1. Introduction
Given
E a symplectic vector space of dimension
, the set
of all Lagrangian subspaces of
E is called the Lagrangian Grassmannian of
E. These spaces have a prominent role in symplectic geometry that, in the words of
Dusa McDuff “
Symplectic geometry: is the geometry of closed skew-symmetric form, thus symplectic geometry is essentially topological in nature ”, see [
1]. In this article it is shown that the Lagrangian Grassmannian
has a rich algebraic structure when we assign a coordinate system known as Plücker coordinates. For this we prove the existence of a matrix
, whose kernel contains all the Lagrangian subspaces of
E. This matrix is built with the minimal family of linear form in
that nullify the Lagrangian Grassmannian under Plücker inclusion. another way of seeing
is as a sum of matrices of the family
where
, is a
-matrix, sparce, with
-ones in each row and
-ones in each column where
and
is an index that measures the degree of isotropy in
E. In this paper, we have:
In
Section 3 and
Section 4 we construct a family of homogeneous polynomial equations whose solutions parameterize the elements of
, we call this family of polynomials
Plücker relations of Lagrangian Grassmannian. In
Section 5 and
Section 6 we show that the linear relations of Plücker of the Lagrangian-Grassmannain is the minimal family, up to linear combination, of homogeneous linear polynomials that nullify
.
In
Section 7 calculate the matrix
associated with the linear envelope
of
, we call this
the Plücker matrix of the Lagrangian Grassmannian. We can see that
is the incidence matrix of a family of subsets of the set of indices
and so
is a direct sum of submatrices, each belonging to the set
. Where
is a sparce matrix of zeroes and ones with
k-ones in each row and
-ones in each column.
Section 8 the
isotropy index is studied as an invariant of
and that, among other things, allows us to compare Lagrangian Grassmannian.
De Concini and Lakshmibai [1981] [
2] show that the Lagrangian Grassmannian
is defined by quadratic relations. These relations are obtained by expressing
as a linear section of
, so
, where
is the projectivization of a vector space
such that
, where
is
-representation of highest weight
, and where
see [
3] (pages 182–184), [
2,
4].
The advantage of our approach is that we have the equations
that define
as a projective variety and with this we obtain a totally explicit information of
as a linear section of the Grassmannian
(see Theorem 6) and in this way, we can give a connection with matrix theory and symplectic geometry which opens a computational horizon in these topics. In [
5] we show that the homogeneous linear functionals
also allow us to describe the
k-Grassmannian-Isotropic
, of a symplectic vector space
E of dimension
and we give the Plücker matrix of
which is a generalization of
. The following bibliography is relevant for this research in [
6,
7,
8,
9,
10] we can see a few results about
. See [
9,
11,
12,
13,
14], where you can see some applications of
.
4. Plücker Relations of Lagrangian Grassmannian
For an
m-dimensional vector space
E, denote by
the set of vector subspaces of dimension
ℓ of
E. The Grassmannian
is a algebraic variety of dimension
and can be embedded in a projective space
, where
by Plücker embedding. The
Plücker embedding is the injective mapping
given on each
by choosing a basis
of
W and then mapping the vector subspace
to the tensor
. Since choosing a different basis of
W changes the tensor
by a nonzero scalar, this tensor is a well-defined element in the projective space
, where
. If
, then
if and only if for each pair of tuples
and
, the Plücker coordinates of
w satisfy the
Plücker relations
where
means that the corresponding term is omitted and where
,
, see [
17] (Section 4) and [
19]. Under the inclusion of Plücker the Lagrangian Grassmannian is given by
Lemma 4.
Proof. Using the Definition 1 we clearly have given that for all .
