This paper explores the structure of vector spaces over residue class rings, analyzing subspace interactions and automorphisms of Grassmann graphs over these rings, revealing their combinatorial properties.
Contribution
It introduces a matrix-based approach to study subspaces over residue class rings and characterizes the automorphisms of Grassmann graphs in this setting.
Findings
01
Grassmann graph $G_{p^s}(n,m)$ is connected and vertex-transitive
02
Valency, clique number, and maximum cliques are determined
03
Automorphisms of the Grassmann graph are characterized
Abstract
Let Zps be the residue class ring of integers modulo ps, where p is a prime number and s is a positive integer. Using matrix representation and the inner rank of a matrix, we study the intersection, join, dimension formula and dual subspaces on vector subspaces of Zpsn. Based on these results, we investigate the Grassmann graph Gps(n,m) over Zps. Gps(n,m) is a connected vertex-transitive graph, and we determine its valency, clique number and maximum cliques. Finally, we characterize the automorphisms of Gps(n,m).
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TopicsFinite Group Theory Research · Coding theory and cryptography · Advanced Topics in Algebra
Full text
Vector spaces and Grassmann graphs
over residue class rings***L. Huang is supported by NSFC (11371072), B. Lv is supported by NSFC (11501036, 11301270), K. Wang is supported by NSFC
( 11671043, 11371204). Supported by the
Fundamental Research Funds for the Central University of China.
a *School of Math. and Statis.,
Changsha University of Science and
Technology, Changsha, 410004, China
b* *Sch. Math. Sci. &
Lab. Math. Com. Sys., Beijing Normal University, Beijing, 100875,
China *
Abstract
Let Zps be the residue class ring of integers modulo ps, where p is a prime number and s is a positive integer.
Using matrix representation and the inner rank of a matrix, we study the intersection, join, dimension formula and dual subspaces on
vector subspaces of Zpsn. Based on these results, we investigate the Grassmann graph Gps(n,m) over Zps.
Gps(n,m) is a connected vertex-transitive graph, and we determine its valency, clique number and maximum cliques. Finally,
we characterize the automorphisms of Gps(n,m).
Keywords: residue class ring, subspace, dimension formula, Grassmann graph, maximum clique, automorphism
Throughout, let R be a commutative local ring and R∗ the set of all units of R. For a subset S of R, let Sm×n be the set of all m×n matrices over S,
and Sn=S1×n. Denote by Ir (I for short) the r×r identity matrix. For A∈Rm×n and B∈Rn×m,
if AB=Im, we call that A has a right inverse and B is a right inverse of A. Similarly, if AB=Im, than B
has a left inverse and A is a left inverse of B. The cardinality of a set X is denoted by ∣X∣.
A 1×n matrix over R is called an n-dimensional vector over R.
For αi∈Rn, i=1,…,k, the vector subset {α1,…,αk} is called unimodular if the matrix
\scriptsize\left(\begin{array}[]{c}\alpha_{1}\\
\vdots\\
\alpha_{k}\\
\end{array}\right) has a right inverse.
Let V⊆Rn be a linear subset (i.e., an R-module). A largest unimodular vector set of V is a unimodular vector subset of V
which has maximum number of vectors. The dimension of V, denoted by dim(V), is the number of vectors in a largest unimodular vector set of V.
A linear subset X of Rn is called a k-dimensional vector subspace (k-subspace or subspace for short) of Rn,
if X has a basis {α1,α2,…,αk} being unimodular.
Every basis of a subspace can be extended to a basis of Rn (cf. [19, Corollary I.5]). We define the [math]-subspace to be {0}.
Let Zps denote the residue class ring of integers modulo ps, where p is a prime and s is a positive integer.
The Zps is a Galois ring, a commutative local ring, a finite principal ideal ring (cf. [18, 23]),
and a Hermite ring (according to Cohn’s definition [4, 5]). The principal ideal (p) is the unique maximal ideal of Zps,
and denoted by Jps. The Jps is also the Jacbson radical [1, 4] of Zps.
When s=1, Zp is a finite field.
For any x∈Zps, x is invertible (i.e., a unit) if and only if x∈/Jps.
We have (cf. [18, 23]) that
[TABLE]
The residue class ring Zps plays an important role in mathematics and information science. However, since there are zero divisors,
the properties of the vector spaces over Zps are essentially different from the vector spaces over a finite field.
For example, the intersection of two vector subspaces over Zps may not be a vector subspace (cf. Section 3 below).
This brings difficulty to study of geometry and graph theory on Zps. By using matrix representation and the inner rank [5] of a matrix,
we will discuss the basic properties of vector spaces over Zps. For example, intersection, join, dimension formula and
dual subspaces of Zpsn.
Recently, some scholars studied some graphs (for instance, symplectic graphs and bilinear forms graph) on Zps or a finite commutative ring
(cf. [10, 14, 15, 16, 20]). Note that the Grassmann graph over a finite field plays an important role in geometry [22, 24, 25],
graph theory [3] and coding theory [7, 8, 22]. Thus, the study of Grassmann graph over
Zps has good significance for geometry, combinatorics and coding theory.
We define the Grassmann graph over Zps as follows.
Suppose m,n are integers with 1≤m<n. The Grassmann graph over Zps, denoted by Gps(n,m), has vertex set the set all m-subspaces
of Zpsn, and two vertices are adjacent if their intersection is a linear subset of dimension m−1. Based on our results on vector subspaces of Zpsn,
we will study Grassmann graph over Zps and its automorphisms.
The paper is organized as follows. In Section 2, we recall the basic properties of matrices over Zps and the bilinear forms graphs over Zps.
In Section 3, we will discuss vector subspaces of Zpsn. For example, intersection, join and dimension formula of
two vector subspaces of Zpsn; dual subspaces and arithmetic distances of subspaces.
In Section 5, we show that the Grassmann graph Gps(n,m) is a connected vertex-transitive graph, and
determine its valency, clique number and maximum cliques. In Section 6, we characterize the automorphisms of Gps(n,m).
2 Matrices and bilinear forms graphs over Zps
In this section, we recall some basic properties of matrices over Zps. For instance, matrix factorization,
the inner rank and McCoy rank of matrix over Zps. We also introduce the bilinear forms graph over Zps.
2.1 Matrices
Let GLn(R) be the set of n×n invertible matrices over R.
For A∈Rm×n, let tA denote the transpose matrix of a matrix A and det(X) the determinant [2] of a
square matrix X over R.
Let 0m,n ([math] for short) be the m×n zero matrix.
Denote by Eijm×n (Eij for short) the m×n matrix whose (i,j)-entry is 1 and all other entries are [math]’s.
Let diag(A1,…,Ak) denote a block diagonal matrix where Ai is an mi×ni matrix.
For 0=A∈Rm×n, by Cohn’s definition [5], the inner rankρ(A) of A, is the least integer r such that
[TABLE]
Let ρ(0)=0. Any factorization such that as (2.1) where r=ρ(A) is called a minimal factorization of A.
For A∈Rm×n, it is clear that ρ(A)≤min{m,n} and ρ(A)=0 if and only if A=0.
When R is a field, we have ρ(A)=rank(A), where rank(A) is the usual rank of matrix A over a field.
For matrices over R, the followings hold (cf. [5, 4, Section 5.4]):
[TABLE]
[TABLE]
[TABLE]
[TABLE]
Denote by Ik(A) the ideal in R generated by all k×k minors of A, k=1,…,min{m,n}.
Let AnnR(Ik(A))={x∈R:xIk(A)=0} denote the annihilator of Ik(A). The McCoy rank of A, denoted by rk(A), is the following integer:
[TABLE]
We have that rk(A)=rk(tA);
rk(A)=rk(PAQ) where P and Q are invertible matrices of the appropriate sizes; and rk(A)=0 if and only if AnnR(I1(A))=(0) (cf. [2, 17]).
Since Zps is an Hermite ring (according to Cohn’s definition [4]),
every matrix over Zps which has right inverse is completable (i.e., it can be extended to an invertible matrix over Zps).
Since Zps is a commutative local ring, a matrix \scriptsize\left(\begin{array}[]{c}\alpha_{1}\\
\vdots\\
\alpha_{m}\\
\end{array}\right)\in\mathbb{Z}_{p^{s}}^{m\times n} has a right inverse if and only if α1,…,αm are m linearly independent vectors over Zps.
Lemma 2.1
(cf. [21, Chap. II]), or [18, p.327], or [14, Lemma 2.3])* Let R=Zps, and let A∈Rm×n be a non-zero matrix.
Then there are P∈GLm(R) and Q∈GLn(R) such that*
[TABLE]
where 1≤k1≤⋯≤kt≤max{s−1,1}. Moreover, the parameters (r,t,k1,…,kt) are uniquely determined by A.
In (2.6), Ir or diag(pk1,…,pkt) may be absent.
Lemma 2.2
(see [14, Lemmas 2.4 and 2.7])* Let 0=A∈Zpsm×n (s≥2) be of the form (2.6). Then r+t is the inner rank of A,
and r is the McCoy rank of A.*
Let A∈Zpsm×n (s≥2). By Lemma 2.2, rk(A)≤ρ(A), and
rk(A)=0 if and only if A∈Jpsm×n.
