Alternating multilinear forms
1 Permutations
Let be a real vector space. Let be the set of multilinear maps .
Definition 1.
A map is called alternating if with for some implies . Let be the set of alternating elements of .
For a set , let be the group of bijections , and let . For , write .
Definition 2.
For a function and a permutation , define the function by
Theorem 3.
For a function and for ,
Proof.
Define . For and for , we have
Thus
∎
For , define by
called a transposition. Define
called an adjacent transposition. We can write a transposition , , as a product of adjacent transpositions:
Theorem 4.
For ,
Theorem 5.
Let . if and only if for all .
Proof.
(i) Suppose that and let ; we have to show that . Let and for define by
Because is multilinear and alternating, on the one hand
and on the other hand
Therefore
that is,
Thus, as ,
Because is equal to a product of adjacent transpositions, it then follows from Theorem 3 and Theorem 4 that .
(ii) Suppose that for all . Let with for some ; we have to show that . On the one hand,
On the other hand, using that ,
Hence
which implies that . This shows that . ∎
Theorem 6.
Let . If with for some , then .
Proof.
Check that there is some satisfying and . For this ,
But , so . Therefore . ∎
Definition 7.
For , define
Lemma 8.
is a linear map .
Proof.
Let . For , , hence . Namely, is multilinear. It remains to show that it is alternating.
Theorem 9.
Let . if and only if .
2 Wedge products
A permutation is called a -riffle shuffle if
Denote by those elements of that are -riffle shuffles.
Lemma 10.
.
Let be the set of those such that (i) for each , the map
belongs to , and (ii) for , the map
belongs to .
Definition 11.
For define
Theorem 12.
is a linear map .
Proof.
Let , and say with for some .
Let be those such that . For , by Theorem 6,11 1 are distinct and ; they need not be adjacent.
Let be those such that . For , by Theorem 6,
Thus
and
Let be those for which and and let be those for which and . If then
and
so . Likewise, if then . Thus . For , let and , for which and . Then, as ,
Therefore
But , so
Thus . ∎
Definition 13.
For and , define the tensor product by
It is apparent that
and thus it makes sense to write the tensor product without indices.
Definition 14.
Define the wedge product
by, for ,
i.e., for ,
Theorem 15.
For and ,
Proof.
For ,
Let and .
∎
Theorem 16.
For and ,
Proof.
Define by
Then22 2 For example, take and . Then Here
Thus
Let , then for ,
and for ,
But so
thus
which means that . Likewise, if then
and
and because it follows that .
Hence for ,
Thus
∎
Let be the set of those such that (i) for each , the map
belongs to , (ii) for , the map
belongs to , and (iii) for , the map
belongs to .
Let be those such that
Let be those such that
Let be those such that
Lemma 17.
and
Proof.
Let and . Then
and
It follows that
and
and for , , so
Thus . ∎
Define by
and define by
Lemma 18.
For ,
and
and so
Proof.
Theorem 19.
If , , and , then
Proof.
3 Linear forms
Let , the dual space of , whose elements we call linear forms. It is immediate that .
Theorem 20.
If then for ,
Proof.
For the claim is immediate. For , on the one hand, using the definition of the wedge product,
and as the claim is true for . Suppose the claim is true for some and let and . Then, setting , we have
thus the claim is true for . ∎
Let and and put
. The Leibniz formula for the determinant of an matrix tells us
Then Theorem 20 gives
Lemma 21.
If are linearly independent then there are such that
Theorem 22.
are linearly dependent if and only if
Proof.
Suppose are linearly dependent, say, for some , ,
Then, as ,
Suppose that are linearly independent. By Lemma 21, there are such that
Then , and hence
so is not identically . ∎
4 Rk
We now take . For define by
Let for , in other words,
For ,
Theorem 23.
(i) If then for ,
(ii) If then
(iii)
(iv) If then