Mutually orthogonal Latin squares

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In combinatorial mathematics, two Latin squares of the same size (order) are said to be orthogonal if when superimposed the ordered paired entries in the positions are all distinct. A set of Latin squares, all of the same order, all pairs of which are orthogonal is called a set of mutually orthogonal Latin squares. This concept of orthogonality in combinatorics is strongly related to the concept of blocking in statistics, which ensures that independent variables are truly independent with no hidden confounding correlations. "Orthogonal" is thus synonymous with "independent" in that knowing one variable's value gives no further information about another variable's likely value.

Contents

An outdated term for pair of orthogonal Latin squares is Graeco-Latin square, found in older literature.

Graeco-Latin squares

A Graeco-Latin square or Euler square or pair of orthogonal Latin squares of order n over two sets S and T (which may be the same), each consisting of n symbols, is an n×n arrangement of cells, each cell containing an ordered pair (s, t), where s is in S and t is in T, such that every row and every column contains each element of S and each element of T exactly once, and that no two cells contain the same ordered pair.

The arrangement of the s-coordinates by themselves (which may be thought of as Latin characters) and of the t-coordinates (the Greek characters) each forms a Latin square. A Graeco-Latin square can therefore be decomposed into two orthogonal Latin squares. Orthogonality here means that every pair (s, t) from the Cartesian product S×T occurs exactly once.

Orthogonal Latin squares were studied in detail by Leonhard Euler, who took the two sets to be S = {A, B, C, ...}, the first n upper-case letters from the Latin alphabet, and T =  , β, γ, ...}, the first n lower-case letters from the Greek alphabet hence the name Graeco-Latin square.

Existence

When a Graeco-Latin square is viewed as a pair of orthogonal Latin squares, each of the Latin squares is said to have an orthogonal mate. In an arbitrary Latin square, a selection of positions, one in each row and one in each column whose entries are all distinct is called a transversal of that square. [1] Consider one symbol in a Graeco-Latin square. The positions containing this symbol must all be in different rows and columns, and furthermore the other symbol in these positions must all be distinct. Hence, when viewed as a pair of Latin squares, the positions containing one symbol in the first square correspond to a transversal in the second square (and vice versa).

A given Latin square of order n possesses an orthogonal mate if and only if it has n disjoint transversals. [2]

The Cayley table (without borders) of any group of odd order forms a Latin square which possesses an orthogonal mate. [2]

Thus Graeco-Latin squares exist for all odd orders as there are groups that exist of these orders. Such Graeco-Latin squares are said to be group based.

Euler was able to construct Graeco-Latin squares of orders that are multiples of four, [2] and seemed to be aware of the following result.

No group based Graeco-Latin squares can exist if the order is an odd multiple of two (that is, equal to 4k + 2 for some positive integer k). [3]

History

Although recognized for his original mathematical treatment of the subject, orthogonal Latin squares predate Euler. In the form of an old puzzle involving playing cards, [4] the construction of a 4 x 4 set was published by Jacques Ozanam in 1725. [5] The problem was to take all aces, kings, queens and jacks from a standard deck of cards, and arrange them in a 4 x 4 grid such that each row and each column contained all four suits as well as one of each face value. This problem has several solutions.

A common variant of this problem was to arrange the 16 cards so that, in addition to the row and column constraints, each diagonal contains all four face values and all four suits as well.

According to Martin Gardner, who featured this variant of the problem in his November 1959 Mathematical Games column, [6] the number of distinct solutions was incorrectly stated to be 72 by Rouse Ball. This mistake persisted for many years until the correct value of 144 was found by Kathleen Ollerenshaw. Each of the 144 solutions has eight reflections and rotations, giving 1152 solutions in total. The 144×8 solutions can be categorized into the following two equivalence classes:

SolutionNormal form
Solution #1A♠K♥Q♦J♣
Q♣J♦A♥K♠
J♥Q♠K♣A♦
K♦A♣J♠Q♥
Solution #2A♠K♥Q♦J♣
J♦Q♣K♠A♥
K♣A♦J♥Q♠
Q♥J♠A♣K♦

For each of the two solutions, 24×24 = 576 solutions can be derived by permuting the four suits and the four face values, independently. No permutation will convert the two solutions into each other, because suits and face values are different.

