Intertwinors from Semistandard Tableaux Span, part 1
Now that we’ve shown the intertwinors that come from semistandard tableaux are independent, we want to show that they span the space . This is a bit fidgety, but should somewhat resemble the way we showed that standard polytabloids span Specht modules.
So, let be any intertwinor, and write out the image
Here we’re implicitly using the fact that .
First of all, I say that if and
, then the coefficients of
and
differ by a factor of
. Indeed, we calculate
This tells us that
Comparing coefficients on the left and right gives us our assertion.
As an immediate corollary to this lemma, we conclude that if has a repetition in some column, then
. Indeed, we can let
be the permutation that swaps the places of these two identical entries. Then
, while the previous result tells us that
, and so
.
Independence of Intertwinors from Semistandard Tableaux
Let’s start with the semistandard generalized tableaux and use them to construct intertwinors
. I say that this collection is linearly independent.
Indeed, let’s index the semistandard generalized tableaux as . We will take our reference tableau
and show that the vectors
are independent. This will show that the
are independent, since any linear dependence between the operators would immediately give a linear dependence between the
for all
.
Anyway, we have
Since we assumed to be semistandard, we know that
for all summands
. Now the permutations in
do not change column equivalence classes, so this still holds:
for all summands
. And further all the
are distinct since no column equivalence class can contain more than one semistandard tableau.
But now we can go back to the lemma we used when showing that the standard polytabloids were independent! The are a collection of vectors in
. For each one, we can pick a basis vector
which is maximum among all those having a nonzero coefficient in the vector, and these selected maximum basis elements are all distinct. We conclude that our collection of vectors in independent, and then it follows that the intertwinors
are independent.
Dominance for Generalized Tabloids
Sorry I forgot to post this yesterday afternoon.
You could probably have predicted this: we’re going to have orders on generalized tabloids analogous to the dominance and column dominance orders for tabloids without repetitions. Each tabloid (or column tabloid) gives a sequence of compositions, and at the th step we throw in all the entries with value
.
For example, the generalized column tabloid
gives the sequence of compositions
while the semistandard generalized column tabloid
gives the sequence of compositions
and we find that since
for all
.
We of course have a dominance lemma: if ,
occurs in a column to the left of
in
, and
is obtained from
by swapping these two entries, then
. As an immediate corollary, we find that if
is semistandard and
is different from
, then
. That is,
is the "largest" (in the dominance order) equivalence class in
. The proofs of these facts are almost exactly as they were before.
Semistandard Generalized Tableaux
We want to take our intertwinors and restrict them to the Specht modules. If the generalized tableau has shape
and content
, we get an intertwinor
. This will eventually be useful, since the dimension of this hom-space is the multiplicity of
in
.
Anyway, if is our standard “reference” tableau, then we can calculate
We can see that it will be useful to know when . It turns out this happens if and only if
has two equal elements in some column.
Indeed, if , then
Thus for some with
we must have
. But then we must have all the elements in each cycle of
the same, and these cycles are restricted to the columns. Since
is not the identity, we have at least one nontrivial cycle and at least two elements the same.
On the other hand, assume in the same column of
. Then
. But then the sign lemma tells us that
is a factor of
, and thus
.
This means that we can eliminate some intertwinors from consideration by only working with things like standard tableaux. We say that a generalized tableau is semistandard if its columns strictly increase (as for standard tableaux) and its rows weakly increase. That is, we allow repetitions along the rows, but only so long as we never have any row descents. The tableau
is semistandard, but
is not.
Intertwinors from Generalized Tableaux
Given any generalized Young tableau with shape
and content
, we can construct an intertwinor
. Actually, we’ll actually go from
to
, but since we’ve seen that this is isomorphic to
, it’s good enough. Anyway, first, we have to define the row-equivalence class
and column-equivalence class
. These are the same as for regular tableaux.
So, let be our reference tableau and let
be the associated tabloid. We define
Continuing our example, with
we we define
Now, we extend in the only way possible. The module is cyclic, meaning that it can be generated by a single element and the action of
. In fact, any single tabloid will do as a generator, and in particular
generates
.
So, any other module element in is of the form
for some
. And so if
is to be an intertwinor we must define
Remember here that acts on generalized tableaux by shuffling the entries by place, not by value. Thus in our example we find
Now it shouldn’t be a surprise that since so much of our construction to this point has depended on an aribtrary choice of a reference tableau , the linear combination of generalized tableaux on the right doesn’t quite seem like it comes from the tabloid on the left. But this is okay. Just relax and go with it.
