Discrete Mathematics North-Holland
ON INCIDENCE PROJECTIVE
MATRICES PLANES
OF
FINITE
MONTARON
Bernard
Renix Electronique, Received
227
56 (1985’) 227-237
December
BP 1146, 31036
Toulouse,
Ceder,
France
1984
In Section 1 and 2, we show that any incidence matrix of a finite projective plane (FPP) can be arranged as a special matrix in which many terms are known. The unknown part of this ordered form of an incidence matrix is shown to be formed by permutation sub-matrices having interesting algebraic and combinatoric properties (Section 3). In Section 4, we introduce a special class of FPP called ‘simple’ FPP. The existence of a simple FPP of order n is related to the existence of a particular n-group called ‘projector’ group. Finally, we make a search of projector groups of orders up to 12, and we give examples of simple FPP, with orders up to 8.
1. Introduction The following
properties
characterize
the incidence
matrix
of a F’PP of order
n
[II); (1) the
(see
matrix is (n*+ n + 1, n2+ IZ+ 1) and their terms are zero and one; (2) each row and each column contains exactly n + 1 non-zero terms; (3) for each pair of columns (resp. rows) (jI, j2), there exists a unique row (resp. column) i, such that terms (i, jJ and (i j2) are ones; (4) two incidence matrices which differ only by permutations of the rows or the columns correspond to the same Fl’P.
2. Ordered form of an FPP
incidence
matrix
According to property (4), we may order any FPP incidence matrix, by permuting rows or columns. An ordering process is described in this section, in which the ordered form is obtained after 5 permutation steps. The permutations used at each step are chosen so that they do not modify parts of the matrix which have been ordered at the previous steps. Step 1. By permuting columns, the to II + 1. By permuting rows (except of column 1 are placed on rows 1 to Fig. 1. The sub-matrices Aii are (n, Aoo = 0, 0012-365X/85/$3.30
0
n + 1 ones of row 1 are placed on columns 1 row 1, which is not moved), then n + 1 ones r~+ 1. The matrix has now the form shown in n). Property (3) implies that
(zero matrix). 1985, Elsevier
Science
Publishers
B.V.
(North-Holland)
8. Montaron
228
1
11...11
oo...oo
oo.........oo
oo...oo
J_
’.
A00
A01
. ........
A
.
*10
A11
.........
*1n
0 0 . . . .
. . . .
.
0
.
.
0
.
.
A
Anl
on
i 0 0 .
0 .
. .
. .
.
. .
. .
.
.
0
’. .
no.
A
.*.*....I
ml
0
Fig. 1
Step 2. n ones of row 2 are distributed amongst matrices Aor, A,,*, . . _, Ao,. By permuting columns >n + 1, these n ones are placed in Aor, which first row is now ‘all 1’. By .property (3) the remaining part of A,,r is ‘all 0’. The same process is then applied to A,,, . . _ , A,,. Similarly, by permuting rows >n + 1, one can arrange the ones of columns 2 to n + 1 in such a way that matrices AkO, 1s k s n, have their column k ‘all 1’. This does not modify matrices A,r, . . . , Ao,. So, we get V k 1 c k s n,
Ak,, = ‘AOk, and A,,
is ‘all 0’ except row k which is ‘all 1’.
Taking into account the new form of AOk and A,,,, k # 0, and properties (2), (3), the Aij matrices, i, jf 0, appear now to have exactly one ‘1’ per row and per column: Vi#O,
VjfO,
AijEP,,
where P,, is the set of all (n, n) permutation
matrices.
Step 3. Any permutation of the columns containing the submatrix Arj, for a given jf 0, does not modify the ordered form obtained at Steps 1 and 2. Since Arj is a permutation matrix, we can arrange their columns so that AIj becomes the identity matrix I,. This process is applied independently for all j# 0. Permutations on the rows containing Air, i 2 2, are used to transform these matrices into I,. So, we get Vk, k#O,
Akl=Alk
= I,.
By property
(3), main
Vi, Vj, i, j 2 2, where
On incidence
matrices
diagonals
of matrices
tr(A,)
of finite projective planes
229
A+ i, j > 2, are now ‘all 0’
= 0 or equivalently
A, E I?:,
PE is the set of (n, n) permutation matrices without fixed point. Two (n, m) matrices
Definition.
be antipodal (denoted Lemma
1.
A, B which terms
are zero and one, are said to
A () B) iff no ‘1’ has the same location
in A and in B.