Thirty-six officers problem

Generalisation of the 36 officers puzzle for 1 to 8 ranks (chess pieces) and regiments (colours) - cases 2 and 6 have no solutions 36 officers problem.svg
Generalisation of the 36 officers puzzle for 1 to 8 ranks (chess pieces) and regiments (colours) cases 2 and 6 have no solutions

A problem similar to the card problem above was circulating in St. Petersburg in the late 1700s and, according to folklore, Catherine the Great asked Euler to solve it, since he was residing at her court at the time. [7] This problem is known as the thirty-six officers problem, [8] and Euler introduced it as follows: [9] [10]

A very curious question, which has exercised for some time the ingenuity of many people, has involved me in the following studies, which seem to open a new field of analysis, in particular the study of combinations. The question revolves around arranging 36 officers to be drawn from 6 different regiments so that they are ranged in a square so that in each line (both horizontal and vertical) there are 6 officers of different ranks and different regiments.

Leonhard Euler

Euler's conjecture and disproof

Redrawing of the November 1959 Scientific American order-10 Graeco-Latin square - in the SVG file, hover over the letters to hide the background and vice versa Scientific American November 1959 Graeco Latin square.svg
Redrawing of the November 1959 Scientific American order-10 Graeco-Latin square in the SVG file, hover over the letters to hide the background and vice versa

Euler was unable to solve the problem, but in this work he demonstrated methods for constructing Graeco-Latin squares where n is odd or a multiple of 4. Observing that no order two square exists and being unable to construct an order six square, he conjectured that none exist for any oddly even number n ≡ 2 (mod 4). The non-existence of order six squares was confirmed in 1901 by Gaston Tarry through a proof by exhaustion. [11] [12] However, Euler's conjecture resisted solution until the late 1950s, but the problem has led to important work in combinatorics. [13]

In 1959, R.C. Bose and S. S. Shrikhande constructed some counterexamples (dubbed the Euler spoilers) of order 22 using mathematical insights. [14] Then E. T. Parker found a counterexample of order 10 using a one-hour computer search on a UNIVAC 1206 Military Computer while working at the UNIVAC division of Remington Rand (this was one of the earliest combinatorics problems solved on a digital computer).

In April 1959, Parker, Bose, and Shrikhande presented their paper showing Euler's conjecture to be false for all n ≥ 7. [15] Thus, Graeco-Latin squares exist for all orders n > 1 except n = 2, 6. In the November 1959 edition of Scientific American, Martin Gardner published this result. [6] The front cover is the 10 × 10 refutation of Euler's conjecture.

Thirty-six entangled officers problem

A quantum solution to a classically impossible problem. If the chess pieces are quantum states in a superposition, then a pair of orthogonal quantum Latin squares of size 6 exists. The relative sizes of chess pieces denote the contribution of the corresponding quantum states. A pair of mutually orthogonal quantum Latin squares of size 6.png
A quantum solution to a classically impossible problem. If the chess pieces are quantum states in a superposition, then a pair of orthogonal quantum Latin squares of size 6 exists. The relative sizes of chess pieces denote the contribution of the corresponding quantum states.

Extensions of mutually orthogonal Latin squares to the quantum domain have been studied since 2017. [17] In these designs, instead of the uniqueness of symbols, the elements of an array are quantum states that must be orthogonal to each other in rows and columns. In 2021, an Indian-Polish team of physicists (Rather, Burchardt, Bruzda, Rajchel-Mieldzioć, Lakshminarayan, and Życzkowski) found an array of quantum states that provides an example of mutually orthogonal quantum Latin squares of size 6; or, equivalently, an arrangement of 36 officers that are entangled [16] [18] . [19] This setup solves a generalization of the 36 Euler's officers problem, as well as provides a new quantum error detection code, allowing to encode a 6-level system into a three 6-level system that certifies occurrence of one error.

Examples of mutually orthogonal Latin squares (MOLS)

A set of Latin squares of the same order such that every pair of squares are orthogonal (that is, form a Graeco-Latin square) is called a set of mutually orthogonal Latin squares (or pairwise orthogonal Latin squares) and usually abbreviated as MOLS or MOLS(n) when the order is made explicit.