For matrices A,B,C over Zps, By Lemmas 2.1 and 2.2, it is easy to see that (cf. [14])
[TABLE]
[TABLE]
Lemma 2.3
(see [2, Corollary 2.21])* Let A∈Zpsn×n.
Then A∈GLn(Zps) if and only if det(A)∈Zps∗.*
Note that if a∈Zps∗ and b∈Jps, then a±b∈Zps∗.
Lemma 2.1 implies the following lemma.
Lemma 2.4
(cf. [14, Lemma 2.10])* Let A∈Zpsm×n where s≥2 and n≥m. Then rk(A)=rk(A±B) for all B∈Jpsm×n.
Moreover, A has a right inverse if and only if rk(A)=m.*
Let Tp={0,1,…,p−1}⊆Zps.
For two distinct elements a,b∈Tp, we have a−b∈Zps∗.
Without loss of generality, we may assume that Tp=Zp in our discussion.
Lemma 2.5
(see [1, Proposition 6.2.2] or [18, p.328])* Every non-zero element x in Zps can be written as
x=upt where u is a unit and 0≤t≤s−1. Moreover, the integer t is unique and u is unique modulo the ideal (ps−t) of Zps.*
Lemma 2.6
(cf. [18, p.328])* Every non-zero element x in Zps can be written uniquely as*
[TABLE]
By Lemma 2.6,
every matrix X∈Zpsm×n can be written uniquely as
[TABLE]
Note that every matrix in Tpm×n can be seen as a matrix in Zpm×n.
We define the natural surjection
[TABLE]
by π(X)=X0 for all X∈Zpsm×n of the form (2.9). Clearly, π(A)=A if A∈Zpm×n.
For X,Y∈Zpsm×n and Q∈Zpsn×k, We have
[TABLE]
[TABLE]
[TABLE]
Theorem 2.7
Let X∈Zpsm×n(n≥m). Then the following hold:
(i)
rk(X)=rank(π(X)).
(ii)
X* has a right inverse if and only if π(X) has a right inverse.*
(iii)
When n=m, X is invertible if and only if π(X) is invertible. Moreover, if X is invertible, then
[TABLE]
*Proof. *Without loss of generality, we assume that s≥2.
(i). Let rk(X)=r. By Lemma 2.1, there are matrices P∈GLm(Zps) and Q∈GLn(Zps) such that
[TABLE]
where D=diag(pk1,…,pkt), 1≤k1≤⋯≤kt≤s−1.
Using (2.12), we have that π(P) and π(Q) are invertible, and
π(X)=π(P)diag(Ir,0t,0m−r−t,n−r−t)π(Q).
Thus rank(π(X))=r=rk(X).
(ii). If X has a right inverse, then (2.12) implies that π(X) has a right inverse. Conversely, suppose π(X) has a right inverse.
Using (i), we get rank(π(X))=m=rk(X). If follows from Lemma 2.4 that X has a right inverse.
(iii). Suppose that n=m. Similar to the proof of (ii), X is invertible if and only if π(X) is invertible.
Now, let X=X0+X1p+⋯+Xs−1ps−1∈Zpsn×n be invertible, where Xi∈Zpn×n, i=0,…,s−1.
Write X−1=Y0+Y1p+⋯+Ys−1ps−1∈Zpsn×n, where Yi∈Zpn×n, i=0,…,s−1.
Then X0Y0=In, and hence (2.14) holds.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
Lemma 2.8
(see [14, Lemma 4.2])* If A∈GLn(Zps−1) where s≥2, then A∈GLn(Zps).*
Lemma 2.9
(see [14, Lemma 4.3])* If A∈Zps−1m×n where s≥2, then both A and Ap
can be viewed as matrices in Zpsn×n with the same inner rank.*
2.2 Bilinear forms graphs
All graphs in this paper are simple [9] and finite. Suppose G is a graph.
Denote the distance between vertices x and y in G by dG(x,y) (d(x,y) for short).
Let V(G) be the vertex set of G. For x,y∈V(G), we write x∼y if vertices x and y are adjacent.
Recall that a clique of G is a complete subgraph of G. A clique C is maximal if there is no clique of G which properly contains C as a subset.
A maximum clique of G is a clique of G which has maximum cardinality.
The clique numberω(G) of G is the number of vertices in a maximum clique.
For convenience, we regard that a maximal clique and its vertex set are the same.
An independent set of G is a subset of vertices such that no two vertices are adjacent. A largest independent set
of G is an independent set of maximum cardinality. The independence numberα(G) is the number of vertices in a largest independent set of G.
As a natural extension of the bilinear forms graph over a finite field, the bilinear forms graph over Zps was defined as follows (cf. [14]).
The bilinear forms graph over Zps, denoted by Γ(Zpsm×n),
has the vertex set Zpsm×n where m,n≥2, and two vertices A and B are adjacent if ρ(A−B)=1.
In Zpsm×n, let
[TABLE]
A maximal clique C of Zpsm×n is called of type one (resp. type two),
if C is of the form C=PM1+A (resp. C=N1Q+A),
where P and Q are fixed invertible matrices over Zps and A∈Zpsm×n is fixed.
Lemma 2.10
(see [14, Lemma 3.4])* Let C be a maximal clique of Γ(Zpsm×n) (s≥2) containing the vertex [math].
Then C⊈Jpsm×n.*
Lemma 2.11
(see [14, Theorem 3.6])* Let Γ=Γ(Zpsm×n) and k=max{m,n}. Then*
[TABLE]
Moreover, if n>m, then every maximum clique of Γ is of type one. If m=n, then every maximum clique of Γ is of type one or type two.
In this section, we study vector subspaces of Zpsn. For example, intersection, join and dimension formula of
two subspaces of Zpsn. These results have many applications in geometry and combinatorics.
In general, a linear subset X in Rn may not be a subspace, although it has a dimension.
For example, let R=Zps, and let X⊆Jpsn be a linear subset with X={0}. Then dim(X)=0 because ps−1x=0 for all x∈X.
Thus, X is not a subspace of Rn. On the other hand, if X⊆Zpsn is a linear subset with dim(X)=0, we cannot imply X={0} (i.e., a [math]-subspace).
Let X=[α1,…,αk] be a k-subspace of Zpsn. Then X has a matrix representation\scriptsize\left(\begin{array}[]{c}\alpha_{1}\\
\vdots\\
\alpha_{k}\\
\end{array}\right)\in\mathbb{Z}_{p^{s}}^{k\times n} (cf. [11, 12]).
For simpleness, the matrix representation of X is also written as X.
If X is a matrix representation of the subspace X, then for any invertible matrix P∈GLk(Zps),
PX is also a matrix representation of X. Thus, the matrix representation is not unique. However,
the subspace X has a unique matrix representation which is the row-reduced echelon formX=(Ik,B)Q, where Q is a permutation matrix.
3.1 Join and dimensional formula of subspaces
In Zpsn, a join of two subspaces A and B is a minimum dimensional subspace containing A and B.
In general, when s≥2 the join is not unique.
For example, suppose that s≥3, α=(1,p,0), β=(1,p2,0), γ=(0,1,ps−1),
e1=(1,0,0) and e2=(0,1,0). Then [e1,e2] and [e1,γ] are two distinct joins of [α] and [β].
Denoted by A∨B the set of all joins of subspaces A and B in Zpsn with the same minimum dimension dim(A∨B).
We have A∨B=B∨A. When B⊆A are two subspaces, we have A∨B={A}.
Let X,Y be two subspaces of Zpsn. In general, X∩Y is a linear subset but it may not be a subspace of Zpsn.
For example, let \scriptsize X=\left(\begin{array}[]{cccc}1&0&0&0\\
0&1&0&0\\
\end{array}\right),
\scriptsize Y=\left(\begin{array}[]{cccc}1&0&0&0\\
0&1&p^{s-1}&0\\
\end{array}\right) (s≥2) are 2-subspaces of Zps4.
Then (1,pi,0,0)∈X∩Y, i=0,1,…,s−1. It follows that X∩Y is not a free Zps-module, and hence X∩Y is not a subspace of Zps4.
Theorem 3.1
Let n>k≥m≥1. Suppose A and B are k-subspace and m-subspace of Zpsn, respectively, and B⊈A.
Then there is U∈GLn(Zps) such that
[TABLE]
where D=diag(pi1,…,pir,0m−r,n−m−r), 1≤r≤min{m,n−k} and 0≤i1≤…≤ir≤max{s−1,1}.
*Proof. *Without loss of generality, we assume that s≥2. By the matrix representation of subspace and Lemma 2.1,
there is U1∈GLn(Zps) such that A=(0,Ik)U1. Without loss of generality, we assume U1=In and hence A=(0,Ik). Write B=(B1,B2′) where
B1∈Zpsm×(n−k) and B2′∈Zpsm×k. When k>m, by elementary operations of matrix, we may assume with no loss of generality that
B2′=(0m,k−m,B2) where B2∈Zpsm×m. Thus B=(B1,0m,k−m,B2).
