Research notes on every problem, and a library of the papers behind them. Built from the open erdos repository.
Updated
In the corrected range of lemma_2, for every ,
Since , this implies the source-strength error . This is an explicitly compilation-supplied alternative, using the source's product law and moment estimates; it is not the printed conditional-entropy proof. The latter is reconstructed at conditional_entropy.
Bears on. Problem 297.
Proof
Put and . The product law assigns to a subset the exact probability
The second identity follows by expanding the entropy of each Bernoulli variable and using . Let . Berry–Esseen gives a fixed positive probability, say at least , to for large : subtract the two distribution functions at normalized values 0 and . The error is and .
Each atom in this window has, by (1), probability at most . There must therefore be at least such atoms. Since , this proves the bound for . Intersect each set with . Positivity of the reciprocal weights preserves the inequality , and each image has at most preimages. This gives the stated bound.