Visual
Magic Squares and Group Orbits I
2. Conway Squares and Their Representations
The colored shapes in the table below will be used
to represent sixteen objects, with each one having four visual attributes:
color, border, shape, and size. As indicated in the table, each attribute has
two values: color can be green or yellow, border can be fat or thin, shape can
be square or triangle, and size can be small or large.
Illustration 2.1
Definition
2.1. The collection of sixteen colored
shapes in Illustration 2.1 will be called Conway items. A set of four Conway items is said to have the Conway property just in case both values of each attribute (color, border,
shape, and size) occur exactly twice. Notice that both the left and right main
diagonals of the table in Illustration 2.1 each have the Conway property with green and yellow occurring twice for color,
fat and thin occurring twice for border, square and triangle occurring twice
for shape, and small and large occurring twice for size. However, none of the
rows or columns have the Conway property.
A Conway square
is any rearrangement of the table above in which each
of the four rows, the four columns, and the two (left and right) main diagonals
have the Conway property. In addition, we will refer to the process of
creating Conway squares in pursuit of finding all Conway squares as the Conway game.
We note that our use of Conway items to create visual magic squares is our extension and
modification of the visual approach used in Section 1 to create Euler squares.
We call these new visual magic squares 'Conway squares' because in [1] (p. 778) John Conway calls a (base 10) 4 ´ 4 magic square perfect just in case nim-adding any number from 0 to 15 to every
entry of it produces a magic square. Though only base 10 magic squares are
considered there, this notion of preservation under nim-addition gave us a hint
that considering a base 2 representation (see Definition 2.2 below) might be
interesting and fruitful. Furthermore, in Section 3 of this paper we show how
to use this base 2 representation to generate all Conway squares via finite group orbits.
Exercise
2.1. Play the Conway game by rearranging the Conway items in the table above until you have a Conway square. Here is a Conway
items template that you can print out on photo quality paper and cut out to
make your own pieces for the Conway game. Hint: Since both of
the main diagonals in the table have the Conway property you can begin the game with both of these
diagonals on the square.
Exercise
2.2. Play the Conway game starting with
both diagonals as in Exercise 2.1, except that this time interchange the first
two objects on the right main diagonal with the two objects below them on this
diagonal. So, the new right main diagonal starting from the upper right and
proceeding down and to the left should be: the large yellow square with thin
border, the small yellow square with fat border, the large green triangle with
thin border, and the small green triangle with fat border.
Definition
2.2. As with Euler squares, we also want
to numerically code Conway squares. In order to do this, we will first numerically
code our Conway items as ordered 4-tuples (vectors) of zeroes and ones.
So, let [c, b, sh, s] be an ordered 4-tuple of zeroes and ones, then the
different values of c = 0, 1 will represent green, and yellow,
respectively; the different values of b = 0, 1 will represent fat
and thin border, respectively; the different values of sh = 0, 1
will represent square and triangle, respectively; the different values of
s = 0, 1 will represent small and large, respectively. This is the base 2 representation of our Conway items. In order to convert it to a base 10 representation,
we simply set n = 8c + 4b + 2sh + s.
The tables below illustrate this correspondence
between Conway items and their numerical coding in base 2 and base 10.
Base 2 and Base 10 Coding of Conway Items
Illustration 2.2
If the Conway items in a Conway square are
numerically coded using the base 2 (base 10) coding, then the resultant
numerical square will be called a base
2 (base 10) Conway square. For example,
consider the following Conway square and its two numerical codings.
Base 2 and Base 10 Coding of this Conway Square
Illustration 2.3
Exercise
2.3. Code each of the Conway squares found in Exercises 2.1 & 2.2 into their base 2
and base 10 representations, and then verify that these base 10 Conway squares are magic squares.
Theorem
2.3. Every base 10 Conway square is a magic square.
Exercise
2.4. Try to explain why Theorem 2.3 holds
by finding numerical properties of the base 2 coding of a Conway square that force the corresponding base 10 coding to be a
magic square.
Theorem
2.4. Let f be the natural mapping of Euler
items onto Conway items given by mapping each Euler item in Illustration 1.1
onto the corresponding Conway item located in the same position in Illustration 2.1.