Using Lemma 2.1, we may assume with no loss of generality that
[TABLE]
where 1≤r≤min{m,n−k} and 0≤i1≤…≤ir≤s−1.
Case 1. B2 is invertible.
Let U2=diag(In−m,B2−1). Then A=(0,Ik)=(0,Ik)U2 and B=(B1,0m,k−m,Im)U2.
Thus (3.1) holds.
Case 2. B2 is not invertible.
Without loss of generality, we let
diag(pi1,…,pir)=diag(It,D1),
where
D1=diag(pit+1,…,pir), 1≤it+1≤…≤ir≤s−1.
Write \scriptsize B_{2}=\left(\begin{array}[]{c}B_{21}\\
B_{22}\\
\end{array}\right)\in\mathbb{Z}_{p^{s}}^{m\times m}
where B21∈Zpsr×m and B22∈Zps(m−r)×m. Then B22 has a right inverse.
Without loss of generality, we may assume that B22=(Im−r,0). Then A=(0,Ik) and
[TABLE]
where D2 is an (r−t)×(n−m−t) diagonal matrix over Jps, Y1∈Zpst×r and Y2∈Zps(r−t)×r.
Since (0,D2,0,Y2) has a right inverse, it is easy to see that Y2 has a right inverse. Hence
there exists C1∈Zpst×r such that
\scriptsize\left(\begin{array}[]{c}C_{1}+Y_{1}\\
Y_{2}\\
\end{array}\right) is invertible. Put
[TABLE]
Then A=AU3 and
[TABLE]
Since \scriptsize B_{2}^{\prime\prime}:=\left(\begin{array}[]{cc}0&C_{1}+Y_{1}\\
0&Y_{2}\\
I_{m-r}&0\\
\end{array}\right) is invertible, Case 1 implies that (3.1) holds.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
Theorem 3.2
(dimensional formula)* Let A and B be two subspaces of Zpsn.
Then*
[TABLE]
*Proof. *Let dim(A)=k and dim(B)=m. Without loss of generality, we assume that s≥2, n>k≥m≥1 and B⊈A.
By Theorem 3.1, there is U∈GLn(Zps) such that
A=(0,Ik)U and B=(D,Im)U,
where D=diag(pi1,…,pir,0m−r,n−m−r), 1≤r≤min{m,n−k} and 0≤i1≤…≤ir≤s−1.
Put D1=diag(pi1,…,pir).
Without loss of generality, we may assume that U=In and m≥2. Hence we can assume further that
[TABLE]
In above matrices, some zero elements of matrices may be absent.
Clearly, the (m−r)-subspace (0,0,0,Im−r) is contained in A∩B. On the other hand, the (k+r)-subspace
\small\left(\begin{array}[]{ccccc}I_{r}&0_{r,n-k-r}&0\\
0&0&I_{k}\\
\end{array}\right) contains A and B.
It follows that
[TABLE]
Let α∈A∩B be an n-dimensional vector. Then there are matrices T1∈Zps1×k and T2=(T21,T22)∈Zps1×m,
where T21∈Zps1×r and T22∈Zps1×(m−r), such that
α=T1A=(0,T1), α=T2B=(T21D1,0,T21,T22).
Hence T21D1=0 and α=(0,0,T21,T22). By T21D1=0 we get T21∈Jps1×r. Thus,
[TABLE]
where t1,…,tr∈Jps.
It follows that dim(A∩B)≤m−r. Hence, from (3.3) we obtain
[TABLE]
Assume that d=dim(A∨B). Then there exists a d-subspace W∈A∨B. Since B⊈A, one has d>k.
Thus \scriptsize W=\left(\begin{array}[]{c}W_{1}\\
A\\
\end{array}\right)=\left(\begin{array}[]{cc}W_{11}&0\\
0&I_{k}\\
\end{array}\right), where W11∈Zps(d−k)×(n−k) has a right inverse. Since B⊂W, the r-subspace
B1:=(D1,0r,n−m−r,Ir,0)⊂W. Thus, there is a matrix P=(P1,P2)∈Zpsr×d where P1∈Zpsr×(d−k) and
P2∈Zpsr×k, such that B1=PW and hence (D1,0r,n−m−r,Ir,0)=(P1W11,P2).
It follows from (2.3) that
Clearly, we have \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=\rho\left(\begin{array}[]{ccc}0&0&I_{k}\\
D_{1}&0&0\\
0&0&0\\
\end{array}\right)=k+r. By (3.4) and (3.5), we get (3.2).
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
Remark 3.3
Let A and B be two subspaces of Zpsn. By (3.2), A∨B is the set of subspaces
containing A and B with the same dimension \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right).
3.2 On intersection and join of subspaces
Theorem 3.4
Let A and B be two subspaces of Zpsn and dim(A)+dim(B)≤n.
Then dim(A∩B)=0 if and only if
\scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=\rho(A)+\rho(B). Moreover, A∩B={0} if and only if
\scriptsize{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=\rho(A)+\rho(B).
*Proof. *Let dim(A)=k=ρ(A) and dim(B)=m=ρ(B).
Without loss of generality, we assume that s≥2, k≥m≥1 and B⊈A. Clearly, \scriptsize{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)\leq\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)\leq k+m.
Suppose \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)<k+m.
By Theorem 3.1, there is U1∈GLn(Zps) such that A=(0,Ik)U1 and B=(D,Im)U1,
where D=diag(pi1,…,pir,0m−r,n−m−r), 1≤r<m and 0≤i1≤…≤ir≤s−1.
Thus α:=(0,…,0,1)U1∈A∩B. Since α is unimodular, dim(A∩B)≥1.
Conversely, if dim(A∩B)≥1, then it is clear that \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)<k+m. Therefore, dim(A∩B)≥1 if and only if \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)<k+m. It follows that dim(A∩B)=0 if and only if \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=k+m.
If \scriptsize{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=k+m, then Theorem 3.1 implies that there is U2∈GLn(Zps) such that A=(0,0,Ik)U2 and B=(Im,0,Im)U2.
Thus, it is easy to see that A∩B={0}.
Now, we assume that A∩B={0}. Then dim(A∩B)=0, and hence \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=k+m because (3.2). Suppose \scriptsize{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=k+t<k+m.
By Theorem 3.1, there is U3∈GLn(Zps) such that A=(0,0,Ik)U3 and B=(D1,0,Im)U3, where
D1=diag(It,pit+1,…,pim), 1≤it+1≤…≤im≤s−1. Let β=(0,…,0,ps−im)U3.
Then β=0. By β=ps−im(0,…,0,pim,0,…,0,1)U3=ps−im(0,…,0,1)U3,
we get β∈A∩B, a contradiction. Hence we must have
\scriptsize{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=k+m. Thus, we have that A∩B={0} if and only if
\scriptsize{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=k+m.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
Theorem 3.5
Let A and B be two subspaces of Zpsn. Then:
(i)
A∩B* is a fixed subspace of dimension dim(A∩B) if and only if
\scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right).*
(ii)
A∨B* is a fixed subspace of dimension dim(A∨B) if and only if
\scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right) or dim(A∨B)=n.*
*Proof. *Put dim(A)=k and dim(B)=m.
Without loss of generality, we assume that s≥2, n>k≥m≥1 and B⊈A.
By Theorem 3.1, there is U∈GLn(Zps) such that
A=(0,Ik)U and B=(D,Im)U,
where D=diag(pi1,…,pir,0m−r,n−m−r), 1≤r≤min{m,n−k} and 0≤i1≤…≤ir≤s−1.
Thus \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=k+r and hence n≥k+r. Without loss of generality, we may assume U=In.
By Theorem 3.2, we have dim(A∨B)=k+r and dim(A∩B)=m−r.
(i). Suppose \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right). Then D=diag(Ir,0m−r,n−m−r), \scriptsize B=\left(\begin{array}[]{cccc}I_{r}&0&I_{r}&0\\
0&0&0&I_{m-r}\\
\end{array}\right) and
A=(0,Ik). Thus A∩B contains an (m−r)-subspace A1:=(0,0,0,Im−r),
For any vector x∈A∩B, it is easy to verify x∈A1. Therefore, A∩B=A1 is a fixed (m−r)-subspace.
Conversely, suppose A∩B is a fixed (m−r)-subspace. We show \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right). Otherwise, \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)>{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right), and hence 0=pir∈Jps in the matrix D. By row elementary operations of matrix,
it is easy to see that the (m−r)-subspace
\small A_{2}:=\left(\begin{array}[]{cccc}0&p^{s-i_{r}}&1&0\\
0&0&0&I_{m-r-1}\\
\end{array}\right)\subseteq A\cap B.
Since the (m−r)-subspace A1=(0,0,0,Im−r)⊆A∩B and A1=A2, we get a contradiction.
(ii). Suppose \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right). Similarly, \scriptsize B=\left(\begin{array}[]{cccc}I_{r}&0&I_{r}&0\\
0&0&0&I_{m-r}\\
\end{array}\right) and
A=(0,Ik). Clearly, A∨B contains a (k+r)-subspace
\scriptsize B_{1}:=\left(\begin{array}[]{ccc}I_{r}&0&0\\
0&0&I_{k}\\
\end{array}\right). Since a basis of A can be extended to a basis of any (k+r)-subspace C∈A∨B,
it is easy to prove that every (k+r)-subspace containing A and B must be B1. Thus A∨B={B1} is a fixed (k+r)-subspace.
