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English Pages 112 [136] Year 1984
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1SB.
I.
General cohomology theory and K-theory,
4.
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J.F.ADAMS
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8.
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10.
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ranges II,
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P.DU VAL
F.F.BONSALL & J.DUNCAN
in topology,
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(ed.)
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introduction to topological
(eds.)
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of Newcastle-upon-Tyne,
August
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in
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P.WELCH
R.BROWN & T.L.THICKSTUN
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Groups - St Andrews
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1980,
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A.KOCK
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in ergodic theory,
G.M.KELLY M.J.FIELD M.J.FIELD
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Durham
1981,
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a view towards
several
an algebraic
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(eds.)
(ed.)
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E.S.LANDER (algebraic knots),
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Linear differential operators,
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Probability,
80.
Introduction to the representation theory of
82.
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84.
Finite
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(eds.)
locally
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in combinatorics:
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E.J.N.LOOIJENGA
P.K.DRAXL
Combinatorial Conference 83.
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for the ninth British (ed.)
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in set theory,
(ed.)
A.R.D.MATHIAS
(ed.)
C.FAITH & S.PAGE
89.
An F-space
90.
Polytopes and symmetry,
sampler,
N.J.KALTON,
N.T.PECK & J.W.ROBERTS
S.A.ROBERTSON
London Mathematical Society Lecture Note Series:
90
//
Polytopes and Symmetry STEWART A.
ROBERTSON
Professor of Pure Mathematics, University of Southampton
CAMBRIDGE UNIVERSITY PRESS Cambridge London
New York
Melbourne
Sydney
New Rochelle
Trent University U&rery
PeTEfieOROUQK, out.
Published by the Press The Pitt Building,
Syndicate
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©Cambridge University Press First published
of the University of Cambridge
Trumpington Street,
Melbourne 3206,
1984
Library of Congress
catalogue card number:
Stewart A.
Polytopes and symmetry Society lecture note Polytopes
I.
Title
512'. 33
ISBN
0
521
II.
Series
QA691
27739 6
(London Mathematical
series,
Cambridge
83-15171
British Library Cataloguing in Publication Data
1.
Australia
1984
Printed in Great Britain at the University Press,
Robertson,
1RP
USA
ISSN 0076-0552;
90)
Contents Preface
vii
Synopsis 1.
2.
3.
The Space of Polytopes 1.
Euclidean space
1
2.
Affine hulls of finite sets
2
3.
Lattice structure
3
4.
Polytopes
3
5.
The Hausdorff metric
4
6.
The space of polytopes
6
7.
Similarity and congruence
8
8.
Euclidean similarity
9
9.
The similarity space of polytopes
11
Combinatorial structure 1.
Facial structure
12
2.
Combinatorial equivalence
14
3.
Topological structure of combinatorial types
18
4.
The three standard sequences
23
5.
Simple and simplicial polytopes
24
6.
Duality and polarity
25
7.
Joins
28
8.
Cones
29
9.
Regularity
30
Symmetry equivalence 1.
Transformation groups
35
2.
Slices
36
3.
Normal polytopes
39
4.
Symmetry equivalence
40
5.
Symmetry types as orbit types
42
6.
Symmetry invariants
44
7.
Symmetry equivalence and polarity
46
VI
4.
Products and sums
.
5.
1
Linear decomposition
47
2.
The rectangular product
50
3.
Combinatorial structure
51
4.
Lattice products
51
5.
Face-lattice of rectangular products
52
6.
Combinatorial automorphisms
53
7.
Symmetry groups
54
8.
Deficiency and perfection
55
9.
The rectangular sum
56
Polygons
.
6.
1
Combinatorial structure
58
2.
Possible symmetry groups
60
3.
Symmetry types
61
4.
Deficiency
62
5.
Triangle s
64
6.
Quadrilaterals
68
7.
The
71
1-skeleton
Polyhedra
.
1
Some combinatorial properties of polyhedra
74
2.
Cuboids
75
3.
Vertex-regular polyhedra
79
4.
The nonprismatic groups
84
5.
The prismatic groups
93
6.
Face-regular polyhedra
96
7.
Edge-regular polyhedra
97
8.
Perfect polyhedra
100
Concluding remarks
101
Bibliography
104
Index of symbols
107
Index of names
109
General Index
110
Preface These notes are intended to give a fairly systematic exposition of an approach to the symmetry classification of convex polytopes that casts some fresh light on classical ideas and generates a number of new theorems.
The theory is far from complete, and there is a range of
attractive unsolved problems.
I hope that the level of sophistication
will he found suitable for anyone with a knowledge of contemporary pure mathematics at first degree level. The work has developed sporadically over almost twenty years. In the early stages,
I worked in collaboration with Sheila Carter and
Hugh Morton at Liverpool.
At that time we concentrated on highly
symmetric polytopes, but many of the key ideas apply equally well to the study of polytopes in general.
We were greatly helped in these days by
the generous advice and encouragement of C.T.C. Wall.
Morton's
influence is particularly strong in Chapter 4, which is based on previously unpublished joint work, while Chapter 6 owes much to Sheila Carter's patient investigation of symmetric polyhedra. Southampton in 1970, geometrical insight.