(1) If E is an Euler square, then f [E] (the square obtained by applying f to
each item in E) is a Conway square. Furthermore, this mapping provides a 1-1 embedding
of the set of Euler squares into the set of Conway squares.
(2) The embedding in (1) is not an onto mapping, i.e. every Euler square gets
mapped to a Conway square, but some Conway square doesn't come from an Euler square.
Exercise
2.4.
(a) Using the mapping in Theorem 2.4 (1), map all of the Euler squares in
Exercise 1.5 into Conway squares, and check (visually) that the resultant squares
are Conway squares.
(b) After doing (a), try to explain why this mapping works by describing (for
example) how a row of Euler items satisfying the Euler property must get mapped
to a row of Conway items satisfying the Conway Property.
(c) In addition, verify Theorem 2.4 (2) by explaining why the Conway square in Illustration 2.3 could not have come from any
Euler square using the mapping in Theorem 2.4 (1).
Hint for (b) and (c): It is easier to try to use the numerical representations
of these squares, rather than directly using their visual representations in
terms of Euler and Conway items. If you get stuck here, there is more helpful
information below.
One interesting aspect of Theorem 2.4 is that we
have been able to state it in terms of visual objects: Euler and Conway items,
and in terms of visual magic squares: Euler and Conway squares. Though this
visual approach is very appealing in that it allows us to easily create and
recognize these visual magic squares, it is somewhat more difficult to use in
actually proving results about these squares. Often that's the trade off one
deals with in mathematics. Sometimes a visual representation is easier to use
to see what's going on intuitively, but an appropriate numerical representation
provides an immediate well-developed theoretical framework within which we can
more easily state and verify important properties and results. Our intention in
setting Exercise 2.4 was for the reader to experience this situation in doing
math, and hence realize the necessity and usefulness of the numerical
representations. The next theorem is essentially the numerical equivalent of
Theorem 2.4.
Theorem
2.5. Let e be an Euler item, let [i, j] be
its base 4 representation, and let [k, l, m, n] be the base 2 representation of
[i, j]. Further, for each such e let g be the natural mapping sending [i, j] to
[k, l, m, n].
(1) If E is the base 4 representation of an Euler square, then g[E] (the square
obtained by applying g to each entry in E) is the base 2 representation of a Conway square. Furthermore, this mapping provides a 1-1 embedding
of the set of base 4 Euler squares into the set of base 2 Conway squares.
(2) The embedding in (1) is not an onto mapping, i.e. every base 4 Euler square
gets mapped to a base 2 Conway square, but some base 2 Conway square doesn't
come from a base 4 Euler square.
Exercise
2.5. Explain why Theorem 2.5 holds. Again,
note that Theorem 2.5 is just a restatement of Theorem 2.4 in terms of
numerical representations of Euler and Conway squares, and so this exercise is
really just a continuation of Exercise 2.4 (b) and (c) with a more detailed
hint on what numerical representations to use.
Notation. In the following development we will use 'Euler square'
and 'Conway square' to refer to both their corresponding visual item representations,
and to their various numerical representations in different bases. With this
notational convention we now see (can say) that it follows from Theorems 2.4
and 2.5 that every Euler square is a Conway square, but not vice versa. We
noted in Remark 1.7 that it follows from Theorem 1.6 that there are 144
essentially different Euler squares. We know that the Conway squares include these Euler squares, and in the remainder
of this section we will determine the total number of (essentially different) Conway squares. Following the hint in Exercise 1.7, we saw that
it was not difficult to count Euler squares because of the strict and uniform
constraints necessary to have an Euler square. In contrast, the fine structure
of different types of Conway squares is more subtle, and we will now develop the
necessary additional concepts we need to classify and count all Conway squares.
Definition
2.6. Two Conway items are similar
or in the
same similarity class just in case they differ by an even number
of attributes. If a and b are two similar items, we will write a ~ b, and
denote the similarity class of a by [a], i.e. [a] = {b: b ~ a}. Further, any
two Conway items that differ in all 4 attributes will be called complementary or complements of each other. If a and b are complementary items, we will
write a' = b or b' = a, since complements are unique. In addition, any two Conway items that differ in exactly 2 attributes (hence agree in
exactly 2 attributes) will be called bicomplementary
or bicomplements of each other. Also, we will denote the set of all
bicomplements of a by a* (note that bicomplements aren't unique).