If dim(A∨B)=k+r=n, then dim(A∨B)=Zpsn and hence A∨B is fixed.
Conversely, suppose A∨B is a fixed (k+r)-subspace. If k+r=n, then (ii) holds. Now, we assume that k+r<n.
We assert \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right). Otherwise, \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)>{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right), and hence 0=pir∈Jps in the matrix D. By elementary row operations of matrix, it is easy to see that the (k+r)-subspace
\scriptsize B_{2}:=\left(\begin{array}[]{ccccc}I_{r-1}&0&0&0&0\\
0&1&p^{s-1}&0&0\\
0&0&0&0&I_{k}\\
\end{array}\right) contains A and B. Also, the (k+r)-subspace \small B_{1}=\left(\begin{array}[]{ccc}I_{r}&0&0\\
0&0&I_{k}\\
\end{array}\right)
contains A and B, a contradiction since B1=B2.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
3.3 Enumeration on subspaces
For any non-negative integers m,n,q with n≥m and q≥2, the Gaussian binomial coefficient is
[TABLE]
where [0n]q:=1. Let [m0]q:=0 (if m>0). We have [mn]q=[n−mn]q.
Theorem 3.6
Let n>m>k≥1. Then:
(i)
The number of m-subspaces of Zpsn is p(s−1)m(n−m)[mn]p.
(ii)
In Zpsn, the number of k-subspaces in a given m-subspace is p(s−1)k(m−k)[km]p.
(iii)
In Zpsn, the number of m-subspaces containing a given k-subspace is p(s−1)(m−k)(n−m)[m−kn−k]p.
*Proof. *(i). Let nm,s be the number of m-subspaces of Zpsn. When s=1,
it is well-known that nm,1=[mn]p. Now, we assume s≥2.
Let π:Zpsm×n→Zpm×n be the natural surjection (2.10).
Suppose S is the set of all m-subspaces of Zpsn. By Theorem 2.7,
π(S) is the set of all m-subspaces of Zpn. Thus ∣π(S)∣=[mn]p.
Let A be any fixed m-subspace in π(S). By Theorem 3.1, there is UA∈GLn(Zp) such that A=(0,Im)UA. It is easy to see that
the preimages π−1(A)={(X,Im)UA:X∈Jpsm×(n−m)}. By ∣π−1(A)∣=p(s−1)m(n−m), we obtain nm,s=p(s−1)m(n−m)[mn]p.
(ii). By (i), it is clear.
(iii). Let S be the set of m-subspaces in Zpsn containing a given k-subspace B in Zpsn.
By Theorem 3.1, we can assume that B=(0,Ik)U where U∈GLn(Zps). Then
[TABLE]
Using (i), we obtain ∣S∣=p(s−1)(m−k)(n−m)[m−kn−k]p.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
3.4 Dual subspace and arithmetic distance
Now, we study dual subspace and arithmetic distance on vector subspace of Zpsn.
The dual subspace is an important tool that can simplify some complex calculations.
Let P be an m-subspace of Zpsn, and let
[TABLE]
The P⊥ is the set of vectors which are orthogonal to every vector of P. Obviously, P⊥ is a linear subset of Zpsn.
By Theorem 3.1, we can assume that P=(0,Im)U, where U∈GLn(Zps). Thus, it is easy to prove that
[TABLE]
Hence P⊥ is an (n−m)-subspace of Zpsn. The subspace P⊥ is called the dual subspace of P. We have
[TABLE]
[TABLE]
If P1⊆P2 are two subspaces of Zpsn, then
the definition of P⊥ implies that P2⊥⊆P1⊥. It follows from (3.8) that
[TABLE]
Lemma 3.7
Let A be an m-subspace of Zpsn, and let
π:Zpsm×n→Zpm×n be the natural surjection (2.10). Then
[TABLE]
*Proof. *By Theorem 3.1, there is U∈GLn(Zps) such that A=(0,Im)U. From (3.6) we have
A⊥=(In−m,0)tU−1. Let U=U0+U1p+⋯+Us−1ps−1 and U−1=Y0+Y1p+⋯+Ys−1ps−1,
where Ui,Yi∈Zpm×n, i=0,…,s−1. It is clear that Y0=U0−1.
Then tU−1=tU0−1+tY1p+⋯+tYs−1ps−1.
Using (2.12), we obtain that π(A)=(0,Im)U0 and π(A⊥)=(In−m,0)tU0−1.
Thus (3.10) holds.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
For two subspaces A,B of Zpsn, the arithmetic distance between A and B, denoted by ad(A,B),
is defined by
[TABLE]
Clearly, ad(A,B)≥0 and ad(A,B)=ad(B,A). Moreover, ad(A,B)=0⇔A⊆B or B⊆A.
Theorem 3.8
Let A and B be two subspaces of Zpsn. Suppose that C is a subspace of Zpsn
with dim(C)=min{dim(A),dim(B)}. Then
[TABLE]
*Proof. *Without loss of generality, we assume that dim(A)=max{dim(A),dim(B)}. Thus dim(B)=min{dim(A),dim(B)}.
By the conditions, dim(C)=dim(B).
By (3.2) and (3.11), we have that
ad(A,B)=dim(A∨B)−dim(A)=dim(B)−dim(A∩B),
ad(A,C)=dim(A∨C)−dim(A)=dim(C)−dim(A∩C), and ad(C,B)=dim(C∨B)−dim(B)=dim(C)−dim(C∩B).
Thus, the inequality (3.12) is equivalent to the following inequality:
[TABLE]
Write d1=dim(A∩C) and d2=dim(C∩B). Let A1 be a d1-subspace in A∩C and
B1 a d2-subspace in C∩B. Then A1∩B1⊆A∩B and hence dim(A1∩B1)≤dim(A∩B).
Since A1,B1⊆C, dim(C)≥dim(A1∨B1).
Using (3.2) we get dim(A1∨B1)=d1+d2−dim(A1∩B1).
Thus,
[TABLE]
Therefore, we have proved the inequality (3.13).
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
Theorem 3.9
Let n>m and let A and B be two m-subspaces of Zpsn. Then
[TABLE]
*Proof. *Assume that ad(A,B)=r.
By (3.11) and Theorem 3.1, without loss of generality, we assume that A=(0,Im) and B=(D,Im),
where D=diag(pi1,…,pir,0m−r,n−m−r), 1≤r≤min{m,n−m} and 0≤i1≤…≤ir≤max{s−1,1}.
By (3.7), both A⊥ and B⊥ are (n−m)-subspaces of Zpsn.
Applying (3.6), A⊥=(In−m,0). Let B⊥=(X1,X2) where X1∈Zps(n−m)×(n−m) and
X2∈Zps(n−m)×m. Since B⊥⋅tB=0, we have X1tD+X2=0 and hence ρ(X2)=ρ(−X1tD)≤r because (2.3).
Thus
[TABLE]
On the other hand, using (3.8) we have similarly ad(A,B)=ad((A⊥)⊥,(A⊥)⊥))≤ad(A⊥,B⊥).
Therefore (3.14) holds.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
4 Grassmann graphs over Zps
In this section, we discuss the basic properties of Grassmann graph over Zps.
We will determine the valency of every vertex, the clique number and maximum cliques of the Grassmann graph.
4.1 Valency, clique number and independence number
For any two vertices A,B of the Grassmann graph Gps(n,m), by Theorem 3.2 and (3.11), we have
[TABLE]
By (3.11), for vertices A,B,C of Gps(n,m), \scriptsize{\rm ad}(A,B)=\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)-m is the arithmetic distance between A and B in Gps(n,m). Clearly, ad(A,B)≥0, ad(A,B)=0⇔A=B; ad(A,B)=ad(B,A);
ad(A,B)≤ad(A,C)+ad(C,B) by Theorem 3.8.
Theorem 4.1
If A and B are two vertices of Gps(n,m), then
[TABLE]
*Proof. *Without loss of generality, we assume that s≥2.
Let A,B∈V(Gps(n,m)) and ad(A,B)=r, where 1≤r≤min{m,n−m}. By Theorem 3.1,
we may assume with no loss of generality that A=(0,Im) and B=(D,Im),
where D=diag(pi1,…,pir,0m−r,n−m−r), and 0≤i1≤…≤ir≤s−1.
Let Aj=(Dj,Im) where Dj=diag(pi1,…,pij,0m−j,n−m−j), j=1,…,r−1.
Then A∼A1∼⋯∼Ar−1∼B.
Hence d(A,B)≤ad(A,B). Applying the triangle inequality, it is easy to prove that d(A,B)≥ad(A,B).
Thus (4.2) holds.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
By Theorem 3.9, (4.1) and (3.6), it is easy to see that
Gps(n,m) is isomorphic to Gps(n,n−m).
When m=1, Gps(n,1) a complete graph. Thus, we always assume that n≥2m≥4 in our discussion on
Gps(n,m) unless specified otherwise.
