We develop a framework for graph sparsification and sketching, based on a new
tool, short cycle decomposition – a decomposition of an unweighted graph into
an edge-disjoint collection of short cycles, plus few extra edges. A simple
observation gives that every graph G on n vertices with m edges can be
decomposed in O(mn) time into cycles of length at most 2logn, and at most
2n extra edges. We give an m1+o(1) time algorithm for constructing a
short cycle decomposition, with cycles of length no(1), and n1+o(1)
extra edges. These decompositions enable us to make progress on several open
questions:
- We give an algorithm to find (1±ϵ)-approximations to effective
resistances of all edges in time m1+o(1)ϵ−1.5, improving over
the previous best of O~(min{mϵ−2,n2ϵ−1}).
This gives an algorithm to approximate the determinant of a Laplacian up to
(1±ϵ) in m1+o(1)+n15/8+o(1)ϵ−7/4 time.
- We show existence and efficient algorithms for constructing graphical
spectral sketches – a distribution over sparse graphs H such that for a fixed
vector x, we have w.h.p. x′LHx=(1±ϵ)x′LGx and
x′LH+x=(1±ϵ)x′LG+x. This implies the existence of
resistance-sparsifiers with about nϵ−1 edges that preserve the
effective resistances between every pair of vertices up to (1±ϵ).
- By combining short cycle decompositions with known tools in graph
sparsification, we show the existence of nearly-linear sized degree-preserving
spectral sparsifiers, as well as significantly sparser approximations of
directed graphs. The latter is critical to recent breakthroughs on faster
algorithms for solving linear systems in directed Laplacians.
Improved algorithms for constructing short cycle decompositions will lead to
improvements for each of the above results.