If A, B, C E P,,, then
A()B+AC()BC
and CA()CB.
This lemma will be used in Section 3. By property (3), after Step 3, for all i, i 32 (resp. Vj, j 3 2) the n - 1 matrices Aii, j 2 2 (resp. i 2 2) are pairwise antipodal. Since Aii have an ‘all 0’ diagonal, we get:
Theorem
1. The Aii sub-matrices of the ordered form of the FPP incidence matrix,
are such that: Vi, i 2 2
i
Aij = J, - I,,,
j=2
Vj, j Z- 2
2 Aii = J,, - I,,, i=2
where J,, is the ‘all 1’ (n, n) matrix. Step 4. Let p, q E P,. Then qp is obtained by permuting columns of q, and tpq is obtained by permuting rows of q. p and ‘p are used to permute rows and columns of the incidence matrix as shown in Fig. 2. This transformation does not modify
P
............. .............
Aon
,............
*1Tl
....... ...... . .
A2* .
.
.
.
. A nn
Fig. 2
B. Montaron
230
the properties
of the ordered
vi, iz
1,
ViiSl,
form after
Step 1, 2, 3, since
A,jp = A,j, ‘PA~~P = A,j; ‘pAi
= Aio, ‘pAi 1p = Ai1
and Vi, j>2, Let $ denote
tpAijp E P”,. an equivalence
binary
relation
over Pz, defined
as follows:
Vq,q’EP0,,q$q’tt3pEPJq’=tpqp. We have now proved
the following
theorem:
Theorem 2. After Step 3, one of the Aii matrices for i,j 2 2 (for instance be chosen amongst the leaders of equivalence classes of P2$. This is step 4-the
number
of possibilities
for AZ2 is now quite
A,J
may
small.
Lemma 2. Let q E P”,, then (1) q symmetrical (‘q = q) * Vp E P,, tp q p symmetrical, (2) q antisymmetrical (tq ( > q) + Vp E P,, tp q p antisymmetrical, (3) VP E pm tP 4 P E p”,. If n is odd, there are no symmetrical matrices in P”,. If n is ‘even, the whole set of symmetrical matrices of P”,, forms an equivalence class of PQ$, whose leader is shown in Fig. 3. The following results on leaders are easily deduced from the decomposition of permutation by disjoined antisymmetrical matrices of equation
cycles. The number of equivalence of Pf is equal to the number
where k > 1 and 3
Fig. 3
classes in the set of of integral solutions
(x,, x2, . . . , xk) is related on the main
0
1
1
0
diagonal
to a of L,.
231
On incidence matrices of finite projective planes
”
10
=
3+3+4 3+7 5+5 4+6
:
5 classes
Fig. 4
These sub-matrices are respectively permutation matrices. An example
(x1, x1), (x,, x,), . . . , (xk, xk) and are circular is shown for L,, in Fig. 4.
The number of equivalence classes in the set of Pz matrices which are not symmetrical and not antisymmetrical is equal to the number of integral solutions of equations
where kal, x1=2, x,#2 and ~cx,=zx,~..*~x,. xk) is related to a leader Each vector (x1,. . . , previously. See example in Fig. 5. The number given in Fig. 6 for n G 12.
II=
10:
Example:
Llo =
2+2+2+4 2+2+3+3 2+2+6 2+3+5 2+4+4 2+8
matrix
of choices
6 classes
10=2+2+2+/l r 01100000000 1000000000 0001000000 0010000000 0000010000 0000100000 %0000000100
Fig. 5
L, of P3$
1
as explained
for AZ2 at Step 4 is
232
B. Montaron
S.
n
21 30 4 50 61 70 81 90 10 11 12
1
1 0 1
Fig. 6. S = symmetrical
A.S.
Others
0 1 1 1 7 2 3 4 5 6 9
0 0 c1 1 1 3 3 4 6 Ii 11
leaders,
Total
1 1 2 2 4 4 7 8 12 14 21
AS. = antisymmetrical
leaders.
1
11
00
00
1
111
000
000
000
1 1
00 00
11 00
00 11
0 0
10 10
10 01
10 01
1 1 1
000 000 000
111 000 000
000 111 000
000 000 111
D 0
01 01
10 01
01 10
0 0 0
100 100 100
100 010 001
100 010 001
100 010 001
0 0 0
010 010 010
100 010 001
010 001 100
001 100 010
0 0 0
001 001 001
100 010 001
001 100 010
010 001 100
n=2
n=3
100 00010
01000 00100 00010 00001 10000
01000
1000 00100
00001 10000 01000 00100 00010
00100 00010 00001 10000 01000
OOOOl 10000 01000 00100 00010
01000 00100 00010 00001 10000
00010 00001 10000 01000 00100
00010 00001 10000 01000 00100
01000 00100 00010 00001 10000
00001 10000 01000 00100 00010
00100 00010 00001 10000 01000
00001 10000 01000 00100 00010
00010 00001 10000 01000 00100
00100 00010 00001 10000 01000
01000 00100 00010 00001 10000
00
0000
forms.
