In this lecture, we generalized our setting to weighted graphs where is a positive weight function on edges. We also looked at the basic spectral theory of the normalized Laplacian, defined by
,
which operates on functions via
.
In particular, we associated with the normalized Rayleigh quotient,
,
and we showed that we can express the second-smallest eigenvalue as
.
We defined the expansion of a subset by
,
where is the characteristic function for .
Finally, we defined the expansion of a graph by
We then stated and (almost) proved the following discrete Cheeger inequality.
Theorem 1. For any weighted graph , we have
,
where .
Exercises (optional)
- Prove that for the normalized Laplacian, just as for the combinatorial Laplacian, the number of connected components in a graph G is precisely the multiplicity of the smallest eigenvalue.
- We saw the the right-hand inequality in Theorem 1 is asymptotically tight. Prove that the left-hand side is asymptotically tight for the complete graph on n nodes.