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Mutual-information chain rule without subtracting infinities

Statement

Assume AC. For standard-Borel random elements X,Y,Z, I((Z,X);Y)=I(Z;Y)+I(X;Y∣Z). The right side is a sum in [0,+∞]. This chain rule is asserted as an equality of extended nonnegative quantities; no difference of possibly infinite entropies or divergences occurs.

Facts & Assumptions

Given: AC and standard-Borel random elements X,Y,Z on one probability space.

[A1]

AC is required for the Radon–Nikodym divergences and standard-Borel conditional laws. The Axiom of Choice

[F1]

Mutual information is the KL divergence of a joint law from the product of its marginals. Measure-theoretic mutual information

[F2]

Conditional mutual information is the KL divergence from the same-Z-marginal conditionally independent product law. Conditional mutual information by a same-marginal product law

[F3]

For disintegrated joint laws, KL equals the marginal KL plus the average conditional KL, as an extended sum. KL chain rule for standard-Borel disintegrations

[F4]

The same-marginal conditional-product law exists, has the stated rectangle formula, and is independent of kernel versions. The same-marginal conditional-product law is well-defined

[F5]

Standard-Borel joint laws admit the regular conditional distributions and disintegration identities used below. Disintegration of a joint law on standard borel spaces

[F6]

The product of supplied probability kernels is a probability kernel, and KL is invariant under a measurable coordinate bijection. The product of two probability kernels is a probability kernel KL is invariant under a measurable bijection

Proof

Given: The hypotheses in the Statement.

1.1A1F1F4F5F6given

Let K(z,⋅) be a regular conditional law of X given Z and let Q=PZX⊗PY on (Z×X)×Y. In the coordinate order Z,X,Y, Q has Z marginal PZ and conditional law K(z,⋅)⊗PY for (X,Y). On every rectangle C×A×B, the law formed from this base and kernel has mass ∫CK(z,A)PY(B)PZ(dz)=PZX(C×A)PY(B), so it equals Q by rectangle uniqueness.

2.1A1F1F3step 1.1

Apply [F3] to the joint law of (Z,X,Y) and Q using their common Z marginal. With PXY∣z denoting the conditional law of (X,Y) given Z=z, this gives I((Z,X);Y)=D(PZXY∥PZX⊗PY)=∫D(PXY∣z∥PX∣z⊗PY)PZ(dz). The formula is an extended sum of nonnegative KL values.

3.1A1F2F3F5step 2.1

For PZ-almost every z, disintegrate the two measures in step 2.1 over Y. Their Y marginals are PY∣z and PY, while their conditional X laws are PX∣Y,z and PX∣z, respectively. [F3] gives D(PXY∣z∥PX∣z⊗PY)=D(PY∣z∥PY)+∫D(PX∣Y=y,z∥PX∣z)PY∣z(dy). Applying [F3] with the common Y marginal PY∣z identifies the last integral as D(PXY∣z∥PX∣z⊗PY∣z).

4.1A1F2F3F6step 3.1∎

Integrate step 3.1 over PZ. The first term becomes D(PYZ∥PY⊗PZ), which equals I(Z;Y) by the measurable coordinate swap [F6]. Applying [F3] with the common Z marginal of the joint law and its conditional-product reference shows that the second term integrates to I(X;Y∣Z) as defined in [F2]. All terms are nonnegative KL divergences, so their extended sum is well-defined even when one or more are infinite.

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