In Illustration 2.4
below, we have labeled each Conway item
with its base 10 coding in order to easily refer to each item.
Illustration 2.4
Using the numerical labels in Illustration 2.4,
and considering the left main diagonal, we see that item 0 differs from itself
in 0 attributes, item 0 differs from item 5 in 2 attributes (border and size),
item 0 differs from item 10 in 2 attributes (color and shape), and item 0
differs from object 15 in all 4 attributes (color, border, shape, and size).
So, the items on the left main diagonal, i.e. items 0, 5, 10, and 15, are all
in the same similarity class.
Furthermore, items 0 and 15 are complementary,
since they differ in all 4 attributes, and items 5 and 10 are complementary as well.
In addition, items 0 and 5 are bicomplementary, and so are items 0 and 10,
items 15 and 5, and items 15 and 10.
Exercise
2.6. Verify that the similarity relation ~
defined on Conway items is an equivalence relation, and that there are two equivalence
classes w.r.t. ~ , each one of size eight. Further, verify that there are eight
complementary pairs of items, that each similarity class contains four
complementary pairs, and that each individual item has six bicomplements. Note
that you may represent these items using
the base 10 labels in Illustration 2.4, e.g. 0 ~ 5 and 0' = 15.
Exercise
2.7. Verify that each similarity class can
be written in terms of anyone of its elements as follows: [a] = {a, a'} È a*,
i.e. the similarity class of a is comprised of a, the complement of a, and all
the bicomplements of a.
Exercise
2.8. Write a clear, detailed, math
argument explaining why complementary items have the same bicomplements, i.e.
if a' = b, then a* = b*.
Next, we have the same Conway square as in Illustration 2.3, except that we have also
labeled each object with its base 10 coding. Note that one similarity class {0,
5, 10, 15, 3, 6, 9, 12} occurs on the two main diagonals, and the other
similarity class {14, 13, 2, 1, 11, 7, 8, 4} occurs in the middle of the top
and bottom rows, and in the middle of the leftmost and rightmost columns of the
table. Furthermore, in order to easily distinguish between these two similarity
class, the Conway items in the second similarity class have their numerical
labels underlined.
Illustration 2.5
Definition
2.7. (Diagonal
Types) We will now define three different diagonal types of Conway squares that were previewed Exercises 1.2 in Section 1 and
Exercise 2.3 in this section. For this definition we will let a, b, c, d, and
complements a', b', c', d', range over the eight Conway items in one (unspecified) similarity class, and we will
let w, x, y, z, and complements w', x', y', z', range over the Conway items in the other similarity class.
1. A Type
D1 Conway square
is a Conway square with the items in the two similarity classes
organized as follows:
Illustration 2.6
Note that for ease of viewing, we have partitioned
the pattern for a Type D1 Conway square (the one on the left of the equality in
Illustration 2.6) into two partial squares, each depicting the location of one
of the two similarity classes. We use a plus sign to indicate schematically how
the two patterns are joined together.
Also, the name 'D1' corresponds to constructing a Conway square by placing a Conway item a in the upper left hand corner of the square and
then placing its complement, a', one position below it on the left main
diagonal. It turns out that beginning in this way and completing to a Conway square forces the resulting square to be of Type D1.
2. A Type
D2 Conway square
is a Conway square with the items in the two similarity classes
organized as follows:
Illustration 2.7
Note that for ease of viewing, we have partitioned
the pattern for a Type D2 Conway square (the one on the left of the equality in
Illustration 2.7) into two partial squares, each depicting the location of one
of the two similarity classes. We use a plus sign to indicate schematically how
the two patterns are joined together.
Also, the name 'D2' corresponds to constructing a Conway square by placing a Conway item a in the upper left hand corner of the square and
then placing its complement, a', two positions below it on the left main
diagonal. It turns out that beginning in this way and completing to a Conway square forces the resulting square to be of Type D2.
