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Let , by a partition of
upper and
lower points we mean a partition of the set
, that is, a decomposition of the set of
points into non-empty disjoint subsets, called blocks. The first
points are called upper and the last
points are called lower. The set of all partitions on
upper and
lower points is denoted
. We denote the union
.
We illustrate partitions graphically by putting points in one row and
points on another row below and connecting by lines those points that are grouped in one block. All lines are drawn between those two rows.
Below, we give an example of two partitions and
defined by their graphical representation. The first set of points is decomposed into three blocks, whereas the second one is into five blocks. In addition, the first one is an example of a non-crossing partition, i.e. a partition that can be drawn in a way that lines connecting different blocks do not intersect (following the rule that all lines are between the two rows of points). On the other hand, the second partition has one crossing.
A block containing a single point is called a singleton. In particular, the partitions containing only one point are called singletons and for clarity denoted by an arrow and
.
Let us fix a complex number . Let us denote
the vector space of formal linear combination of partitions
. That is,
is a vector space, whose basis is
.
Now, we are going to define some operations on . First, let us define those operations just on partitions.
Now we can extend the definition of tensor product and composition on the vector spaces linearly. We extend the definition of the involution antilinearly. These operations are called the category operations on partitions.
The set of all natural numbers with zero as a set of objects together with the spaces of linear combinations of partitions
as sets of morphisms between
and
with respect to those operations form a monoidal
-category. All objects in the category are self-dual. This category is called the (linear) category of all partitions.
Suppose the parameter is now a natural number
. For every partition
we define a linear map
as
where ,
and the symbol
is defined as follows. Let us assign the
points in the upper row of
by the numbers
(from left to right) and the
points in the lower row by
(again from left to right). Then
if the points belonging to the same block are assigned the same numbers. Otherwise
.
As an example, we can express and
, where
and
come from the example above, using multivariate
function as follows
We extend this definition to the linear spaces linearly, i.e.
and hence
.
Proposition. The map is a monoidal unitary functor. That is, we have the following
Consider the symmetric group and denote by
its representation by permutation matrices.