For example, a set of MOLS(4) is given by: [20]

And a set of MOLS(5): [21]

While it is possible to represent MOLS in a "compound" matrix form similar to the Graeco-Latin squares, for instance,

1,1,1,12,2,2,23,3,3,34,4,4,45,5,5,5
2,3,5,43,4,1,54,5,2,15,1,3,21,2,4,3
3,5,4,24,1,5,35,2,1,41,3,2,52,4,3,1
4,2,3,55,3,4,11,4,5,22,5,1,33,1,2,4
5,4,2,31,5,3,42,1,4,53,2,5,14,3,1,2

for the MOLS(5) example above, it is more typical to compactly represent the MOLS as an orthogonal array (see below). [22]

In the examples of MOLS given so far, the same alphabet (symbol set) has been used for each square, but this is not necessary as the Graeco-Latin squares show. In fact, totally different symbol sets can be used for each square of the set of MOLS. For example,

Any two of text, foreground color, background color and typeface form a pair of orthogonal Latin squares:
fjordsjawboxphlegmqiviutzincky
zinckyfjordsjawboxphlegmqiviut
qiviutzinckyfjordsjawboxphlegm
phlegmqiviutzinckyfjordsjawbox
jawboxphlegmqiviutzinckyfjords

is a representation of the compounded MOLS(5) example above where the four MOLS have the following alphabets, respectively:

The above table therefore allows for testing five values in each of four different dimensions in only 25 observations instead of 625 (= 54) observations required in a full factorial design. Since the five words cover all 26 letters of the alphabet between them, the table allows for examining each letter of the alphabet in five different typefaces and color combinations.

The number of mutually orthogonal Latin squares

The mutual orthogonality property of a set of MOLS is unaffected by

Using these operations, any set of MOLS can be put into standard form, meaning that the first row of every square is identical and normally put in some natural order, and one square has its first column also in this order. [23] The MOLS(4) and MOLS(5) examples at the start of this section have been put in standard form.

By putting a set of MOLS(n) in standard form and examining the entries in the second row and first column of each square, it can be seen that no more than n 1 squares can exist. [24] A set of n 1 MOLS(n) is called a complete set of MOLS. Complete sets are known to exist when n is a prime number or power of a prime (see Finite field construction below). However, the number of MOLS that may exist for a given order n is not known for general n, and is an area of research in combinatorics.

Projective planes

A set of n − 1 MOLS(n) is equivalent to a finite affine plane of order n (see Nets below). [10] As every finite affine plane is uniquely extendable to a finite projective plane of the same order, this equivalence can also be expressed in terms of the existence of these projective planes. [25]

As mentioned above, complete sets of MOLS(n) exist if n is a prime or prime power, so projective planes of such orders exist. Finite projective planes with an order different from these, and thus complete sets of MOLS of such orders, are not known to exist. [10]

The only general result on the non-existence of finite projective planes is the BruckRyser theorem, which says that if a projective plane of order n exists and n ≡ 1 (mod 4) or n ≡ 2 (mod 4), then n must be the sum of two (integer) squares. [26] This rules out projective planes of orders 6 and 14 for instance, but does not guarantee the existence of a plane when n satisfies the condition. In particular, n = 10 satisfies the conditions, but no projective plane of order 10 exists, as was shown by a very long computer search, [27] which in turn implies that there do not exist nine MOLS of order 10.

No other existence results are known. As of 2020, the smallest order for which the existence of a complete set of MOLS is undetermined is 12. [10]

McNeish's theorem

The minimum number of MOLS(n) is known to be 2 for all n except for n = 2 or 6, where it is 1. However, more can be said, namely, [28]

MacNeish's Theorem: If is the factorization of the integer n into powers of distinct primes then

the minimum number of MOLS(n)

MacNeish's theorem does not give a very good lower bound, for instance if n ≡ 2 (mod 4), that is, there is a single 2 in the prime factorization, the theorem gives a lower bound of 1, which is beaten if n > 6. On the other hand, it does give the correct value when n is a power of a prime.

For general composite numbers, the number of MOLS is not known. The first few values starting with n = 2, 3, 4... are 1, 2, 3, 4, 1, 6, 7, 8, ... (sequence A001438 in the OEIS ).