3. A Type D3 Conway square is a Conway square with all the objects of one similarity class
occurring on the two main diagonals, with all the objects of the other
similarity class occurring in the remaining positions, and with the following
organization:
Illustration 2.8
Note that for ease of viewing, we have partitioned
the pattern for a Type D3 Conway square (the one on the left of the equality in
Illustration 2.8) into two partial squares, each depicting the location of one
of the two similarity classes. We use a plus sign to indicate schematically how
the two patterns are joined together.
Also, the name 'D3' corresponds to constructing a Conway square by placing a Conway item a in the upper left hand corner of the square and
then placing its complement, a', three positions below it on the left main
diagonal. It turns out that beginning in this way and completing to a Conway Square forces the resulting square to be of Type D3.
Theorem
2.8. There are 384 Conway squares of each Diagonal Type (D1, D2, D3), yielding a
total of 1152 Diagonal Type Conway squares.
Corollary
2.9. Each Diagonal Type Conway square is
preserved under the eight symmetry transformations described in Remark 1.7,
i.e. the symmetries of the (geometrical) square. Hence,
there are 48 essentially different
Conway squares of each Diagonal Type (D1, D2, D3), yielding a
total of 144 essentially different Diagonal Type Conway squares.
Sketch of
Proof of Theorem 2.8: Type D1 Conway squares.
Note that we will use a Conway game construction to give a proof sketch, similar to the
hint in Exercise 1.7 using the Euler game to count Euler squares. In this case,
we will play the Conway game, building an arbitrary Type D1 Conway square,
counting all our possible choices along the way, until the rest of the choices
are forced. The reader is encouraged to play the Conway game while reading this proof sketch, mirroring all the
steps in a specific case.
So, we begin by placing an arbitrary Conway item a in the upper left hand corner for which we have 16
possible choices, then a' must go in the first position below a on the left
main diagonal. Next, since we must have the same similarity class occupying the
left main diagonal, we have 6 choices remaining for the first position below a'
on this diagonal, say b, and then b' must go below it on this diagonal. Now, we
have 4 choices remaining for the first position immediately to the right of a
in the first row, say c, and then c' must go in the second row immediately
below a. Thus, we have the following sequence of partial squares:
Finally, it can be seen by playing the Conway game that the rest of the entries are forced and in the correct
positions for a Type D1 Conway square. Hence, there are (16)(6)(4) = 384 Type
D1 Conway squares. ||
Sketch of
Proof of Theorem 2.8: Type D2 Conway squares.
We begin by placing an arbitrary Conway item a in the upper left hand corner for which we have 16
possible choices, then a' must go in the second position below a on the left
main diagonal. Next, since we must have the same similarity class occupying the
left main diagonal, we have 6 choices remaining for the first position below a
on this diagonal, say b, and then b' must go below a' in the last position on
this diagonal. Now, we have 4 choices remaining for the second position to the
right of a in the first row, say c, and then c' must go below a in the first
position in third row. Thus, we have the following sequence of partial squares:
Finally, it can be seen by playing the Conway game that the rest of the entries are forced and in the
correct positions for a Type D2 Conway square. Hence, there are (16)(6)(4) =
384 Type D2 Conway squares. ||
Sketch of
Proof of Theorem 2.8: Type D3 Conway squares.
We begin by placing an arbitrary Conway item a in the upper left hand corner for which we have 16
possible choices, then a' must go in the third position below a on the left
main diagonal. Next, since we must have the same similarity class occupying the
left main diagonal, we have 6 choices remaining for the first position below a
on this diagonal, say b, and then b' must go next below b on this diagonal.
Now, we have 4 choices remaining for the last position to the right of a in the
first row, say c, and then c' must go below a in the first position in fourth
row. Thus, we have the following sequence of partial squares:
Finally, it can be seen by playing the Conway game that the rest of the entries are forced and in the correct
positions for a Type D3 Conway square. Hence, there are (16)(6)(4) = 384 Type
D3 Conway Squares. ||
Exercise
2.9. If you haven't done so already, play
the Conway game while reading each proof sketch above, mirroring all the steps
in a specific case for each of the three Diagonal Types. As a result, you will
have constructed a Conway square of each of the three Diagonal Types. Try this
yourself before viewing these examples: Type D1 Example, Type D2 Example, Type D3 Example
Exercise
2.10. By viewing Illustrations 2.6, 2.7,
and 2.8, convince yourself that each of the eight symmetries of the square do
indeed preserve each of the Diagonal Types. And so, as stated in Corollary 2.9,
ignoring these symmetries there really are only 48 = 384/8 essentially
different Conway squares of each of the three Diagonal Types.
