Dec. 09, 2019

room 201 building 37

The speaker is Ohad Trabelsi (Weizmann).

We investigate the time-complexity of the All-Pairs Max-Flow problem: Given a graph with n nodes and m edges, compute for all pairs of nodes the maximum-flow value between them. If Max-Flow (the version with a given source-sink pair s, t) can be solved in time T(m), then an O(n^2) · T(m) is a trivial upper bound. But can we do better? 

For directed graphs, recent results in fine-grained complexity suggest that this time bound is essentially optimal. In contrast, for undirected graphs with edge capacities, a seminal algorithm of Gomory and Hu (1961) runs in much faster time O(n)·T(m). Under the plausible assumption that Max-Flow can be solved in near-linear time m^(1+o(1)), this half-century old algorithm yields an nm^(1+o(1)) bound. Several other algorithms have been designed through the years, including \tO(mn) time for unit-capacity edges (unconditionally), but none of them break the O(mn) barrier. Meanwhile, no super-linear lower bound was shown for undirected graphs. 

We design the first hardness reductions for All-Pairs Max-Flow in undirected graphs, giving an essentially optimal lower bound for the node-capacities setting. For edge capacities, our efforts to prove similar lower bounds have failed, but we have discovered a surprising new algorithm that breaks the O(mn) barrier for graphs with unit-capacity edges! Assuming T(m) = m^(1+o(1)) , our algorithm runs in time m^(3/2+o(1)) and outputs a cut-equivalent tree (similarly to the Gomory-Hu algorithm). Even with current Max-Flow algorithms we improve state-of-the-art as long as m = O(n^(5/3−ε)). Finally, we explain the lack of lower bounds by proving a non-reducibility result. This result is based on a new quasi-linear time \tO(m) non-deterministic algorithm for constructing a cut-equivalent tree and may be of independent interest.