  The main contribution of this work is to relate information complexity to
"tension" [Prabhakaran and Prabhakaran, 2014] - an information-theoretic
quantity defined with no reference to protocols - and to illustrate that it
allows deriving strong lower-bounds on information complexity. In particular,
we use a very special case of this connection to give a quantitatively tighter
connection between information complexity and discrepancy than the one in the
work of Braverman and Weinstein (2012) (albeit, restricted to independent
inputs). Further, as tension is in fact a multi-dimensional notion, it enables
us to bound the 2-dimensional region that represents the trade-off between the
amounts of communication in the two directions in a 2-party protocol.
  This work is also intended to highlight tension as a fundamental measure of
correlation between a pair of random variables, with rich connections to a
variety of questions in computer science and information theory.