Theorem 4.2
The Gps(n,m) is a connected vertex-transitive graph of the valency
[TABLE]
*Proof. *Let A=(0,Im) be a fixed vertex of of Gps(n,m).
For any vertex Y of Gps(n,m), Theorem 3.1 implies that Y=(0,Im)U where U∈GLn(Zps). Since the map X↦XU−1 is an
automorphism of Gps(n,m), Gps(n,m) is vertex-transitive. Thus Gps(n,m) is an r-regular graph, where r is the same valency of each vertex.
Without loss of generality, we assume s≥2.
By (4.2), it is clear that Gps(n,m) is connected.
Let X be any vertex of Gps(n,m) with X∼A. Write X=(X1,X2)
where X1∈Zpsm×(n−m) and X2∈Zpsm×m.
Since \scriptsize\rho\left(\begin{array}[]{c}A\\
X\\
\end{array}\right)=m+1, ρ(X1)=1. Using Lemma 2.1, X can be written as
\scriptsize X=\left(\begin{array}[]{cc}\alpha&\beta\\
0&X_{22}\\
\end{array}\right) where 0=α∈Zpsn−m and X22∈V(Gps(m,m−1)). Thus, (4.3) implies that
X22 has p(s−1)(m−1)[1m]p different choices. For every fixed choice X22, we can assume further that
\scriptsize\left(\begin{array}[]{cc}\alpha&\beta\\
0&X_{22}\\
\end{array}\right)=\left(\begin{array}[]{ccc}x&y&0\\
0&0&I_{m-1}\\
\end{array}\right), where x∈Zpsn−m, y∈Zps and (x,y) is unimodular with x=0, and A=(0,Im) does not change.
Case 1. y∈Zps∗. We can assume y=1. Then for every fixed choice X22, (x,1) with x=0 has
∣Zps∣n−m−1=ps(n−m)−1 different choices.
Case 2. y∈Jps. Then for every fixed choice X22, unimodular (x,y) with x=0 has
[TABLE]
different choices.
Combination Case 1 with Case 2, for every fixed choice X22, unimodular (x,y) with x=0 has
p(s−1)(n−m)[1n−m]p+ps(n−m)−1 different choices.
It follows that vertex X with X∼A has
[TABLE]
different choices. Thus (4.4) holds. \hfill□\vskip6.0ptplus2.0ptminus2.0pt
For every (m−1)-subspace P of Zpsn, let [P⟩m denote the set of all m-subspaces containing P, which is called a star.
For every (m+1)-subspace Q of Zpsn, let ⟨Q]m denote the set of all m-subspaces of Q, which is called a top.
Note that Theorem 3.2. It is easy to see that every star or top is a clique of Gps(n,m).
In Gps(n,m), by Theorem 3.6, we have
[TABLE]
When n=2m, we have ∣[P⟩m∣=∣⟨Q]m∣. On the other hand, ∣[P⟩m∣<∣⟨Q]m∣ if n<2m; and
[TABLE]
Let P and Q be an m-subspace and an (m+1)-subspace of Zpsn, respectively.
By Lemma 3.1, there are U1,U2∈GLn(Zps) such that P=(0,Im−1)U1 and Q=(0,Im+1)U2. Thus
[TABLE]
[TABLE]
When n=2m, we define
[TABLE]
[TABLE]
In Gps(2m,m), using (3.9) and (4.5), it is easy to see that
[TABLE]
Lemma 4.3
In Gps(n,m), every star or top is a maximal clique.
where U1∈GLn(Zps) is fixed.
Let X=(X1,X2)U1∈V(Gps(n,m)) and X∼Z for all Z∈[P⟩m, where X1∈Zpsm×(n−m+1)
and X2∈Zpsm×(m−1). Then
[TABLE]
for all unimodular α∈Zpsn−m+1.
Thus ρ(X1)=1. By Lemma 2.1, \scriptsize X=\left(\begin{array}[]{cc}\alpha_{1}&\alpha_{2}\\
0&X_{2}^{\prime}\\
\end{array}\right)U_{1} where X2′∈Zps(m−1)×(m−1). Clearly, X2′ is invertible.
It follows that X∈[P⟩m, and hence [P⟩m is a maximal clique.
where U2∈GLn(Zps) is fixed.
Let W∈V(Gps(n,m)) and W∼Z for all Z∈⟨Q]m. By W∼(0,Im)U2, we have similarly that
\scriptsize W=\left(\begin{array}[]{ccc}\alpha_{1}&\alpha_{2}&\alpha_{3}\\
0&0&W_{22}\\
\end{array}\right)U_{2}, where α1∈Zpsn−m−1, α2∈Zps and W22∈Zps(m−1)×m.
Since W22 has a right inverse, it is easy to see that there is Y0∈V(Gps(m+1,m)) such that \scriptsize\rho\left(\begin{array}[]{c}(0,W_{22})\\
Y_{0}\\
\end{array}\right)=m+1. By W∼(0,Y0)U2∈⟨Q]m, we get α1=0. Thus W∈⟨Q]m, and hence ⟨Q]m is a maximal clique.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
Theorem 4.4
(i)* The clique number of Gps(n,m) (when n≥2m) is*
[TABLE]
(ii)
Let M be a maximum clique of Gps(n,m), and let π:Zpsm×n→Zpm×n
be the natural surjection (2.10).
Then when n>2m, π(M) is a star in Gp(n,m). When n=2m, π(M) is a star or a top in Gp(n,m).
*Proof. *Put Gps=Gps(n,m). When s=1, this theorem is well-known (cf. [6, 13, 22]). From now on we assume that s≥2 and n≥2m.
Write ω=ω(Gps).
Let π:Zpsm×n→Zpm×n be the natural surjection (2.10).
Let M={A1,…,Aω} be a maximum clique of Gps.
Suppose {π(Ai1),…,π(Aik)} is the set all different elements in {π(A1),…,π(Aω)}.
By (4.1) and Theorem 2.7(i), {π(Ai1),…,π(Aik)} is a clique of Gp. Thus
[TABLE]
Moreover, M has a partition into k cliques: M=M1∪M2∪⋯∪Mk, where Mt is a clique with π(Mt)=π(Ait), t=1,…,k.
Thus
[TABLE]
(i). Put nt=∣Mt∣, t=1,…,k. Then Mt={π(Ait)+Bt1,π(Ait)+Bt2,…,π(Ait)+Btnt}, where Btj∈Jpsm×n,
j=1,…,nt.
By Theorem 3.1, there is Ut∈GLn(Zp) such that π(Ait)=(0,Im)Ut.
Note that Im+B is invertible for all B∈Jpsm×m. The matrix representation π(Ait)+Btj can be written as
π(Ait)+Btj=(Ctj,Ik)Ut, where Ctj∈Jpsm×(n−m), j=1,…,nt. Therefore,
[TABLE]
By (4.1), it is clear that {Ct1,Ct2,…,Ctnt} is a clique of the bilinear forms graph
Γ(Zpsm×(n−m)). Since Ctj∈Jpsm×(n−m), from (2.9) we can write Ctj=Dtjp
where Dtj∈Zps−1m×(n−m),
j=1,…,nt. By Lemma 2.9, {Dt1,Dt2,…,Dtnt} is a clique of
Γ(Zps−1m×(n−m)). By Lemma 2.11,
∣Mt∣=nt≤ω(Γ(Zps−1m×(n−m)))=p(s−1)(n−m), t=1,…,k. Therefore,
[TABLE]
By (4.5) and (4.13), every star is a maximum clique of Gps and (4.12) holds.
(ii). Using (4.13) and (4.12), it is easy to see that k=[1n−m+1]p, and hence π(M) is a maximum clique of Gp
for every maximum clique M of Gps. When n>2m (resp. n=2m), it is well-known (cf. [13, 22]) that every maximum clique of Gp
is a star (resp. a star or a top). Therefore, when n>2m, π(M) is a star of Gp(n,m). When n=2m, π(M) is a star or a top of Gp(n,m).
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
It is a difficult open problem to compute the independence number of Grassmann graph. We can only give the following estimation of independence number on Gps(n,m).
Theorem 4.5
Let n≥2m and let Gps=Gps(n,m). Then
[TABLE]
*Proof. *Without loss of generality, we assume s≥2.
Let N={B1,…,Bh} be a largest independent set of Gp, where h=α(Gp).
Applying Theorem 3.1, there is Qt∈GLn(Zp) such that Bt=(0,Im)Qt, t=1,…,h.
Let {P1,P2,…,Pr} be a largest independent set of the bilinear forms graph Γ(Zps−1m×(n−m)),
where r=p(s−1)(m−1)(n−m) because (2.16). Put
[TABLE]
Then ∣Nt∣=r.