The smallest case for which the exact number of MOLS(n) is not known is n = 10. From the Graeco-Latin square construction, there must be at least two and from the non-existence of a projective plane of order 10, there are fewer than nine. However, no set of three MOLS(10) has ever been found even though many researchers have attempted to discover such a set. [29]

For large enough n, the number of MOLS is greater than , thus for every k, there are only a finite number of n such that the number of MOLS is k. [30] Moreover, the minimum is 6 for all n > 90.

Finite field construction

A complete set of MOLS(q) exists whenever q is a prime or prime power. This follows from a construction that is based on a finite field GF(q), which only exist if q is a prime or prime power. [31] The multiplicative group of GF(q) is a cyclic group, and so, has a generator, λ, meaning that all the non-zero elements of the field can be expressed as distinct powers of λ. Name the q elements of GF(q) as follows:

α0 = 0, α1 = 1, α2 = λ, α3 = λ2, ..., αq-1 = λq-2.

Now, λq-1 = 1 and the product rule in terms of the α's is αiαj = αt, where t = i + j -1 (mod q -1). The Latin squares are constructed as follows, the (i, j)th entry in Latin square Lr (with r ≠ 0) is Lr(i,j) = αi + αrαj, where all the operations occur in GF(q). In the case that the field is a prime field (q = p a prime), where the field elements are represented in the usual way, as the integers modulo p, the naming convention above can be dropped and the construction rule can be simplified to Lr(i,j) = i + rj, where r ≠ 0 and i, j and r are elements of GF(p) and all operations are in GF(p). The MOLS(4) and MOLS(5) examples above arose from this construction, although with a change of alphabet.

Not all complete sets of MOLS arise from this construction. The projective plane that is associated with the complete set of MOLS obtained from this field construction is a special type, a Desarguesian projective plane. There exist non-Desarguesian projective planes and their corresponding complete sets of MOLS can not be obtained from finite fields. [32]

Orthogonal array

An orthogonal array, OA(k,n), of strength two and index one is an n2 × k array A (k ≥ 2 and n ≥ 1, integers) with entries from a set of size n such that within any two columns of A (strength), every ordered pair of symbols appears in exactly one row of A (index). [33]

An OA(s + 2, n) is equivalent to s MOLS(n). [33] For example, the MOLS(4) example given above and repeated here,

can be used to form an OA(5,4):

rcL1L2L3
11111
12222
13333
14444
21243
22134
23421
24312
31324
32413
33142
34231
41432
42341
43214
44123

where the entries in the columns labeled r and c denote the row and column of a position in a square and the rest of the row for fixed r and c values is filled with the entry in that position in each of the Latin squares. This process is reversible; given an OA(s,n) with s ≥ 3, choose any two columns to play the r and c roles and then fill out the Latin squares with the entries in the remaining columns.

More general orthogonal arrays represent generalizations of the concept of MOLS, such as mutually orthogonal Latin cubes.

Nets

A (geometric) (k,n)-net is a set of n2 elements called points and a set of kn subsets called lines or blocks each of size n with the property that two distinct lines intersect in at most one point. Moreover, the lines can be partitioned into k parallel classes (no two of its lines meet) each containing n lines. [34]

An (n + 1, n)-net is an affine plane of order n.

A set of k MOLS(n) is equivalent to a (k + 2, n)-net. [10]

To construct a (k + 2, n)-net from k MOLS(n), represent the MOLS as an orthogonal array, OA(k + 2, n) (see above). The ordered pairs of entries in each row of the orthogonal array in the columns labeled r and c, will be considered to be the coordinates of the n2 points of the net. Each other column (that is, Latin square) will be used to define the lines in a parallel class. The n lines determined by the column labeled Li will be denoted by lij. The points on lij will be those with coordinates corresponding to the rows where the entry in the Li column is j. There are two additional parallel classes, corresponding to the r and c columns. The lines rj and cj consist of the points whose first coordinates are j, or second coordinates are j respectively. This construction is reversible. [35]