Since coming to
I have received the benefit of A.W. Deicke's acute Deicke’s contributions to my understanding of
cuboids and polyhedra generally have been considerable.
Other
colleagues, notably David Chillingworth, Gareth Jones and David Singerman, have helped me by producing good examples and neat lines of argument in response to my questions.
In recent years, D.G. Kendall has
been developing a theory of shapes for finite sets of points in Euclidean space that has something in common with my approach to polytopes, although Kendall is concerned with a rather different class of problems. His concern is with statistical questions, and convexity does not hold the central position that I have given it here.
Kendall's work makes
considerable use of metrical ideas, which I have used only to generate topologies.
Nevertheless,
there is a common spirit in the two theories,
and the reader who sees anything of interest in this account will certainly derive great benefit from a study of Kendall's work. Kendall
(1983)
See
for a recent version and references to previous and forth¬
coming articles. Another substantial piece of work that is related to my approach to polytopes is Schwarzenberger's study of crystallography in n-dimensional space
(Schwarzenberger (1980)).
viii
Schwarzenberger gives a systematic treatment of the concepts needed to provide a coherent framework for the classification of 'crystal'
structures in Euclidean n-space
tures involved are lattices in
En
En
.
The geometrical struc¬
rather than polytopes,
and the groups
are infinite discrete subgroups of the Euclidean group rather than finite subgroups of the orthogonal group.
The situation in crystal¬
lography is more difficult to handle than in the theory of polytopes, since the symmetry groups themselves admit continuous deformations. I thank I.M. James for his patient encouragement, June Kerry for her efficient work in preparing the typescript,
and D.G. Kendall for
his friendly attitude in giving me access to some of his unpublished work.
Southampton June,
1983.
S.A. Robertson
0.
SYNOPSIS
The following is a brief outline of some of the main ideas and results that are discussed in detail in the main body of the text. There is no direct relation between the organisation of the paragraphs here and the arrangement of the various chapters. 1.
Euclidean space The polytopes discussed in this book are convex polytopes in
Euclidean n-space
E
,
where
n
is any positive integer.
So that all
polytopes can be treated simultaneously as members of a single family, it is convenient to regard
En
as a fixed linear subspace of
Consequently, we employ the union
E
of all the spaces
receptacle for all polytopes, referring to 2.
E
En
En+1
.
as a
as Euclidean space.
Polytopes Our objects of study are the convex hulls
finite subsets conv A
A
of
E
.
The dimension
dim P
is the dimension of its affine hull
called an n-polytope if
dim P = n
.
P = conv A
of the
of a polytope
aff P = aff A ,
Thus the empty set
0
P =
and
P
is the
unique (-1)-polytope, while 0-polytopes are singleton subsets of 1-polytopes are closed bounded straight line segments in are
(convex,
3.
Symmetry
plane) polygons,
and 3-polytopes are
E
is
E ,
, 2-polytope
(convex) polyhedra.
The broad aim of the theory is the classification of polytopes according to their geometrical symmetry.
The first step in the creation
of such a theory is the choice of a basic equivalence relation on the family
, 1
The quotient space
consists of the O-dimensional symmetry types of all squares and of all 1-polytopes.
cm Squares *
rect«w«les
and
c l-polijte>pes
xii
8.
Deficiency For each polytope
action
ap
P
we try to find relations between the
and the topological invariants of the symmetry type
to which (the similarity class of)
P
belongs.
,'" n .
z e E
,
In this way
we obtain a sequence of inclusions -,n+l
and we can write
E =
En = lim En . n=l
The space
E
has a real linear structure given by
^(xi)
where
z^ = Ax^ + uy^
Y = (y-)
£ E
.
,
+ y(yi)
i = 1,...
= (zi)
, n,...
The metrical structure of
,
,
for
A,yeR ,
x = (x^)
E
is determined by the
,
0°
familiar Euclidean inner product for all
x,y c E
are then given by
.
< , >
The associated norm ||x |[
= /
and
The resulting metric space E
,
is called Euclidean space.
cause us no trouble, lie in some
En .
,
where ||
||
d(x,y) (E,d)
,
The fact that
x^y^
and Euclidean metric = ||x - y ||
respectively.
E
is not complete will
since we are interested only in subsets of
En
at once.
d
which we denote simply by
Our only reason for introducing
handle all the spaces
=
E
E
that
is to be able to
2
2.
Affine hulls of finite sets Le t
!}-
denote the family of all finite subsets of
denote the number of elements in
A e ^ by frA
iff
A
If
is a singleton
A e
,
{a}
,
a z E
.
We
(and extend this
notation to finite sets in general in Chapter 2). ^A = 1
E
Thus 4^0 = 0
and
.
then any linear combination
E
^ caa
f°r which
I
.t =1 is called an affine combination of A . The set of all aeA aaffine combinations of A is called the affine hul1 aff A of A , any such subset by
A .
X = affA
More generally,
of
affA,
A
A e ^ .
affA = A
iff
happen that
affA ,
then
Then A = 0
aff:(?->• A or
A
affA = affB
A
basis for
S
where
E
,
A z ^
affS
and
denotes the
ACS
.
is a surjective map.
is a singleton
{a}
for distinct sets S
of
A ,
A,
aff S
.