By Lemma 2.9 and (4.1), Nt is an independent set of Gps, t=1,…,h. Note that (pPi,0)Qt is a matrix
over Jps, i=1,…,r, t=1,…,h. For any X=(pPi,Im)Qt∈Nt and Y=(pPj,Im)Qu∈Nu, where t=u and 1≤i,j≤r,
by \scriptsize\rho\left(\begin{array}[]{c}B_{t}\\
B_{u}\\
\end{array}\right)\geq{\rm rk}\left(\begin{array}[]{c}B_{t}\\
B_{u}\\
\end{array}\right)>m+1 and Lemma 2.4,
we have
[TABLE]
Thus, M′:=N1∪N2∪⋯∪Nh is an independent set of Gps. Consequently
[TABLE]
If G is a vertex-transitive graph, then it is well-known (cf. [9, Lemma 7.2.2]) that
α(G)≤ω(G)∣V(G)∣. Since Gps is vertex-transitive, (4.3) and (4.12) imply that
α(Gps)≤p(s−1)(m−1)(n−m)[1n−m+1]p[mn]p.
\hfill□\vskip6.0ptplus2.0ptminus2.0pt
4.2 Maximum cliques
Theorem 4.6
When n>2m, every maximum clique of Gps(n,m) is a star. When n=2m, every maximum clique of Gps(n,m) is
either a star or a top.
*Proof. *When s=1, this theorem is well-known (cf. [6, 13, 22]). From now on we assume that s≥2 and n≥2m.
Let Eij=Eijm×(n−m). Recall that Γ(Zpsm×(n−m))
is the bilinear forms graph on Zpsm×(n−m).
Let M be a maximum clique of Gps(n,m). By Theorem 3.1, we may assume with no loss of generality that A=(0,Im)∈M.
We show that there is a vertex B∈M such that
\scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=m+1. Otherwise, for any vertex B∈M with B∼A, we have \scriptsize m+1=\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)>{\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=m.
It is easy to see that B=(B1,Im) where B1∈Jpsm×(n−m) with ρ(B1)=1.
Thus, there exists a clique N of Γ(Zpsm×(n−m)) containing [math], such that
N⊆Jpsm×(n−m) and M={(X,Im):X∈N}.
Clearly, for every maximal clique C containing [math] in Γ(Zpsm×(n−m)), the set {(X,Im):X∈C} is a clique of Gps(n,m).
Since M={(X,Im):X∈N} is a maximum clique, N must be a maximal clique of Γ(Zpsm×(n−m)),
but N⊆Jpsm×(n−m), a contradiction to Lemma 2.10.
Therefore, there is vertex B∈M such that
\scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=m+1. By Theorem 3.1, we may assume with no loss of generality that
[TABLE]
Let π:Zpsm×n→Zpm×n be the natural surjection (2.10).
For any vertex X in π(M), let π−1(X) denote the preimages of X in M, i.e.,
π−1(X)={Y∈M:π(Y)=X}.
By Theorem 4.4(ii), when n>2m, π(M) is a star in Gp(n,m). When n=2m, π(M) is a star or a top in Gp(n,m).
Case 1. π(M) is a star in Gp(n,m).
We will prove that M is a star in Gps(n,m).
Since π(A)=A, π(B)=B and A∩B=(0,Im−1),
(4.7) implies that
[TABLE]
Let ei be the i-th row of In−m+1, and let
[TABLE]
By (4.12), we have π−1(Ai)=p(s−1)(n−m). From Lemma 2.11, there is a maximum clique Ci
of Γ(Zps−1m×(n−m)) such that
[TABLE]
i=1,…,n−m+1. Here \scriptsize\left(\begin{array}[]{c}\beta_{i1}\\
\beta_{i3}\\
\end{array}\right) or \scriptsize\left(\begin{array}[]{c}\beta_{i2}\\
\beta_{i4}\\
\end{array}\right) may be absent if i=1 or i=n−m+1.
Let Xn−m∈π−1(An−m). Then Xn−m∼A and hence \scriptsize\rho\left(\begin{array}[]{c}A\\
X_{n-m}\\
\end{array}\right)=m+1. It follows that βn−m,3=0. Since Xn−m∼B, we have similarly βn−m,4=0. Therefore, we obtain
and hence \small\rho\left(\begin{array}[]{cc}0&1\\
A_{21}p&A_{22}p\\
\end{array}\right)=1.
Consequently A21p=0. Since \small\left(\begin{array}[]{cccc}A_{11}p&A_{12}p&1&0\\
0&A_{22}p&0&I_{m-1}\\
\end{array}\right)\sim B, it is easy to see that A22p=0. Thus
[TABLE]
Let
[TABLE]
By π−1(Bα)=p(s−1)(n−m) and Lemma 2.11, there is a maximum clique Cα
of Γ(Zps−1m×(n−m)), such that
[TABLE]
Let ei′ be the i-th row of In−m. Since
[TABLE]
and (4.1), we get
\small\rho\left(\begin{array}[]{c}e_{n-m}^{\prime}\\
B_{2}p\\
\end{array}\right)=1, which implies that B2p=(0,β2) where β2∈Jps(m−1)×1.
By (4.18), we have
[TABLE]
It follows from (4.1) that
\small\rho\left(\begin{array}[]{c}\alpha+B_{1}p-\beta\\
B_{2}p\\
\end{array}\right)=1 for all β∈Jps1×(n−m). Taking β=B1p, we get
\small\rho\left(\begin{array}[]{c}\alpha\\
B_{2}p\\
\end{array}\right)=\rho\left(\begin{array}[]{c}\alpha\\
(0,\beta_{2})\\
\end{array}\right)=1. Thus, when α=en−m′, we have that B2p=(0,β2)=0.
When α=en−m′,
which implies that B2p=(0,β2)=0. Therefore, we always have B2p=0. Then we have proved that
[TABLE]
Put
[TABLE]
Then
[TABLE]
Let \scriptsize\left(\begin{array}[]{ccc}\alpha+D_{1}p&D_{2}p&0\\
D_{3}p&D_{4}p&I_{m-1}\\
\end{array}\right)\in\pi^{-1}(D_{\alpha}).
Then \scriptsize\left(\begin{array}[]{ccc}\alpha+D_{1}p&D_{2}p&0\\
D_{3}p&D_{4}p&I_{m-1}\\
\end{array}\right)\sim A, and hence
\scriptsize\rho\left(\begin{array}[]{c}\alpha+D_{1}p\\
D_{3}p\\
\end{array}\right)=1. Since α+D1p is unimodular, \scriptsize\left(\begin{array}[]{c}\alpha+D_{1}p\\
D_{3}p\\
\end{array}\right) has a minimal factorization \scriptsize\left(\begin{array}[]{c}\alpha+D_{1}p\\
D_{3}p\\
\end{array}\right)=\left(\begin{array}[]{c}1\\
\gamma\\
\end{array}\right)(\alpha+D_{1}p), and hence D3p=γ(α+D1p). Therefore, applying elementary row operations of matrix,
we can assume
[TABLE]
Put \scriptsize\left(\begin{array}[]{ccc}\alpha+D_{1}p&D_{2}p&0\\
0&D_{4}^{\prime}p&I_{m-1}\\
\end{array}\right)\in\pi^{-1}(D_{\alpha}).
By (4.19), \scriptsize\left(\begin{array}[]{ccc}\alpha+D_{1}p&D_{2}p&0\\
0&D_{4}^{\prime}p&I_{m-1}\\
\end{array}\right)\sim\left(\begin{array}[]{ccc}\alpha^{\prime}+B_{1}p&1&0\\
0&0&I_{m-1}\\
\end{array}\right) for all B1p∈Jpsn−m and 0=α′∈Zpn−m. Thus, by (4.1) we get
\scriptsize\rho\left(\begin{array}[]{cc}\alpha^{\prime}+B_{1}p&1\\
\alpha+D_{1}p&D_{2}p\\
0&D_{4}^{\prime}p\\
\end{array}\right)=2, for all 0=α′∈Zpn−m.
Clearly, there exists 0=α′∈Zpn−m such that
\scriptsize{\rm rk}\left(\begin{array}[]{c}\alpha^{\prime}+B_{1}p\\
\alpha+D_{1}p\\
\end{array}\right)=\rho\left(\begin{array}[]{c}\alpha^{\prime}+B_{1}p\\
\alpha+D_{1}p\\
\end{array}\right)=2, which implies that D4′p=0. Therefore,
[TABLE]
Let P=A∩B=(0,0,Im−1). By (4.18)-(4.20), we have that M=π−1(π(M))=[P⟩m is a star in Gps(n,m).
Case 2. π(M) is a top in Gp(n,m) with n=2m.
We show that M is a top in Gps(n,m) as follows. Define
\mathcal{M}^{\perp}=\left\{X^{\perp}:\mbox{Xisanym−subspacein\mathcal{M}}\right\}.
By Lemma 3.7, we have π(M⊥)=(π(M))⊥.
It follows from (4.9) that (π(M))⊥ is a star in Gp(n,m). By the Case 1, M⊥ is a star in Gps(n,m).
Applying (3.8) and (4.9), M=(M⊥)⊥ is a top in Gps(n,m).
Combination Case 1 with Case 2, when n>2m, every maximum clique of Gps(n,m) is a star. When n=2m, every maximum clique of Gps(2m,m) is
either a star or a top.
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5 Automorphisms of Grassmann graph over Zps
Recall that an endomorphism of a graph G is an adjacency preserving map from V(G) to itself.