For example, the OA(5,4) in the above section can be used to construct a (5,4)-net (an affine plane of order 4). The points on each line are given by (each row below is a parallel class of lines):

l11:(1,1) (2,2) (3,3) (4,4)l12:(1,2) (2,1) (3,4) (4,3)l13:(1,3) (2,4) (3,1) (4,2)l14:(1,4) (2,3) (3,2) (4,1)
l21:(1,1) (2,4) (3,2) (4,3)l22:(1,2) (2,3) (3,1) (4,4)l23:(1,3) (2,2) (3,4) (4,1)l24:(1,4) (2,1) (3,3) (4,2)
l31:(1,1) (2,3) (3,4) (4,2)l32:(1,2) (2,4) (3,3) (4,1)l33:(1,3) (2,1) (3,2) (4,4)l34:(1,4) (2,2) (3,1) (4,3)
r1:(1,1) (1,2) (1,3) (1,4)r2:(2,1) (2,2) (2,3) (2,4)r3:(3,1) (3,2) (3,3) (3,4)r4:(4,1) (4,2) (4,3) (4,4)
c1:(1,1) (2,1) (3,1) (4,1)c2:(1,2) (2,2) (3,2) (4,2)c3:(1,3) (2,3) (3,3) (4,3)c4:(1,4) (2,4) (3,4) (4,4)

Transversal designs

A transversal design with k groups of size n and index λ, denoted T[k, λ; n], is a triple (X, G, B) where: [36]

The existence of a T[k,1;n] design is equivalent to the existence of k-2 MOLS(n). [37]

A transversal design T[k,1;n] is the dual incidence structure of an (k,n)-net. That is, it has nk points and n2 blocks. Each point is in n blocks; each block contains k points. The points fall into k equivalence classes (groups) of size n so that two points in the same group are not contained in a block while two points in different groups belong to exactly one block. [38]

For example, using the (5,4)-net of the previous section we can construct a T[5,1;4] transversal design. The block associated with the point (i, j) of the net will be denoted bij. The points of the design will be obtained from the following scheme: rii, cj ↔ 5j, and lij ↔ 5i + j. The points of the design are thus denoted by the integers 1, ..., 20. The blocks of the design are:

b11:6 11 16 1 5b22:6 13 19 2 10b33:6 14 17 3 15b44:6 12 18 4 20
b12:7 12 17 1 10b21:7 14 18 2 5b34:7 13 16 3 20b43:7 11 19 4 15
b13:8 13 18 1 15b24:8 11 17 2 20b31:8 12 19 3 5b42:8 14 16 4 10
b14:9 14 19 1 20b23:9 12 16 2 15b32:9 11 18 3 10b41:9 13 17 4 5

The five "groups" are:

6 7 8 9
11 12 13 14
16 17 18 19
1 2 3 4
5 10 15 20

Graph theory

A set of k MOLS(n) is equivalent to an edge-partition of the complete (k + 2)-partite graph Kn,...,n into complete subgraphs of order k + 2. [10]

Applications

Mutually orthogonal Latin squares have a great variety of applications. They are used as a starting point for constructions in the statistical design of experiments, tournament scheduling, and error correcting and detecting codes. Euler's interest in Graeco-Latin squares arose from his desire to construct magic squares. The French writer Georges Perec structured his 1978 novel Life: A User's Manual around a 10×10 Graeco-Latin square.

