  Over the past few years, a family of interesting new inequalities for the
entropies of sums and differences of random variables has been developed by
Ruzsa, Tao and others, motivated by analogous results in additive
combinatorics. The present work extends these earlier results to the case of
random variables taking values in $\mathbb{R}^n$ or, more generally, in
arbitrary locally compact and Polish abelian groups. We isolate and study a key
quantity, the Ruzsa divergence between two probability distributions, and we
show that its properties can be used to extend the earlier inequalities to the
present general setting. The new results established include several variations
on the theme that the entropies of the sum and the difference of two
independent random variables severely constrain each other. Although the
setting is quite general, the result are already of interest (and new) for
random vectors in $\mathbb{R}^n$. In that special case, quantitative bounds are
provided for the stability of the equality conditions in the entropy power
inequality; a reverse entropy power inequality for log-concave random vectors
is proved; an information-theoretic analog of the Rogers-Shephard inequality
for convex bodies is established; and it is observed that some of these results
lead to new inequalities for the determinants of positive-definite matrices.
Moreover, by considering the multiplicative subgroups of the complex plane, one
obtains new inequalities for the differential entropies of products and ratios
of nonzero, complex-valued random variables.
