorname{supp}(q),\\[6pt] +\infty & \text{otherwise,}\end{cases}D(p∥q)≡⎩⎨⎧​x∑​p(x)log(p(x)/q(x))+∞​if supp(p)⊆supp(q),otherwise,​

with the logarithm base 222 and the convention that terms with p(x)=0p(x)=0p(x)=0 contribute 000.

The relative entropy is the fundamental divergence of information theory: mutual information and conditional mutual information are relative entropies between a joint distribution and a product (or Markov) distribution, and its non-negativity (Theorem 10.7.1) and monotonicity under channels (Corollary 10.7.2) are the sources of all entropy inequalities of the chapter. Note that qqq is only required to be a non-negative function, not a probability distribution.

Formalization Note. WildeQIT.relEntropy p q takes p : WildeQIT.FinDist α and an arbitrary real function q : α → ℝ and returns an extended real number (EReal): the real value ∑xp(x)log⁡2(p(x)/q(x))\sum_x p(x)\log_2(p(x)/q(x))∑x​p(x)log2​(p(x)/q(x)) coerced into EReal when Function.support p.prob ⊆ Function.support q (Mathlib's Function.support f = {x | f x ≠ 0} is exactly Definition 10.5.1), and ⊤ (=+∞=+\infty=+∞) otherwise. Terms with p(x)=0p(x)=0p(x)=0 vanish automatically (Real.logb 2 0 = 0). Wilde's standing assumption q≥0q\ge 0q≥0 is not built into the definition; theorems about D(p∥q)D(p\|q)D(p∥q) carry it as an explicit hypothesis.

Definition code
import Definitions.Def_WildeQIT_FinDist
import Mathlib.Analysis.SpecialFunctions.Log.Base
import Mathlib.Data.EReal.Basic

/-!
Wilde, *Quantum Information Theory* (2nd ed.), Definition 10.5.1 (Support) and
Definition 10.5.2 (Relative entropy). The support of `f : 𝒳 → ℝ` is `supp(f) = {x : f(x) ≠ 0}`
(Mathlib's `Function.support`). For a probability distribution `p` on `𝒳` and `q : 𝒳 → [0,∞)`,
`D(p‖q) ≡ ∑_x p(x) log (p(x)/q(x))` if `supp(p) ⊆ supp(q)`, and `+∞` otherwise.
-/

namespace WildeQIT

open Classical in
/-- Definition 10.5.2. The relative entropy `D(p‖q)` of a probability distribution `p` on `α`
with respect to a function `q : α → ℝ` (intended non-negative), in bits, as an extended real:
`D(p‖q) = ∑_x p(x) log₂ (p(x)/q(x))` when `supp p ⊆ supp q`, and `+∞` otherwise.
Here `supp f = {x | f x ≠ 0}` (Definition 10.5.1). Terms with `p(x) = 0` contribute `0`. -/
noncomputable def relEntropy {α : Type} [Fintype α] (p : FinDist α) (q : α → ℝ) : EReal :=
  if Function.support p.prob ⊆ Function.support q then
    ((∑ x, p.prob x * Real.logb 2 (p.prob x / q x) : ℝ) : EReal)
  else ⊤

end WildeQIT
Source
Wilde, Quantum Information Theory, 2nd ed. (Cambridge University Press, 2017; arXiv:1106.1445v8), Chapter 10 (Classical Information and Entropy), §Relative Entropy, Definition 10.5.2, LaTeX label def-cie:rel-ent (book source roster-items.csv line 16628); support as in Definition 10.5.1 (line 16617).

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