An automorphism of a graph G is an adjacency preserving bijective map from V(G) to itself.
In the algebraic graph theory [9], the characterization of graph automorphism is an important problem.
In this section, we determine the automorphisms of Gps(n,m), and our main result is as follows.
Theorem 5.1
Let n≥2m≥4, and let φ be an automorphism of Gps(n,m). Then either there exists
U∈GLn(Zps) such that
[TABLE]
or n=2m and there exists U∈GLn(Zps) such that
[TABLE]
Theorem 5.1 also has important significance for the geometry of matrices [12, 25], and it is also the fundamental theorem of the projective geometry
of rectangular matrices over Zps. To prove Theorem 5.1, we need the following knowledge and lemmas.
In Gps(n,m) (where n>m≥1), two vertices A,B are said to be McCoy adjacent (Mc-adjacent for short),
denoted by A∼mcB, if \scriptsize\rho\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}A\\
B\\
\end{array}\right)=m+1. Two Mc-adjacent vertices are adjacent but not vice versa.
An endomorphism φ of Gps(n,m) is called to preserve Mc-adjacency if A∼mcB implies that φ(A)∼mcφ(B)
for any two vertices A and B.
Lemma 5.2
Let n>m≥1, and let A,B be two distinct vertices of Gps(n,m) with d(A,B)=k.
Then there are vertices A1,…,A2k−1 of Gps(n,m) such that
A∼mcA1∼mc⋯∼mcA2k−1∼mcB.
*Proof. *Let Eij=Eijm×(n−m).
Suppose that A∼B. By Theorem 3.1, there is U∈GLn(Zps) such that
A=(0,Im)U and B=(piE11,Im)U, where 0≤i≤max{s−1,1}. Put C=(piE11+E12,Im)U. Then
A∼mcC∼mcB.
Now, let d(A,B)=k>1. Then there are vertices B1,…,Bk−1 such that A∼B1∼⋯∼Bk−1∼B.
Thus, there are vertices C1,…,Ck such that
A∼mcC1∼mcB1⋯∼mcBk−1∼mcCk∼mcB.
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Lemma 5.3
Let n>m≥2. Then A is a vertex of Gps(n,m) if and only if there are two vertices P1,P2∈V(Gps(n,m−1))
such that P1∼mcP2 and A={A}=P1∨P2.
*Proof. *Let A be a vertex of Gps(n,m). By Theorem 3.1, we may assume with no loss of generality that A=(0,Im).
Put P1=(0,Im−1),P2=(0,Im−1,0m,1)∈V(Gps(n,m−1)). Then \scriptsize\rho\left(\begin{array}[]{c}P_{1}\\
P_{2}\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}P_{1}\\
P_{2}\\
\end{array}\right)=m, and hence P1∼mcP2. By Theorem 3.5(ii), we get A={A}=P1∨P2.
Conversely, suppose there are vertices P1,P2∈V(Gps(n,m−1)) such that P1∼mcP2 and A={A}=P1∨P2.
Then A is a fixed m-subspace and hence A is a vertex of Gps(n,m).
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Lemma 5.4
Let [P1⟩m,[P2⟩m be two distinct stars in Gps(n,m) where n≥2m≥4. Then:
(i)
[P1⟩m∩[P2⟩m=∅* if and only if P1∼P2 (in Gps(n,m−1)). Moreover,
if [P1⟩m∩[P2⟩m=∅,
then [P1⟩m∩[P2⟩m=P1∨P2.*
(ii)
In Gps(n,m), ∣[P1⟩m∩[P2⟩m∣=1 if and only if P1∼mcP2 (in Gps(n,m−1)).
*Proof. *(i). Assume that [P1⟩m∩[P2⟩m=∅. Let vertex C∈[P1⟩m∩[P2⟩m. Then P1,P2⊂C.
It follows from Remark 3.3 that dim(P1∨P2)=m and C∈P1∨P2.
Thus P1∼P2 (in Gps(n,m−1)) and [P1⟩m∩[P2⟩m⊆P1∨P2.
Conversely, suppose that P1∼P2 (in Gps(n,m−1)). Then (4.1) implies that dim(P1∨P2)=m.
By Remark 3.3, P1∨P2⊆[P1⟩m∩[P2⟩m
and hence [P1⟩m∩[P2⟩m=∅. Therefore, [P1⟩m∩[P2⟩m=∅ if and only if P1∼P2 (in Gps(n,m−1)).
Now, we assume [P1⟩m∩[P2⟩m=∅. Then \scriptsize\rho\left(\begin{array}[]{c}P_{1}\\
P_{2}\\
\end{array}\right)=m={\rm dim}(P_{1}\vee P_{2}) and [P1⟩m∩[P2⟩m⊆P1∨P2.
By Remark 3.3 again, we have P1∨P2⊆[P1⟩m∩[P2⟩m. Thus [P1⟩m∩[P2⟩m=P1∨P2.
(ii). Suppose that ∣[P1⟩m∩[P2⟩m∣=1 in Gps(n,m). By (i), P1∨P2 is a fixed m-subspace.
By Theorem 3.5(ii), we have
\scriptsize\rho\left(\begin{array}[]{c}P_{1}\\
P_{2}\\
\end{array}\right)={\rm rk}\left(\begin{array}[]{c}P_{1}\\
P_{2}\\
\end{array}\right)=m, and hence P1∼mcP2 (in Gps(n,m−1)).
Conversely, suppose that P1∼mcP2 (in Gps(n,m−1)). Using (i) and Theorem 3.5(ii), we obtain
∣[P1⟩m∩[P2⟩m∣=∣P1∨P2∣=1.
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Lemma 5.5
In Gps(n,m), if [P⟩m∩⟨Q]m=∅, then ∣[P⟩m∩⟨Q]m∣=ps−1(p+1).
*Proof. *When s=1, this lemma is known by [13, Lemma 2.1]. From now on we assume that s≥2.
Suppose [P⟩m∩⟨Q]m=∅. Then P⊂Q. By Lemma 2.1,
without loss of generality, we may assume that P=(0,Im−1). Thus \scriptsize Q=\left(\begin{array}[]{cc}Q_{1}&0\\
0&I_{m-1}\\
\end{array}\right), where Q1∈Zps2×(n−m+1) has a right inverse.
Using appropriate elementary operations of matrix, we may assume with no loss of generality that Q=(0,Im+1).
Let vertex A∈[P⟩m∩⟨Q]m. Then P⊂A⊂Q. By (4.7) and (4.8), we have
\scriptsize A=\left(\begin{array}[]{ccc}0&\alpha_{1}&0\\
0&0&I_{m-1}\\
\end{array}\right) where α1∈Zps2 is unimodular. Since the number of unimodular vectors in Zps2 is
∣Zps∗∣∣Zps∣2−∣Jps∣2=ps−1(p+1),
we obtain ∣[P⟩m∩⟨Q]m∣=ps−1(p+1).
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Lemma 5.6
Let n≥2m≥4. Suppose φ is an automorphism of Gps(n,m) and φ maps stars to stars.
Let φ([X⟩m)=[X′⟩m, X∈V(Gps(n,m−1)).
Define the map φ1:V(Gps(n,m−1))→V(Gps(n,m−1)) by
φ1(X)=X′. Then:
(i)
The map φ1 is an automorphism of Gps(n,m−1), φ is uniquely determined by φ1, and
[TABLE]
(ii)
Let X,Y,W∈V(Gps(n,m−1)). Then X∼mcY if and only if φ1(X)∼mcφ1(Y).
Moreover, X∼mcY with W⊂X∨Y, if and only if φ1(X)∼mcφ1(Y) with φ1(W)⊂φ1(X)∨φ1(Y).
*Proof. *(i). By Lemma 5.4(i), it is easy to see that φ1 is an injective endomorphism of Gps(n,m−1). Thus
Thus φ1 is an automorphism of Gps(n,m−1).
Put X,Y∈V(Gps(n,m−1)) with X∼mcY. From Theorem 3.5(ii) we know that X∨Y is a fixed m-subspace.
By Lemma 5.4(i), X∨Y=[X⟩m∩[Y⟩m. Thus φ(X∨Y)=[φ1(X)⟩m∩[φ1(Y)⟩m, and hence
∣[φ1(X)⟩m∩[φ1(Y)⟩m∣=1. It follows from Lemma 5.4 that φ1(X)∼mcφ1(Y) and
[TABLE]
Therefore, (5.3) holds and φ1 preserves the Mc-adjacency in Gps(n,m−1).
Let A be a vertex of Gps(n,m). By Lemma 5.3, there are two vertices P1,P2∈V(Gps(n,m−1)) such that P1∼mcP2 and
A=P1∨P2. By (5.3), φ is uniquely determined by φ1.
(ii). Let φ−1 and φ1−1 be the inverse maps of φ and φ1, respectively. Then φ−1 and φ1−1
are also two graph automorphisms. Since φ([X⟩m)=[φ1(X)⟩m for all X∈V(Gps(n,m−1)),
we have φ−1([Z⟩m)=[φ1−1(Z)⟩m for all Z∈V(Gps(n,m−1)). By (i), both φ1 and φ1−1 preserve the Mc-adjacency in Gps(n,m−1).