Modules of Generalized Young Tableaux
We can obviously create vector spaces out of generalized Young tableaux. Given the collection of tableaux of shape
and content
, we get the vector space
. We want to turn this into an
-module.
First, given any tabloid of shape
, we can product a (generalized) tableau
by defining
to be the number of the row in
that contains the entry
. As an example, consider the tabloid
This gives us the function ,
, and
. If
and we use the usual reference tableau
, this gives us the generalized tabloid
The shape of is obviously
, and it’s easy to see that the content is exactly
. Indeed, there are
entries in
with the value
, just as there are
entries in the first row of
.
It should also be clear that this correspondence is a bijection. That is, given any generalized tableau of shape
and content
we can get a tabloid of shape
by turning
into a function and then putting
on row
of
if
.
That means that the basis of generalized tableaux of the vector space
is in bijection with the basis of
-tabloids of the vector space
. And this space carries an action of
— the linear extension of the action on tabloids. We want to pull this action across the bijection we just set up to get an action on
.
On the one hand, this is as easy as saying it: if corresponds to
, we define
to be the generalized tableau corresponding to
and we’re done. To be a bit more explicit, we define
by considering it as a function and setting
So, for example, if
then we can calculate
Even more explicitly, if
then we calculate
We should be clear about a major distinction here: the permutation acts on the entries in
— replacing
by
— but it acts on the places in
— moving
to the position of
.
If we write the correspondence as , then for
to be an intertwinor we need
. This forces
and so this explicit action is forced on us.
The really interesting thing is that when we use this action on the generalized tableaux in , we always get a module
, no matter what shape
we start with.
Generalized Young Tableaux
And now we have another generalization of Young tableaux. These are the same, except now we allow repetitions of the entries.
Explicitly, a generalized Young tableau — we write them with capital letters — of shape
is an array obtained by replacing the points of the Ferrers diagram of
with positive integers. Any skipped or repeated numbers are fine. We say that the “content” of
is the composition
where
is the number of
entries in
.
As an example, we have the generalized Young tableau
of shape and content
.
Notice that if , then
as well, since both count up the total number of places in the tableau. Given a partition
and a composition
, both decomposing the same number
, we define
to be the collection of generalized Young tableaux of shape
and content
. All the tableaux we’ve considered up until now have content
.
Now, pick some fixed (ungeneralized) tableau . We can use the same one we usually do, numbering the rows from
to
across each row and from top to bottom, but it doesn’t really matter which we use. For our examples we’ll pick
Using this “reference” tableau, we can rewrite any generalized tableau as a function; define to be the entry of
in the same place as
is in
. That is, any generalized tableau looks like
and in our particular example above we have ,
, and
. Conversely, any such function assigning a positive integer to each number from
to
can be interpreted as a generalized Young tableau. Of course the particular correspondence depends on exactly which reference tableau we use, but there will always be some such correspondence between functions and generalized tableaux.
The Branching Rule, Part 4
What? More!?
Well, we got the idea to look for the branching rule by trying to categorify a certain combinatorial relation. So let’s take the flip side of the branching rule and decategorify it to see what it says!
Strictly speaking, decategorification means passing from a category to its set of isomorphism classes. That is, in the case of our categories of -modules we should go from the Specht module
to its character
. And that is an interesting question, but since the original relation turned into the dimensions of the modules in the branching rule, let’s do the same thing in reverse.
So the flip side of the branching rule tells us how a Specht module decomposes after being induced up to the next larger symmetric group. That is:
To “decategorify”, we take dimensions
As we see, the right hand side is obvious, but he left takes a little more work. We consult the definition of induction to find
Calculating its dimension is a little easier if we recall what induction looks like for matrix representations: the direct sum of a bunch of copies of , one for each element in a transversal of the subgroup. That is, there are
copies of in the induced representation. We find our new relation:
That is, the sum of the numbers of standard tableaux of all the shapes we get by adding an outer corner to is
times the number of standard tableaux of shape
.
This is actually a sort of surprising result, and there should be some sort of combinatorial proof of it. I’ll admit, though, that I don’t know of one offhand. If anyone can point me to a good one, I’d be glad to post it.
