Direct Sums for Parity Decision Trees

Direct sum theorems state that the cost of solving $k$ instances of a problem is at least $\mathrm{\Omega }(k)$ times the cost of solving a single instance. We prove the first such results in the randomised parity decision tree model. We show that a direct sum theorem holds whenever (1) the lower bound for parity decision trees is proved using the discrepancy method; or (2) the lower bound is proved relative to a product distribution.