Let then is a family of linearly independent vectors in more over by hypothesis then for all and so . □
The proof of the following lemma is a consequence of the Lemma 2 where the kernel of the contraction map f is characterized as follows
Lemma 5. Let written in Plücker coordinates, then we havewhere disappears from the equation if For all
we define a homogeneous linear polynomial
where
Remark 1. Throughout this article, we write the Equation (16) simply aswhere the addend disappears from the Equation (17) if Corollary 1. is independent of the symplectic basis and Proof. From the Lemma 2, we have so then since is an isomorphism and then . □
Following [
20] for definitions of algebraic set, we have below that
,
and
are algebraic sets in
So we have to
is an algebraic set of
see (
14).
Theorem 1. Let E symplectic vector space of dimension thenwhere and are as in (14) and (16), respectively. Proof. Of Lemma 4, (
20) and (
19) we have
□
Definition 2. To the set of homogeneous polynomialswhere , , we call it relations of Pücker of Lagrangian Grassmannian. To the set of linear homogeneous polynomialswe call it linear relations of Plücker of the Lagrangian Grassmannian. Example 1. In the case we have the relations of Plücker of Lagrangian Grassmannian Example 2. The linear relations of Plücker of are Example 3. In the case it was shown in [21] (example 4) that linear relations consists of 28 homogeneous linear equations in 70 variables. Ideal of
The ideal of
in
is defines by
Proposition 1. If the field of definition of the symplectic vector, space E is algebraically closed thenso is a projective variety. Proof. By the Theorem 1 we have
and by Hilbert’s Nullstellensatz theorem, see [
20] (Theorem 1.3 A), the result is fulfilled. □
Let
be a finite field with
q elements, and denote by
an algebraic closure of
. For a vector space
E over
of finite dimension
k, let
be the corresponding vector space over the algebraically closed field
. We will be considering algebraic varieties in the projective space
. Recall that a projective variety
is defined over the finite field
if its vanishing ideal can be generated by polynomials with coefficients in
. If
E is a symplectic vector space, of dimension
define over a finite field
, then the rational points of
are defined as the set
where
,
,
and
more over
see [
22] (Prop. 2.14).
We define the ideal
as
where
y
Lemma 6. The ideal is radical
Proof. The ideal
is zero-dimensional since the set of solutions to the homogeneous polynomial equations
given that (
26) implies
moreover
so
, and by Seindeber’s lemma, ver [
23] (Proposition 3.7.15),
is radical. □
Let
a hyperplane of codimension
t, we say that
is a
linear section of the Lagrangian Grassmannian and let
Lemma 7. Suppose the basis field is perfect then the linear section of the Lagrangian Grassmannian satisfies
Proof. Given the then the ideal is zero dimensional, , thus by Seindeber’s lemma we have that the ideal is radical. □
5. Factorable Morphisms
Let
two integers, we define
with the notation (
2) we define
Let
For
be a basic vector and let
generated by the vector
and
In [
16] (Lemma 1.4.38) it shows that there is a one-to-one correspondence between
and
, where
is a symplectic vector space of dimension
, generated by the symplectic basis
, recall
^ means that the term was omitted.
As consequence we have
and
so in Plücker coordinates we have
denotes the basis vector of the dual vector space
and
the basis vector of dual vector space
. Now with this notation we define in generators an injective linear transformation
with
and
.
Definition 3. We say that is factored if for some where and . We say h satisfies the factoring property if there are at least one coefficient and there are at least one element such that
Example 4. The homogeneous linear polynomials given in the Example 2 are factored Proposition 2. Let such that and is factored. Then where .
Proof. then
and
□
We denote by
, where
^ means that the corresponding term is omitted. We define
an element of in
such that
Lemma 8. Let where and see (28) then Proof. Let
be from (
33) we have
and
for
f contraction map, we have
then
where
and as stated before
. Now
iff
, note that with this condition we have
. Renaming
, we have
. Then
for all
, that is
where
for all
□
Remark 2. Note thatfor all . 6. Linear Envelope of
In this section,
E is a symplectic vector space of dimension
.
Remark 3. Sometimes in (37), it is necessary to distinguish the even case from the odd case so we write to n even number and for n odd number. Lemma 9. is a nontrivial vector subspace of
Proof. The proof follows from (
18) given that
, so
is a vector subspace of
. □
Let to the set we call it a hyperplane containing .