See also

Notes

  1. This has gone under several names in the literature, formule directrix (Euler), directrix, 1-permutation, and diagonal amongst others. ( Dénes & Keedwell 1974 , p. 29)
  2. 1 2 3 Dénes & Keedwell 1974 , p. 155
  3. Dénes & Keedwell 1974 , p. 156
  4. Knuth, Donald (2011), The Art of Computer Programming, vol. 4A: Combinatorial Algorithms Part 1, Addison-Wesley, pp. xv+883pp, ISBN   978-0-201-03804-0 . Errata:
  5. Ozanam, Jacques (1725), Recreation mathematiques et physiques, vol. IV, p. 434, the solution is in Fig. 35
  6. 1 2 Gardner 1966 , pp. 162-172
  7. van Lint & Wilson 1993 , p.251
  8. P. A. MacMahon (1902). "Magic Squares and Other Problems on a Chess Board". Proceedings of the Royal Institution of Great Britain. XVII: 50–63.
  9. Euler: Recherches sur une nouvelle espece de quarres magiques, written in 1779, published in 1782
  10. 1 2 3 4 5 6 Colbourn & Dinitz 2007 , p. 162
  11. Tarry, Gaston (1900). "Le Probléme de 36 Officiers". Compte Rendu de l'Association Française pour l'Avancement des Sciences. Secrétariat de l'Association. 1: 122–123.
  12. Tarry, Gaston (1901). "Le Probléme de 36 Officiers". Compte Rendu de l'Association Française pour l'Avancement des Sciences. Secrétariat de l'Association. 2: 170–203.
  13. van Lint & Wilson 1993 , p.267
  14. Bose, R. C.; Shrikhande, S. S. (1959), "On the falsity of Euler's conjecture about the non-existence of two orthogonal Latin squares of order 4t + 2", Proceedings of the National Academy of Sciences USA, 45 (5): 734–737, Bibcode:1959PNAS...45..734B, doi: 10.1073/pnas.45.5.734 , PMC   222625 , PMID   16590435
  15. Bose, R. C.; Shrikhande, S. S.; Parker, E. T. (1960), "Further results on the construction of mutually orthogonal Latin squares and the falsity of Euler's conjecture", Canadian Journal of Mathematics, 12: 189–203, doi: 10.4153/CJM-1960-016-5 , MR   0122729
  16. 1 2 Rather, Suhail Ahmad; Burchardt, Adam; Bruzda, Wojciech; Rajchel-Mieldzioć, Grzegorz; Lakshminarayan, Arul; Życzkowski, Karol (2022), "Thirty-six entangled officers of Euler: Quantum solution to a classically impossible problem", Physical Review Letters, 128 (8): 080507, arXiv: 2104.05122 , Bibcode:2022PhRvL.128h0507R, doi:10.1103/PhysRevLett.128.080507, PMID   35275648, S2CID   236950798
  17. Goyeneche, Dardo; Raissi, Zahra; Di Martino, Sara; Życzkowski, Karol (2018), "Entanglement and quantum combinatorial designs", Physical Review A, 97 (6): 062326, arXiv: 1708.05946 , Bibcode:2018PhRvA..97f2326G, doi:10.1103/PhysRevA.97.062326, S2CID   51532085
  18. Garisto, Dan (2022), "Euler's 243-Year-Old 'Impossible' Puzzle Gets a Quantum Solution", Quanta Magazine
  19. Pappas, Stephanie (2022), "Centuries-old 'impossible' math problem cracked using the strange physics of Schrödinger's cat", LiveScience
  20. Colbourn & Dinitz 2007 , p. 160
  21. Colbourn & Dinitz 2007 , p. 163
  22. McKay, Meynert & Myrvold 2007 , p. 98
  23. Dénes & Keedwell 1974 , p. 159
  24. Dénes & Keedwell 1974 , p. 158
  25. The term "order" used here for MOLSs, affine planes and projective planes is defined differently in each setting, but these definitions are coordinated so that the numerical value is the same.
  26. Bruck, R.H.; Ryser, H.J. (1949), "The nonexistence of certain finite projective planes", Canadian Journal of Mathematics, 1: 88–93, doi: 10.4153/cjm-1949-009-2 , S2CID   123440808
  27. Lam, C. W. H. (1991), "The Search for a Finite Projective Plane of Order 10", American Mathematical Monthly , 98 (4): 305–318, doi:10.2307/2323798, JSTOR   2323798
  28. Dénes & Keedwell 1974 , p. 390
  29. McKay, Meynert & Myrvold 2007 , p. 102
  30. Lenz, H.; Jungnickel, D.; Beth, Thomas (November 1999). Design Theory by Thomas Beth. Cambridge Core. doi:10.1017/cbo9781139507660. ISBN   9780521772310 . Retrieved 2019-07-06.
  31. Dénes & Keedwell 1974 , p. 167
  32. Dénes & Keedwell 1974 , p. 169
  33. 1 2 Stinson 2004 , p. 140
  34. Colbourn & Dinitz 2007 , p. 161
  35. Dénes & Keedwell 1974 , p. 270
  36. Street & Street 1987 , p. 133
  37. Street & Street 1987 , p. 135
  38. van Lint & Wilson 1993 , p.257

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In linear algebra, a square matrix  is called diagonalizable or non-defective if it is similar to a diagonal matrix. That is, if there exists an invertible matrix  and a diagonal matrix such that . This is equivalent to . This property exists for any linear map: for a finite-dimensional vector space , a linear map  is called diagonalizable if there exists an ordered basis of  consisting of eigenvectors of . These definitions are equivalent: if  has a matrix representation as above, then the column vectors of  form a basis consisting of eigenvectors of , and the diagonal entries of  are the corresponding eigenvalues of ; with respect to this eigenvector basis,  is represented by .

