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The finite Rényi divergence limit is KL

Statement

For probability vectors P,Q on a finite nonempty alphabet, lim⁡α→1Dα(P∥Q)=D(P∥Q) as a two-sided extended-real limit.

Facts & Assumptions

Given: P,Q as in the Statement.

[F1]

Finite probability vectors: P,Q have nonnegative coordinates summing to one, and P≪Q means px>0 only where qx>0.

[F2]

Finite Kullback–Leibler divergence: D(P∥Q) uses pxlog⁡(px/qx) on positive px, and equals +∞ if P≪̸Q.

[F3]

Finite Rényi divergence: for α≠1 the affinity is Sα(P,Q)=∑qx>0pxαqx1−α, with the specified singular-support conventions.

[F4]

Proof

1.1F1F2F3F4F5F6givenconstructalgebra

Suppose P≪Q. On the finite set supp⁡P, every px,qx is positive. Put rx=px/qx and define S(h):=∑px>0pxrxh for every real h. Then S(h)>0, S(0)=1, and S(h)=S1+h(P,Q) for 0<∣h∣<1 by [F3]. By [F4] and [F5], S′(0)=∑px>0pxlog⁡rx=D(P∥Q). The chain rule [F6] gives (log⁡S)′(0)=D(P∥Q). Since log⁡S(0)=0, the definition of this derivative proves the two-sided limit.

1.2F1F3givenalgebra

Suppose P≪̸Q. Let s:=∑x:qx>0px<1. For 0<α<1, the finite sum in [F3] tends to s as α↑1, because each term with qx>0 tends to px. If s=0, that sum is identically zero and Dα=+∞. If s>0, then log⁡Sα→log⁡s<0 while α−1→0 through negative values, so Dα→+∞ from below order one.

2.1F2F3step 1.2algebra∎

For every α>1, the positive P-mass at a zero Q-coordinate makes Sα=+∞, hence Dα=+∞ by [F3]. Also D(P∥Q)=+∞ by [F2]. The left and right limits therefore both equal the stated extended value.

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