Definition 4. The Linear Envelope of is the smallest linear variety that contains in
The proof of the following corollary follows directly from the Definition 4.
Corollary 2.
Proposition 3. Let and a coefficient different from zero of h then it exists such that .
Proof. Suppose that for each you have to this means that then and so then which is a contradiction. Then there are such that . □
For each
, we define
for each
we define
Similarly
for each
and
we define
for each
we define
Corollary 3. Let E symplectic vector space of dimention
- (i)
If even, and let thenwith such that and . - (ii)
If odd, and let thenwith such that and
Proof. The proof follows directly from the Lemma 1 and Proposition 3. □
Lemma 10. Let E symplectic vector space of dimension 4, and such that then for A a non-zero constant and .
Proof. Clearly by Proposition 3 each it is of the form it is easy see that since it satisfies the Equation (24) more over consequently where .
□
Theorem 2. Let E symplectic vector space of dimension , such that and is factored then .
Proof. The proof is by induction on n. If it follows from Lemma 10.
We induction hypothesis is, let symplectic vector space of dimension with and such that then .
If such that and is factored, then by Lemma 2 where then by induction step so . □
Proposition 4. Let such that and satisfies the factoring property from the Definition 3, then or , where and satisfies that for all coefficients moreover .
Proof. The proof is by induction on n. If it follows from Lemma 10.
Induction Step): Let symplectic vector space of dimension with and such that then .
Let
a non-zero coefficient that satisfies the factoring property, from the Definition 3, then there is
but
. Now let
as in (
30). So if
then
where
. We define homogeneous linear polynomials
and
such that
and
so
and
. Note that
, because as we mentioned before
, from (
33) we have that
that is
, since
we obtain
moreover
with
where
then by Proposition 2 we have
then
. Given that
and if
satisfies the factoring property from the Definition 3 continuing recursively in the same way, the process ends in a finite number of steps in
or
, where
and
with
for all coefficients
and
. □
Corollary 4. Let E symplectic vector space of dimension
(a) If odd then
(b) If then such that and satisfies that for all coefficients and
Proof. (a) If
then by Corollary 3
with
such that
and
satisfies the factoring property for all non-zero coefficients of
h then by Proposition 4 we have
(b) If then by Corollary 3 we have where and with such that and . Clearly satisfies factoring property of the Definition 3 for all non-zero coefficients of , so by Proposition 4 we have and each coefficient of satisfies that and . □
For
an arbitrary element where
we say that
For
an arbitrary subset then there are a partition of
of the form
where
to
and
.
where
Lemma 11. Let E symplectic vector space of dimention , non-empty set and such that then .
Proof. Let
and without loss of generality we can assume that
for all
. Now let
We define
then for each
we define
such that
Let
a fixed element,
and
then
Moreover,
implies
so by Corollary 4
given that
is odd number and
we have
so
then
. □
Corollary 5. If even then .
Proof. By Corollary 4(b) and by the Lemma 11, we have . □
Theorem 3. Let E be a symplectic vector space of dimension then
- (I)
- (II)
.
Proof. From the Corollary 4 and Corollary 5 we have
By (I) above, Corollary 2 and (
18) we have
□
Lemma 12. Let a linear transformation such that then .
Proof. we have so that is . □
Corollary 6. Suppose the contraction map f is surjective and suppose is a surjective linear transformation that vanishes then there exists a unique isomorphism such that .
Proof. By Lemma 12 we have
, more over
since both have the same dimension because
f and
G are surjective, then there exists a unique linear isomorphism
h that makes the following diagram commute.
and so we have to
. □
Corollary 7. Suppose the contraction map f is surjective then
- (i)
If H is a matrix of order and maximum rank that annuls , then , where P is an invertible matrix.
- (ii)
Suppose that there exists R matrix such that . Then where P is an invertible matrix.
