Balanced Families of Perfect Hash Functions and Their Applications

TL;DR

This paper introduces a new concept of balanced perfect hash function families that ensures nearly uniform distribution of 1-1 functions across subsets, enabling efficient approximation algorithms for counting paths and cycles in graphs.

Contribution

The paper constructs explicit $ ext{delta}$-balanced perfect hash families with near-optimal size and applies them to develop deterministic approximation algorithms for graph path and cycle counting.

Findings

Constructed $ ext{delta}$-balanced perfect hash families of size $2^{O(k \log \log k)} \log n$

Developed polynomial-time algorithms for approximating path and cycle counts with fixed relative error

Applied color-coding technique to utilize hash families in graph algorithms

Abstract

The construction of perfect hash functions is a well-studied topic. In this paper, this concept is generalized with the following definition. We say that a family of functions from $[n]$ to $[k]$ is a $\delta$-balanced $(n,k)$-family of perfect hash functions if for every $S \subseteq [n]$, $|S|=k$, the number of functions that are 1-1 on $S$ is between $T/\delta$ and $\delta T$ for some constant $T>0$. The standard definition of a family of perfect hash functions requires that there will be at least one function that is 1-1 on $S$, for each $S$ of size $k$. In the new notion of balanced families, we require the number of 1-1 functions to be almost the same (taking $\delta$ to be close to 1) for every such $S$. Our main result is that for any constant $\delta > 1$, a $\delta$-balanced $(n,k)$-family of perfect hash functions of size $2^{O(k \log \log k)} \log n$ can be constructed in time $2^{O(k \log \log k)} n \log n$. Using the technique of color-coding we can apply our explicit constructions to devise approximation algorithms for various counting problems in graphs. In particular, we exhibit a deterministic polynomial time algorithm for approximating both the number of simple paths of length $k$ and the number of simple cycles of size $k$ for any $k \leq O(\frac{\log n}{\log \log \log n})$ in a graph with $n$ vertices. The approximation is up to any fixed desirable relative error.