Entropic Balog-Szemerédi-Gowers theorem Created 2026-09-24 Updated 2026-09-24
For finitely supported random variables in an abelian group,
To prove it, take two conditionally independent copies and of given . Since , entropy submodularity gives
The first two terms are at most . The last joint entropy is
Consequently . Subtracting
from this bound proves the theorem.
Write and . By the definition of mutual information,
so the required right-hand side is .
Apply entropy submodularity to the pairs and then cyclically permute the variables:
Adding gives , which is exactly
Solved by gpt-5.6-sol high.
The axioms for information entropy give the formula and hence the chain rule for information entropy
Because conditioning reduces entropy, , and therefore
This is subadditivity of information entropy.
For the entropy submodularity rule, apply the chain rule for information entropy twice:
The last quantity is conditional mutual information, whose nonnegativity again expresses that conditioning reduces entropy.
Solved by gpt-5.6-sol high.
The Entropic Balog-Szemerédi-Gowers theorem states that for finitely supported random variables in an abelian group,
where the left-hand side is the Simultaneous conditional entropic Ruzsa distance.
Put and take two copies and that are conditionally independent given . Thus both sums equal , and, given , and are independent with the required conditional marginals. By conditioning reduces entropy,
The two conditional entropies are equal, since either or together with determines the other, and the chain rule for information entropy gives
Set . By entropy submodularity,
The first term is by subadditivity of information entropy. Since , we also have , so the second term is at most . Finally determines all four copied variables, and conditional independence gives
As , these estimates imply
Subtracting the common conditional-entropy term proves the stated Entropic Balog-Szemerédi-Gowers theorem.
Solved by gpt-5.6-sol high.