10
00001
1
10000
10000
n=
Fig. 7. Ordered
000
0
1000 0001 0010
0010 0001 1000 0100
0001 0010 0100 1000
0010 0001 1000 0100
0001 0010 0100 1000
0100 lOD0 0001 0010
0001 0010 0100 1000
0100 1000 0001 0010
0010 0001 1000 0100
0100
n=4
5
For n = 4 and 5, only A,, sub-matrices
with i, j 2 2 are shown.
of finiteprojectiueplanes
On incidence matrices
Step 5. The leaders The sequence order)
233
at Step 4 for AZ2 have the first row = (0, 1, 0, . . . ,0).
given
of each first row of matrices
A,,,
. . . , Azn forms
(in an arbitrary
the vectors
(0, 0, 1, 0, . . . , 0); (0, 0, 0, 1, 0, . . . , 0); . * * ; (0, . . . ) 0, l), where
the ‘1’ takes
every
place except
columns
1 and 2.
By permuting blocks of n columns of the incidence matrix, it is possible to arrange the matrices A,,, . . . , A*,,, in a different order without modifying the properties of the ordered form obtained after Step 4. We may choose an arrangement so that first row of AZ3 is (0, 0, 1, 0, . . . , 0), etc. and first row of A,, is (0, 0, . . . , 0, 1). Similarly, we can arrange the matrices A32, _ . . , A,,z in a new order. Finally at Step 5: Vi 2 2, first row of Azi and Ai, has a ‘1’ in column
i.
The matrices obtained after Step 5 are the ordered forms of FPP incidence matrix. For small values of n (2,3,4,5) the ordered forms (Fig. 7) exist and are unique. This shows the existence and unicity of FPP of orders 2, 3, 4, 5.
3. Some other properties
of sub-matrices
Aij
Theorem 1 gives relations between matrices A,, i, j 2 2. Since for permutation matrices p, one has p -’ = ‘p, other relations can be established. Lemma 3. Let Airi, A,, A+ Aipj, be sub-matrices of the ordered form of an FPP incidence matrix, with i, i’, j, j’ 2 2 and i # i’; j # j’. Then property (3) applied to the matrix
is equivalent
to
Ai,jtAijAij’tAi,j, This lemma Theorem
( ) I,.
is easily proved
by calculating
tr(Ai,itAijAij,tAi,j,).
2. vi, j 3 2(i # j)
2
AiktAjk = J,, - I,,,
k=2
Vi, j32(i#
j)
f
Aki’Ak; =Jn-&,.
k=2
Proof
follows
directly
from Lemma
1 and Lemma
3.
B. Montaron
234
Let Vo, Vl, . . . , V;-’
be the column vectors defined as follows:
where Ai+l,j+l are sub-matrices of the ordered form of an FPP incidence matrix. For all i, 1 c i =SII - 1, let I+ = [ Vo, Vt, . _ . , Vy-‘I, Theorem square
3. The (n, n) matrices L1, II,, . . . , I+-,
then: form a complete set of latin
of order n (see [l]).
4. “Simple”
FPP
Definition. An FPP is called simple if the Aii sub-matrices of the ordered form of the incidence matrix have the following properties: (1) Sub-matrices Aij, i, j 5 2 form a latin square; each row Aiz, . , . , A, and each column Azi, . . . , A, is formed of the same set E of n - 1 matrices; (2) The set {I,,}UE is a multiplicative group. As shown in Fig. 7, FPP of orders 2, 3, 4, 5 are all simple. Definition. Let G be a multiplicative group. G is called a projector group iff there exists a latin square T = (tij) of order n - 1, rows and columns of which are formed of set G -{l} such that ti&tij,t;;
# 1,
Vi, i’, j, j’, if
i’, j# j’.