For example,
Of course it may
B e ^ .
If
affA = X
is a proper subset of
is said to be affinely independent and to be an affine
X. The set
is a subset of
A
*£>
of all finite-dimensional linear subspaces of
with inclusion
say.
give
0
-1 .
There is then a parallel projection
where
of
denote the set of all affine planes of the form
and for every proper subset X ,
is called an affine plane generated
for any subset
union of the affine planes Le t
E
and
'honorary membership' of
L = {x-y:x,y e X}
X, Y e ^
.
p:^->^>
poi = 1^ .
X || Y ,
iff
given by
p (X)
= L
,
We say that
P (X) CL P (Y)
or
.
The dimension
dim L
of any
extend this notion to the elements of for each
For convenience, we
assigning to it the dimension
Trivially,
are paral lei, written
F(Y) C PCX)
,
E
X z A •
We say that
L e A
is well-defined, and we
by putting
dim X = dim P(X)
X e A
is an affine k-plane
X = affA .
Then j^A 5 1 + dimX
iff
dim X = k . Exercise: equality Exercise:
Let iff
A e ^ and A
Let
Thus if ^
'^ = Un5l^n •
is affinely independent.
A
.
and j4n
affine planes in
with
En ,
Then
ACED
for some
n .
Hence
af f A C En .
denote the sets of all finite subsets and of all respectively,
then
y =unil
n
and
3
3.
Lattice structure Both
the set
2
3"
\A
and
inherit the partial order by inclusion from
of all subsets of
to this partial order. lower bound of
E ,
In 3 ,
A,B e 3
are
and both are lattices with respect
the least upper bound and greatest
A C) B
and
we denote the least upper bound of greatest lower bound of X U Y = X y \
iff
X, Y e jA
X C Y
or
Let
A,B e 3
af f (A U B) = X y Y ,
and
and
and
Y
is just
Y3 X ,
of all affine planes that contain Exercise:
X
A 0 B
respectively. by
X t)Y ,
XOY .
since
In •SA' #
while the
The fact is that
X y Y
is the intersection
X U Y .
X = affA,
Y = affB .
aff(AC)B)CI X O Y .
Then
F ind
A C B =>
A, B
XCY ,
such that
the last inclusion is proper. Exercise: p(X W Y)
4.
For all
L,M
= p(X) +p(Y)
L fe) M = L + M . and
For all
p (X H Y) C P (X) A P 00
.
Polytopes Let
all
aeA,
A £ 3 • t_ 5 0 3.
.t a aeA a is called a convex combination of ““
of
wThere
Any subset
P = conv A ,
polytope or simply a polytope.
1
- •
A
A .
Z
Any affine combination
set of all convex combinations of
■
■
dim(affA)
,
e
is said to be of dimension
and we refer to
The empty set
A ,
. ——
A e 3 >
A Cl conv A Cl affA = aff(convA)
P = convA
such that, for
is called the convex hull
It follows at once from the definitions
If
X,Y e vsA ,
The
1-polytopes are closed
2-polytope is called a polygon and a
3—polytope is called a polyhedron. Notice that if
A, B £ 3
A more subtle fact is that if conv(A set
B)
V e 3
conv W E
D
.
anci
A C B ,
conv A = conv B = P ,
It follows that for each polytope
such that
P = conv V
is a proper subset of
whose convex hull is
P
.
then conv A Cl conv B .
P .
P
then
P =
there is a unique
and for every proper subset Thus
V
The elements of
is the V
W
of
V ,
'smallest' subset of
are called the vertices
of
P ,
and
V
is called the vertex set
tionship between
vert
and
conv
(P
-*
vert P
of
P
The rela-
.
is shown in the commutative diagram
V Thus
vert
is injective and
conv
is surjective.
It follows from the first Exercise of §2 that an n-polytope has at least vert P
n + 1
vertices,
and has exactly
is affinely independent.
that an n-polytope
P
simp1ex.
E .
n + 1
iff
vertices
iff
these vertices
Such an n-polytope is called an n-
-1 £ n $ 1 ,
Of course for
vertices
Another way of putting this is to say
has exactly
are 'in general position' in
n + 1
P
every n-polytope is an n-simplex.
A 2-simplex is called a triangle and a 3-simplex is called a tetrahedron for reasons that either are familiar already or will become clear shortly. With the second Exercise of § 2 in mind, we note that for each
r
y
A:F(P) -> F(Q) determined
A(A.) = B for some labelling of F _^(Q) Now J 1 = aff B. is given by a unique equation = 1 ,
K.
is sufficiently small, where
Let
£•
= w.
- v.
and
111
b. I 0 J T b. - a. Since J J
n• J
= 1
and
i
Let the combinatorial equivalence
B be such that
En
in the sense that its vertices are
B:FQ(P) - Fq(Q)
isomorphism.
provided
P
where, for some
and the map
by
to
Q
Uij(P)
=
j(Q)
for all
= 1
iff
(P) = 1
,
and hence
+ +