Therefore, for any X,Y∈V(Gps(n,m−1)), it is easy to see that X∼mcY if and only if
φ1(X)∼mcφ1(Y).
Suppose that X,Y,W∈V(Gps(n,m−1)), X∼mcY and W⊂X∨Y. Without losing generality, we assume that W=X and W=Y.
Then dim(W∨Y)=dim(X∨Y)=m.
Hence W∼Y. Similarly, W∼X. By (i), we have that φ1(X)∼mcφ1(Y), φ1(W)∼φ1(Y) and φ1(W)∼φ1(X).
By Theorem 3.5(ii), X∨Y and φ1(X)∨φ1(Y) are two
fixed vertices of Gps(n,m), and X∨Y∈W∨Y.
Using Lemma 5.4(i),
[X⟩m∩[Y⟩m∈[W⟩m∩[Y⟩m, and hence
[TABLE]
By Lemma 5.4(i) again, we have φ1(X)∨φ1(Y)∈φ1(W)∨φ1(Y), it follows from Remark 3.3 that
φ1(W)⊂φ1(X)∨φ1(Y).
Thus, if X∼mcY with W⊂X∨Y, then φ1(X)∼mcφ1(Y) with φ1(W)⊂φ1(X)∨φ1(Y).
Similarly, considering φ1−1, we have that φ1(X)∼mcφ1(Y) with φ1(W)⊂φ1(X)∨φ1(Y) implies that
X∼mcY with W⊂X∨Y.
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Lemma 5.7
Let φ be an automorphism of Gps(2m,m) (where m≥2). If φ maps some star to a star,
then φ maps stars to stars. If φ maps some star to a top, then φ maps stars to tops.
*Proof. *Case 1. φ maps some star to a star.
Then there is a star [P1⟩m such that φ([P1⟩m)=[P1′⟩m.
We prove that φ maps stars to stars as follows.
Let [P2⟩m be any star in Gps(2m,m) with P1∼mcP2 (in Gps(2m,m−1)).
Note that φ carries maximum cliques of Gps(2m,m) to maximum cliques.
By Theorem 4.6,
φ([P2⟩m) is a star or a top. Suppose φ([P2⟩m) is a top. Write φ([P2⟩m)=⟨Q]m. Then
[TABLE]
By Lemma 5.4(ii), we have ∣φ([P1⟩m∩[P2⟩m)∣=∣[P1⟩m∩[P2⟩m∣=1.
But by Lemma 5.5 we get ∣[P1′⟩m∩⟨Q]m∣=ps−1(p+1)>1, a contradiction.
Therefore, φ([P2⟩m) is a star for any star [P2⟩m in Gps(2m,m) with P1∼mcP2.
Now, let [P⟩m be any star in Gps(2m,m) with d(P1,P)=k>1. By Lemma 5.2,
there are vertices A1,…,A2k−1 of Gps(2m,m−1) such that
P1∼mcA1∼mc⋯∼mcA2k−1∼mcP.
Applying the above result, all φ([A1⟩m),…,φ([A2k−1⟩m),φ([P⟩m) are stars.
Therefore, φ maps stars to stars.
Case 2. φ maps some star to a top.
Let ψ(X)=(φ(X))⊥, X∈V(Gps(2m,m)).
By (3.6) and (3.8), it is clear that ψ is a surjection from V(Gps(2m,m)) to itself. By (3.14),
ψ is also an automorphism of Gps(2m,m). Using (4.9), ψ maps some star to a star. It follows from Step 1 that
ψ maps stars to stars. Applying (4.9) again, φ maps stars to tops.
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Let R be a commutative local ring and n≥3. A 1-subspace of Rn is called a line,
and a 2-subspace of Rn is called a plane. Let P(Rn) be the set of lines of Rn, and P(Rn) is called the projective space of Rn.
A bijective map f:P(Rn)→P(Rn) is called a projectivity or collineation if f satisfies the following properties:
(a) For lines L1 and L2, L1+L2 (where L1+L2 is the direct sum of modules) is a plane if and only if f(L1)+f(L2) is a plane.
(b) Suppose L1+L2 is a plane and L is a line. Then L⊂L1+L2 if and only if f(L)⊂f(L1)+f(L2). Thus, a projectivity is a bijection between
lines which preserves planes (cf. [19]).
Remark 5.8
When R=Zps, for lines L1 and L2, L1+L2 is a plane if and only if L1∼mcL2 in V(Gps(n,1)).
Moreover, if L1∼mcL2, then L1+L2=L1∨L2 by Lemma 3.5(ii).
We have the following fundamental theorem of projective geometry [19] over R :
Theorem 5.9
(see [19, Theorem I.13])* Let R be a commutative local ring and n≥3. Suppose that
f:P(Rn)→P(Rn) is a projectivity. Then, there is a semi-linear bijection ϕ:Rn→Rn such that
f=P(ϕ).*
Proof of Theorem 5.1. Let φ be an automorphism of Gps(n,m) where n≥2m≥4.
Since φ carries maximum cliques to maximum cliques, Theorem 4.6 and Lemma 5.7 imply that
φ maps stars to stars, or φ maps stars to tops with n=2m.
Case 1. φ maps stars to stars.
Let
[TABLE]
Define the map φ1:V(Gps(n,m−1))→V(Gps(n,m−1)) by φ1(X)=X′. By Lemma 5.6,
φ1 is an automorphism of Gps(n,m−1), φ is uniquely determined by φ1, and
[TABLE]
Moreover, for X,Y,W∈V(Gps(n,m−1)), X∼mcY if and only if φ1(X)∼mcφ1(Y);
X∼mcY with W⊂X∨Y if and only if φ1(X)∼mcφ1(Y) with φ1(W)⊂φ1(X)∨φ1(Y).
Note that every maximum clique of Gps(n,m−k) (1≤k≤m−1) is a star. The φ1 maps stars to stars.
Put φ0=φ. Similarly, we can define an automorphism
φk:V(Gps(n,m−k))→V(Gps(n,m−k)), such that φk−1 is uniquely determined by φk and
[TABLE]
k=1,…,m−1. Moreover, for all X,Y,W∈V(Gps(n,m−k)), X∼mcY if and only if φk(X)∼mcφk(Y);
X∼mcY with W⊂X∨Y if and only if φk(X)∼mcφk(Y) with φk(W)⊂φk(X)∨φk(Y).
k=1,…,m−1.
Let R=Zps.
Clearly, P(Rn)=V(Gps(n,1)) and φm−1 is a bijective map from P(Rn) to itself.
By Remark 5.8, φm−1:P(Rn)→P(Rn) is a projectivity.
By Theorem 5.9, there is a semi-linear bijection ϕ:Rn→Rn such that φm−1=P(ϕ).
Since 1 generates Zps, every ring automorphism of Zps is the identity mapping.
Consequently, every semi-linear bijection ϕ:Rn→Rn is a linear bijection.
Therefore, there exists U∈GLn(Zps) such that
[TABLE]
For any X∈V(Gps(n,2)), by Lemma 5.3, there are X1,X2∈V(Gps(n,1)) such that \scriptsize X=X_{1}\vee X_{2}=\left(\begin{array}[]{c}X_{1}\\
X_{2}\\
\end{array}\right) with X1∼mcX2.
Since φm−1(X1)∼mcφm−1(X2), from (5.5) and (5.6), we obtain
[TABLE]
Thus
[TABLE]
For any X∈V(Gps(n,3)), by Lemma 5.3, there are X1,X2∈V(Gps(n,2)) such that X=X1∨X2 with
X1∼mcX2. By Theorems 3.1, 3.5(ii) and (3.2), there is X21∈V(Gps(n,1)) such that
\scriptsize X_{2}=\left(\begin{array}[]{c}X_{21}\\
X_{22}\\
\end{array}\right) and \scriptsize X=\left(\begin{array}[]{c}X_{1}\\
X_{22}\\
\end{array}\right), where X22=X1∩X2 is a 2-subspace. Note that φm−2(X1)∼mcφm−2(X2).
Applying (5.5) and (5.7), we have
[TABLE]
Therefore, we get
[TABLE]
Similarly, we can prove that
[TABLE]
Case 2. φ maps stars to tops with n=2m.
Let ψ(X)=(φ(X))⊥, X∈V(Gps(2m,m)).
By (3.6) and (3.8), ψ is surjection from V(Gps(2m,m)) to itself. By (3.14),
ψ is also an automorphism of Gps(2m,m). Using (4.9), ψ maps stars to stars. By the Case 1,
there exists U∈GLn(Zps) such that ψ(X)=XU, X∈V(Gps(2m,m)). Thus
[TABLE]
By above discussion, we complete the proof of Theorem 5.1.
□
Remark 5.10
Suppose that 2≤m<n<2m. Then every maximum clique of Gps(n,m) is a top. Recall that Gps(n,m) is isomorphic to Gps(n,n−m).
By the bijection Y↦Y⊥, it is easy to see that every automorphism φ of Gps(n,m)
is of the form φ(X)=(XU)⊥, where U∈GLn(Zps).
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