Remark
2.10. Note that if we wished, we could
enumerate all the Diagonal Type Conway squares simply by playing the Conway game as in the proof of Theorem 2.8, enumerating all of
them by hand and verifying that each one is a Conway square. However, in Section 3 of this paper we will show
how to do this in a more mathematical way, instead of using brute force.
Definition
2.11. (Row Types) We will now
define three different row types of Conway squares that were previewed in Exercises 1.3 in Section 1
and Exercise 2.3 in this section. For this definition we will let a, b, c, d,
and complements a', b', c', d', range over the eight Conway items in one (unspecified) similarity class, and we will
let w, x, y, z, and complements w', x', y', z', range over the Conway items in the other similarity class.
1. A Type
R1 Conway square is a Conway square with all the items of one similarity class
occurring together in the first two rows, all the items of the other similarity
class occurring together in the last two rows, and organized in the following
patterns:
Illustration 2.9
Note that for ease of viewing, we have partitioned
the pattern for a Type R1 Conway square (the one on the left of the equality in
Illustration 2.9) into two partial squares, each depicting the location of one
of the two similarity classes. We use a plus sign to indicate schematically how
the two patterns are joined together.
Also, the name 'R1' corresponds to constructing a Conway square by placing an item a in the upper left hand corner
of the square and then placing its complement, a', one position to the right of
it in the first row. It turns out that beginning in this way and completing to
a Conway square forces the resulting square to be of Type R1.
2. A Type
R2 Conway square is a Conway square with all the items of one similarity class
occurring together in the first and third rows, all the objects of the other
similarity class occurring together in the second and fourth rows, and
organized as follows:
Illustration 2.10
Note that for ease of viewing, we have partitioned
the pattern for a Type R2 Conway square (the one on the left of the equality in
Illustration 2.10) into two partial squares, each depicting the location of one
of the two similarity classes. We use a plus sign to indicate schematically how
the two patterns are joined together.
Also, the name 'R2' corresponds to constructing a Conway square by placing an item a in the upper left hand corner
of the square and then placing its complement, a', two positions to the right
of it in the first row. It turns out that beginning in this way and completing
to a Conway square forces the resulting square to be of Type R2.
3. A Type
R3 Conway square
is a Conway square with all the items of one similarity class
occurring together in the first and fourth rows, all the items of the other
similarity class occurring together in the second and third rows, and organized
in the following patterns:
Illustration 2.11
Note that for ease of viewing, we have partitioned
the pattern for a Type R3 Conway square (the one on the left of the equality in
Illustration 2.11) into two partial squares, each depicting the location of one
of the two similarity classes. We use a plus sign to indicate schematically how
the two patterns are joined together.
Also, the name 'R3' corresponds to constructing a Conway square by placing an item a in the upper left hand corner
of the square and then placing its complement, a', three positions to the right
of it in the first row. It turns out that beginning in this way and completing
to a Conway square forces the resulting square to be of Type R3.
Theorem
2.12. There are 384 Conway squares of each Row Type R1 and R2, and 768 Conway squares of Row Type R3, yielding a total of 1536 Row Type
Conway squares.
Corollary
2.13. Each Row Type Conway square is
preserved under the four symmetry transformations of the rectangle, i.e. a
rotation by 180 or 360 degrees, or a reflection in the horizontal or vertical
axis through the center. Hence, there are 96 essentially different
Conway squares of each Row Type R1 and R2, and 192 essentially different Conway Squares of Row Type R3, yielding a total of 384 essentially
different Row Type Conway Squares.
Sketch of
Proof of Theorem 2.12: Type R1 Conway squares.
