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A permutation matrix is any
matrix that has exactly one 1 in each row and
column, with all other entries being 0. Here is an example of a
permutation
matrix:
Such a matrix is called a permutation matrix because it is obtained by permuting the rows
or columns of the identity matrix. (This yields a one-to-one correspondence between the set
of
permutation matrices and the set of permutations on
elements. One can verify that multiplying a vector by a permutation matrix
permutes the elements of the vector accordingly.) Every permutation matrix is unitary.
This implies that the eigenvalues of any permutation matrix all lie on the complex unit
circle, and one might wonder how these eigenvalues are distributed when permutation matrices
are chosen at random (that is, uniformly from the set of all
permutation matrices). Some work has already been done in studying the
eigenvalues of permutation matrices. Diaconis and Shahshahani [1] looked at the
trace (sum of the eigenvalues), and Wieand [6], [5] investigated the number
of eigenvalues that lie in a fixed arc of the unit circle. In both cases, the asymptotic
behavior for large
was determined.
Roughly speaking, the number of eigenvalues that lie in a fixed interval on the unit
circle will be proportional to the length of the interval and to the dimension
of the
matrix. In this project, the idea was to allow
to increase while decreasing the size
of the interval, so that the number of eigenvalues lying in it should remain fairly
constant on average. In particular, for fixed positive constants
and
,
we looked at the number of eigenvalues
lying in
the half-open interval
when an
permutation matrix is chosen at random, and we
found the limit of the mean of
as
for certain values of
(including all rational points and certain "well-behaved" irrational points).
Next: Eigenvalues vs. Independent Points
Up: Index
Previous: Index
Nathaniel Blair-Stahn
2003-08-29