Latin square T is called projector. Since T can be ordered by permutation
of rows and columns, the first row and the
first column may be ordered arbitrarily. Definition. The projector index p of an n-group G is the maximum number of complete rows of a projector table T, that it is possible to construct. p is such that lCpq:n-1. Theorem projector
4. There n-group,
exists a simple FPP of order n ijf there exists a multiplicative formed by (n, n) permutation matrices which sum is J,.
Proof follows directly from definitions (simple FPP and projector group), and from Theorem 1, Lemma 3. The projector latin square T of the group of
On incidence
Theorem
matrices
of finite projectiue planes
4 forms the latin square of A, I,’ J‘>-. 2 sub-matrices
235
of the ordered form
of the incidence matrix.
4. Projector
groups of order s12
All group types of order ~12 are known (see [2]). For each type of group shown in Fig. 8 we tried to construct projector tables T, with as many rows as possible. No simple FPP of order 6 or 10 exists, since there are no projector
groups of
order 6 or 10. GROUP TYPE
Fig. 8. Projector
CROUP PROJECTOR II'!DEX "
CROUP TYPE
GROUP PROJECTOR ORDER I'dEX n P
(See I;‘])
ORZER
Z/2Z (.) Z/32 (.) z/42 2/2ZxZ/?Z(.) Z/57 (.) Z/62. D3 = 53 Z/77. c.1 Z/riZ Z/42x2/27.
2 3 4 4 5 6 6 7 8 F!
1 2 1 3 4 1 1 6 1 3
w7Z)3
8
7
D6
c12.
(+) = to be proved;
(.)
index of group of order
2
(See 121) 02 D4 Z/w, Z/3ZXZ/3Z(.) Z/lOZ Z/llZ (.) Z/l?? Z/2ZXZ/6Z A4 03
2
3
4
4
6
13
5
R n 9 9 10 11 12 12 I2 12
2 7 2 8 1 10 1 a4 2(+) l(+)
12
2(+)
(.) = projector
groups
(p = n - 1).
6 5
362514 4
15
5
316
2
6
3
4
2
Fig. 9
5. Simple FPP of order 7 There exists a unique simple FPP of order 7, based on a multiplicative projector group isomorphic to Z/72. The projector latin square of Z/72 is shown in Fig. 9. Let Mi be a permutation matrix (7,7), corresponding to the element i of Z/72. M,, = I,, M, is the circular permutation matrix and Mk = M’; for k = 2, . . . ,6. The multiplicative projector 7-group of Theorem 4 is G = {MO, Ml, . . . , Me}. One has M,+M,+. * . + M6 = J,. The sub-matrices A,, i, i 3 2 of the ordered form of the FPP incidence matrix are obtained by replacing i by Mi in the projector latin square of Fig. 9.
236
B. Montaron
6. Simple FPP of order 8
Let:
E=I,,
Let:
MO = 112,
A=
M’,[;
,“I,
M,=[;
then, we get M,,+M,=***+M,=J, projector g-group of permutation
and G = {MO, . . . , M,} is a multiplicative matrices, isomorphic to (Z/2Z)3. The projector latin square of G is obtained by replacing i by Mi in the projector latin square of (Z/22)’ shown in Fig. 10. Exactly 8 different projector latin squares of (Z/22)” can be built. I.
2
3
4
2
6
4
13
7
5
6
12
3
7
7
6
7
7
n
1
4
5
3
3
4
4
15
5
3
6
6
7
17
7
5
2
613
5
6
7
7
5
S
Fig. 10
7. Simple FPP of orders 9 and 11 There
exist many simple
FPP
of order
9 based on a multiplicative
group
isomorphic to the projector group (Z/32)‘. There exists a unique simple FPP of order 11 based on a multiplicative group isomorphic to Z/llZ. 8. Order 12 The unique candidate for projector 12-group is Z/2ZX Z/62. A multiplicative permutation matrice 12-group isomorphic to Z/2ZX Z/62 is
Fig. 11
On incidence
G = {A& M,, . . . , i&},
matrices
of
finite projectiue planes
231
with
One has Mo+M1+~~~+M,1=J12. Unfortunately, up to now, we built only 4 row-projector tables. One example of these partial projector tables is obtained by replacing i by Mi in Fig. 11. Applying Theorem 7 to this partial ordered form of an hypothetical incidence matrix, we get a set of 4 latin squares of order 12, pairwise orthogonal. It would be interesting to check the existence of simple FPP of order 12 using a computer.
References [ 11 D.R. Hugues and F.C. Piper, Projective Planes [2] A. Bouvier and D. Richard Hermann, Groupes
(Springer, (Herman,
Berlin, 1973). Paris, 1979).