Note that we will again use a Conway game construction to give a proof sketch as we did for
Theorem 2.8.
So, we begin by placing an arbitrary Conway item a in the upper left hand corner for which we have 16
possible choices, then a' must go in the first position to the right of a in
the first row. Next, since we must have the same similarity class occupying the
first two rows, we have 6 choices remaining for the next position in the first
row, say b, and then b' must go to the right of b in the first row. Now, we
have 4 choices remaining for the first position in the second row, say c, and
then c' must go next to c in the second row. Thus, we have the following
sequence of partial squares:
Finally, it can be seen by playing the Conway game that the rest of the entries are forced and in the
correct positions for a Type R1 Conway square. Hence, there are (16)(6)(4) =
384 Type R1 Conway squares. ||
Sketch of
Proof of Theorem 2.12: Type R2 Conway squares.
We begin by placing an arbitrary Conway item a in the upper left hand corner for which we have 16
possible choices, then a' must go in the second position to the right of a in
the first row. Next, since we must have the same similarity class occupying the
first two rows, we have 6 choices remaining for the position immediately to the
right of a in the first row, say b, and then b' must go in the last position in
the first row. Now, we have 4 choices remaining for the first position in the
third row, say c, and then c' must go in the second position to the right of c
in the third row. Thus, we have the following sequence of partial squares:
Finally, it can be seen by playing the Conway game that the rest of the entries are forced and in the
correct positions for a Type R2 Conway square. Hence, there are (16)(6)(4) =
384 Type R2 Conway squares. ||
Sketch of
Proof of Theorem 2.12: Type R3 Conway squares.
We begin by placing an arbitrary Conway item a in the upper left hand corner for which we have 16
possible choices, then a' must go in the third position to the right of a in
the first row. Next, since we must have the same similarity class occupying the
first two rows, we have 6 choices remaining for the position immediately to the
right of a in the first row, say b, and then b' must go immediately to the
right of b in the first row. Now, we have 4 choices remaining for the first
position in the fourth row, say c, and then c' must go in the last position in
the fourth row. Thus, we have the following sequence of partial squares:
In contrast to the other 5 types, it can be seen
by playing the Conway game, that an R3 square is not yet forced and this is due
to the fact that this is the only type in which the same similarity class (the
other one, not yet filled in above) occupies the middle two rows of the square.
Instead, it turns out that there are exactly two elements in this similarity
class, say w and y, such that both of the following extensions of the game
sequence above are possible, and from which each fourth partial square
displayed is forced to an R3 Type Conway square.
Hence, there are (16)(6)(4)(2) = 768 Type R3
Conway squares. ||
Exercise
2.11. If you haven't done so already, play
the Conway game while reading each part of the proof sketch of Theorem 2.12
above, mirroring all the steps in a specific case for each of the three Row
Types. As a result, you will have constructed a Conway square of each of the three Row Types. Try this yourself
before viewing these examples: Type R1 Example, Type R2 Example, Type R3 Example 1, Type R3 Example 2
Exercise
2.12. By viewing Illustrations 2.9, 2.10,
and 2.11, convince yourself that each of the four symmetries of the rectangle
do indeed preserve each of the Row Types. And so, as stated in Corollary 2.13,
ignoring these symmetries there really are only 96 = 384/4 essentially
different Conway squares of each type R1 and R2, and 192 = 768/4
essentially different Conway squares of type R3.
Remark
2.14. Note that if we wished, we could
enumerate all the Row Type Conway squares simply by playing the Conway game as in the proof of Theorem 2.12, enumerating all of
them by hand and verifying that each one is a Conway square. However, this would be quite tedious, so in
Section 3 we will show how to do this in a more mathematical way, instead of
using brute force. In addition, we will show that the six types (D1, D2,
D3, R1, R2, R3) introduced above exhaust the Conway squares, and hence there are exactly 528 = 144 + 384
essentially different Conway squares. Finally, we mention that in [Berlekamp, Conway,
and Guy 1982] different types of magic squares are described. However, though
we used those types as a starting point, we found them to be too coarse.
Instead, we developed our Diagonal Types and Row Types based on similarity
classes, in order to create more refined types needed for a more precise
classification and easier counting.