Proof. The proof of (i) follows directly from the Lemma 6. For the (ii) suppose that
is a rank matrix
such that
, then
and
. If
the affirmation is followed by the previous clause of this lemma. Now suppose that
then
; this implies that
which is a contradiction and therefore
. □
8. Isotropy Index and -Atlas
Definition 7. Let E symplectic vector space of dimension ; we call isotropy index of E.
Let
as Equation (
47) and using notation as in (
13) and
denotes the transposed vector.
Lemma 20. Let f be the contraction map, then .
Proof. Let
and ρ Plücker embedding we denote
, it as in (
13), then by Lemma 2 and by Equation (68) the following diagram commutes i.e.,
so we have
which proves commutativity so
.
□
Corollary 11. is isomorphic to as vector spaces.
Proof. From the Lemma 20 we have , and both have the same dimension so is an isomorphism of vector spaces. □
The following corollary follows directly from the Lemma 20.
Corollary 12. Let E symplectic vector spaces of dimension thenMoreover, . Theorem 5. Let E symplectic vector space of dimension defined over an arbitrary field and the isotropy index.
Then, the following are equivalent:
(a) or
(b)
(c)
(d) and is a base of .
Proof. (a) and (b) are equivalent by [
27] (Theorem 6).
(b) and (c) are equivalent by Corollary 11 and by Corollary 12.
(c) and (d) are equivalent by Theorem 3. □
We say that the embedding rank of is the dimension of the linear envelope .
Lemma 21. Embedding rank of is .
Corollary 13. Let E a symplectic vector space of dimension , let f the contraction map the isotropy index are equivalent
- (1)
f is surjective
- (2)
- (3)
- (4)
char or char
- (5)
is maximum for everything .
Proof. (1) is equivalent (2), (2) is equivalent (3) given that y .
(3) is equivalent (4) is followed from [
27] (Theorem 6) and finally (3) is equivalent (5) is obvious. □
Example 7. By Corollary 12 , the order of is and by Theorem 4, is a submatrix of and it is also easy to see that Example 8. Consider the matrices and in a field . By elementary matrix operations we haveThis matrix we denote by . As we saw in the Example 7, in it is of the formand we denote by . In [
18] (Corollary 1.2) can find a more general case of Theorem 5 also see [
28] for some examples where
, and 7.
Let E be a symplectic vector space of dimension
and let
consider the family of matrices given in (53)
and we call the
-atlas of
.
Lemma 22. Let n integer and let E and symplectic vector spaces of dimension and , respectively, then Proof. If both m and n are even integers or if both m and n odd integers then .
Suppose that n is even integer and is odd integer. If then so what it implies so .
If then . Now if then □
Corollary 14. (a) If E and both are symplectic vector spaces of dimension so they share the same -atlas.
(b) Let E symplectic vector space of dimension and let symplectic vector space of dimension then both spaces share the same -atlas.
Proof. The proof follows directly from the Lemma 22. □
Example 9. Let and two symplectic vector spaces of dimension defined over a field and isotropy index . If char=0 or char then and they share
(a) the same isotropy index ;
(b) the same -atlas ;
(c) the same Plücker relations of the Lagrangian Grassmannian variety.
Example 10. Consider the symplectic vector spaces and , two symplectic vector space non-symplectomorphisms, them
(a) They share the same isotropy index .
(b) They share the same Plücker relations of the Lagrangian Grassmannian variety.
However, they do not share the same 4-atlas so we have:
the 4-atlas of is see Example 5
but the 4-atlas of is see Example 8.
Hypersurfaces in
The linear sections of the Lagrangian-Grassmannian
have applications in other fields of mathematics see [
14]. Using the notation
we define the following linear varieties.
Definition 8. Let even integer then
- (a)
- (b)
Let odd integer then
- (c)
- (d)
Theorem 6. Let E be a symplectic vector space of dimension then is intersection of linear sections of the Grassmannian variety and is included in a projective space of a direct sum of matrix kernels
- (A)
If even integer and let , then - (B)
If odd integer and let , then