I’m currently teaching a course on spectral graph theory, and I decided to lecture on Margulis’ expander construction and the analysis of its spectral gap by Gabber and Galil. I had never realized how intuitive the analysis could be; the lectures notes I had seen didn’t quite reflect this. In particular, we won’t do any unsightly calculations. Everything I’m about to say is probably well-known, but I thought I would write it down anyway.
The idea is to first start with an initial “expanding object,” and then try to construct a family of graphs out of it. First, consider the infinite graph with vertex set
. The edges are given by two maps
and
, where
and
. So the edges are
and
. Clearly
is not adjacent to anything. Except for the origin, this graph is an expander in the following sense.
Lemma 1 For any subset
, we have
where
denotes the edges leaving
.
The following simple proof is inspired by a paper of Linial and London.
Proof: First consider a subset that does not intersect the coordinate axes. Let
represent the four quadrants of
, and let
. Consider that
and
. The latter fact follows because if
then
. Similarly,
and
and
, while all the respective pairs
and
and
are disjoint.
Combining this with the fact that and
are bijections on
immediately shows that
is at least
Dealing with the coordinate axes is not too hard. Suppose now that is arbitrary. Let
. The preceding argument shows
. We will show that
. Averaging these two inequalities with weights
and
completes the proof.
Let , and
. Then we have the bounds:
The first equation follows since each element of is connected to exactly two elements of
, and each element of
is connected to exactly two elements of
. For instance,
is connected to
and
, while
is connected to
and
.
The second follows because every point of is connected to two unique points of
, e.g.
is connected to
and
. The final inequality follows from the fact that
from our first argument (since
does not touch the axes), and because
has no edges to
. Summing these three inequalities yields
.
Of course, is not a finite graph, so for a parameter
, we define the graph
with vertex set
, where
. There are four types of edges in
: A vertex
is connected to the vertices
This yields a graph of degree at most 8.
Theorem 2 There is a constant
such that for every
,
where
is the second-smallest eigenvalue of the Laplacian on
.
Of course, the graphs now have torsion, and thus our expansion result for
is not, a priori, very useful. The non-trivial idea of the proof is that the torsion doesn’t matter, making Lemma 1 applicable. This is not difficult to show using some Fourier analysis. It turns out to be better though, if we first move to the continuous torus.
Recall that,
Let be the 2-dimensional torus equipped with the Lebesgue measure, and consider the complex Hilbert space
equipped with the inner product .
We might also define a related value,
Note that this is just defined as a number; the eigenvalue notation is merely suggestive, but we have not introduced an operator on the torus.
Claim 1 There is some
such that for any
, we have
\
Proof: We simply sketch a proof, which is rather intuitive. Suppose we are given some map such that
. Define its continuous extension
as follows: Under the natural embedding of
into
, every point
sits inside a grid square with four corners
. Writing a local convex combination
, we define
Now it is elementary to verify that . It is also easy to verify that
for some
. (Even if
, we still get a contribution from
to
on this square because we are taking a weighted average.)
Finally, for any , there is a path of length
in
connecting each of the corners of
‘s square to the corners of
‘s square. A similar fact holds for
. In fact, this is the only place where we need to use the fact that edges of the form
and
are present in
. Thus any contribution
to
can be charged against a term in
, and similarly for
.
Now our goal is to show that . We will use the Fourier transform to “remove the torsion.” The point is that
and
, being shift operators, will act rather nicely on the Fourier basis.
We recall that if and we define
by
, then
forms an orthonormal Hilbert basis for
. In particular, every
can be written uniquely as
where . The Fourier transform is defined as a map
, where
. In particular,
is a linear isometry.
Define and
. Then for any
, we have
In particular, for any , we have
and
. The final thing to note is that
. So now if we simply apply the Fourier transform (a linear isometry) to the expression in (1), we get a reformulation that
is precisely
Here we have simply replaced by
in (1), and then written
.
But now recall our initial infinite graph on
. If we denote by
the Laplacian on
, then we can rewrite this as,
In other words, it is precisely the first Dirichlet eigenvalue on , subject to the boundary condition
.
But now the discrete Cheeger inequality tells us that
where is the minimal expansion of any set not containing the origin. Thus we have indeed unwrapped the torsion and returned to our initial question. Lemma 1 shows that
, yielding the desired lower bound on
.
What does it mean for a graph (or graph family) to have torsion ?
Perhaps it was a poor choice of words–the underlying group
has torsion in the sense that it contains elements of finite order, i.e. non-zero elements
such that
. In general such a non-identity element of a group is called a torsion element. So in this case torsion for the graphs just meant “wrap around.”