Abstract:
The monotone minimal perfect hash function (MMPHF) problem is the following
indexing problem. Given a set S = {s1, . . . , sn} of n distinct keys from a universe U of size u,
create a data structure D that answers the following query: Rank(q) ={rank of q in S q ∈ S and arbitrary answer otherwise}.

Solutions to the MMPHF problem are in widespread use in both theory and practice.
The best upper bound known for the problem encodes D in O(n log log log u) bits and per-
forms queries in O(log u) time. It has been an open problem to either improve the space upper
bound or to show that this somewhat odd looking bound is tight.

In this paper, we show the latter: any data structure (deterministic or randomized) for
monotone minimal perfect hashing of any collection of n elements from a universe of size u
requires Ω(n · log log log u) expected bits to answer every query correctly.
We achieve our lower bound by defining a graph G where the nodes are the possible (u choose n)
inputs and where two nodes are adjacent if they cannot share the same D. The size of D is then
lower bounded by the log of the chromatic number of G. Finally, we show that the fractional
chromatic number (and hence the chromatic number) of G is lower bounded by 2^Ω(n log log log u).

Streaming video:
[YouTube] (Sepehr @ DIMACS Workshop on Lower Bounds and Frontiers in Data Structures)