<span class="mw-page-title-main">Hadamard matrix</span> Mathematics concept

In mathematics, a Hadamard matrix, named after the French mathematician Jacques Hadamard, is a square matrix whose entries are either +1 or −1 and whose rows are mutually orthogonal. In geometric terms, this means that each pair of rows in a Hadamard matrix represents two perpendicular vectors, while in combinatorial terms, it means that each pair of rows has matching entries in exactly half of their columns and mismatched entries in the remaining columns. It is a consequence of this definition that the corresponding properties hold for columns as well as rows.

<span class="mw-page-title-main">Euler's rotation theorem</span> Movement with a fixed point is rotation

In geometry, Euler's rotation theorem states that, in three-dimensional space, any displacement of a rigid body such that a point on the rigid body remains fixed, is equivalent to a single rotation about some axis that runs through the fixed point. It also means that the composition of two rotations is also a rotation. Therefore the set of rotations has a group structure, known as a rotation group.

In mathematics, the kernel of a linear map, also known as the null space or nullspace, is the linear subspace of the domain of the map which is mapped to the zero vector. That is, given a linear map L : VW between two vector spaces V and W, the kernel of L is the vector space of all elements v of V such that L(v) = 0, where 0 denotes the zero vector in W, or more symbolically:

<span class="mw-page-title-main">Raj Chandra Bose</span>

Raj Chandra Bose (or Basu) (19 June 1901 – 31 October 1987) was an Indian American mathematician and statistician best known for his work in design theory, finite geometry and the theory of error-correcting codes in which the class of BCH codes is partly named after him. He also invented the notions of partial geometry, association scheme, and strongly regular graph and started a systematic study of difference sets to construct symmetric block designs. He was notable for his work along with S. S. Shrikhande and E. T. Parker in their disproof of the famous conjecture made by Leonhard Euler dated 1782 that for no n do there exist two mutually orthogonal Latin squares of order 4n + 2.

In combinatorial mathematics, a block design is an incidence structure consisting of a set together with a family of subsets known as blocks, chosen such that frequency of the elements satisfies certain conditions making the collection of blocks exhibit symmetry (balance). Block designs have applications in many areas, including experimental design, finite geometry, physical chemistry, software testing, cryptography, and algebraic geometry.

Combinatorial design theory is the part of combinatorial mathematics that deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. These concepts are not made precise so that a wide range of objects can be thought of as being under the same umbrella. At times this might involve the numerical sizes of set intersections as in block designs, while at other times it could involve the spatial arrangement of entries in an array as in sudoku grids.

Latin squares and quasigroups are equivalent mathematical objects, although the former has a combinatorial nature while the latter is more algebraic. The listing below will consider the examples of some very small orders, which is the side length of the square, or the number of elements in the equivalent quasigroup.

<span class="mw-page-title-main">Weighing matrix</span> Mathematical weight device

In mathematics, a weighing matrix of order and weight is a matrix with entries from the set such that:

In mathematics a regular Hadamard matrix is a Hadamard matrix whose row and column sums are all equal. While the order of a Hadamard matrix must be 1, 2, or a multiple of 4, regular Hadamard matrices carry the further restriction that the order be a square number. The excess, denoted E(H), of a Hadamard matrix H of order n is defined to be the sum of the entries of H. The excess satisfies the bound |E(H)| ≤ n3/2. A Hadamard matrix attains this bound if and only if it is regular.

In mathematics, an orthogonal array is a "table" (array) whose entries come from a fixed finite set of symbols, arranged in such a way that there is an integer t so that for every selection of t columns of the table, all ordered t-tuples of the symbols, formed by taking the entries in each row restricted to these columns, appear the same number of times. The number t is called the strength of the orthogonal array. Here are two examples:

<span class="mw-page-title-main">Matrix (mathematics)</span> Array of numbers

In mathematics, a matrix is a rectangular array or table of numbers, symbols, or expressions, arranged in rows and columns, which is used to represent a mathematical object or a property of such an object.

In combinatorial mathematics, a Latin rectangle is an r × n matrix, using n symbols, usually the numbers 1, 2, 3, ..., n or 0, 1, ..., n − 1 as its entries, with no number occurring more than once in any row or column.

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