Permutation Matrices, Their Discrete Derivatives and Extremal Properties
Richard A. Brualdi, Geir Dahl

TL;DR
This paper introduces the concept of discrete derivatives for permutation matrices, characterizes their possible values, and explores special classes like permutations with distinct derivatives and their connection to Costas arrays.
Contribution
It defines and characterizes the discrete derivatives of permutations and investigates their properties and applications, including relations to Costas arrays.
Findings
Characterization of possible derivatives of permutations
Identification of permutations with distinct derivatives
Connection between derivatives and Costas arrays
Abstract
For a permutation , and the corresponding permutation matrix, we introduce the notion of {\em discrete derivative}, obtained by taking differences of successive entries in . We characterize the possible derivatives of permutations, and consider questions for permutations with certain properties satisfied by the derivative. For instance, we consider permutations with distinct derivatives, and the relationship to so-called Costas arrays.
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Permutation Matrices, Their Discrete Derivatives and Extremal Properties
Richard A. Brualdi111Department of Mathematics, University of Wisconsin, Madison, WI 53706, USA. [email protected]
Geir Dahl222Department of Mathematics, University of Oslo, Norway. [email protected]. Corresponding author.
Abstract
For a permutation , and the corresponding permutation matrix, we introduce the notion of discrete derivative, obtained by taking differences of successive entries in . We characterize the possible derivatives of permutations, and consider questions for permutations with certain properties satisfied by the derivative. For instance, we consider permutations with distinct derivatives, and the relationship to so-called Costas arrays.
Dedicated to Volker Mehrmann with admiration and respect.
Key words. Permutation matrix, discrete derivative, Costas array.
AMS subject classifications. 05B20, 15B48.
1 Introduction
Let be a permutation of , a permutation of order . The permutation can be given in the equivalent form as an permutation matrix with 1’s in positions for and 0’s elsewhere. Let denote the set of all permutations of order , and let denote the corresponding set of permutation matrices. We define the *discrete derivative * of and to be the vector
[TABLE]
The integers are the first-order differences of . For we define the th order differences of to be integers for . Note that the th order differences for are sums of first-order differences:
[TABLE]
If , then the zeroth order differences are defined to be the entries of itself. We assemble all these differences in a triangle that we call the difference triangle of . To illustrate, if and , then
[TABLE]
We label the rows of the difference triangle of a permutation of order as so that they correspond to the order of the differences in the rows.
The difference triangle as defined above is different from what is usually called the difference table of a finite sequence that is constructed by taking successive differences of entries in rows. Rows 0 and 1 are the same but then they would differ. Thus, with as above, row 2 of the difference table is
[TABLE]
and differs from row 2 of the difference triangle as given in (2).
The notion of the derivative of a permutation captures the changes in consecutive entries of a permutation , and therefore contains information about e.g. the descents of a permutation. We refer to the book [1] on permutations and their descents. Permutation matrices and more general classes of -matrices are treated in [2].
A Costas permutation (or Costas array or Costas permutation matrix) ([5]) is a permutation of order such that for each , its th order differences in row of its difference triangle are distinct. Since is a permutation, its zeroth order differences are distinct; since has only one st difference, no restriction is placed on st order differences. If we think of a permutation matrix as a configuration of points in the Euclidean plane at the integral positions for , then for a Costas permutation, no two of the line segments determined by these points have both the same length and the same slope, and thus all the line segments they determine are distinct. In terms of its difference triangle, the integers in each row are distinct. We remark that a Golomb ruler of order is defined to be a sequence of distinct positive integers such that all of the entries in its difference triangle are distinct. Since we confine our attention to permutations of a Golumb ruler is possible only in the trivial cases of or . An example of a Costas permutation of order 4 is with difference triangle
[TABLE]
If a symmetry of the dihedral group is applied to a Costas permutation, the result is also a Costas permutation. Other structural properties of Costas permutations are given in [6]. In particular, the following holds:
Proposition 1.1**.**
(Proposition 4.2 in [6]). If , then in a Costas permutation matrix of order , there exists and such that also and where and , that is the line segment joining the points and has the same vertical displacement and opposite horizontal displacement as the line segment joining the points and .
Costas arrays are difficult to construct and are conjectured to exist for all ; one may consult [3] for up-to-date information on their existence. The smallest for which the existence of a Costas array is not known is . It thus seems natural to investigate permutations under less restrictive conditions. Accordingly, we define a permutation to be a -Costas permutation provided that for each , its th order differences are distinct. Thus an -Costas permutation is a Costas permutation. A 1-Costas permutation is a permutation whose discrete derivative consists of distinct integers. For more on Costas arrays, see [6, 7, 8, 9].
In this paper we investigate various properties of the discrete derivative of a permutation, some of which are motivated by the classical derivative of a function. We now summarize the contents of this paper. In Section 2, we develop some basic properties of the discrete derivative of a permutation. In Section 3 we define the local and global variations of a permutation and determine their extreme values with characterizations of equality. Some other extremal questions, and the notion of convexity, are treated in Section 4. Finally, in Section 5 we discuss some possible generalizations of the content of this paper.
2 The discrete derivative
The following observation is the analogue of the fact that a function is determined up to a constant by its derivative. Here, since we are dealing with permutations in , no constant is involved.
Proposition 2.1**.**
A permutation is uniquely determined by its discrete derivative, i.e., the function given by is injective.
Proof. First, it is clear that is uniquely determined by the extension of the discrete derivative, due to the expression
[TABLE]
Next, when is given, then any other with , must be obtained by a shifting of in the sense that for some integer . But this implies that ; otherwise some would not lie in the set . Thus .
Example 2.2**.**
If , then its corresponding permutation matrix is
[TABLE]
In terms of integral points in the plane as previously described, there are only two different line segments of the six determined by successive points. The discrete derivative of is .
By Proposition 2.1 a permutation is determined by the entries in row 1 of its difference triangle . The permutation is, of course, also determined by any of the entries of itself. There are other sets of entries of the difference triangle which determine its corresponding permutation. Consider the complete graph with vertices labeled . To each edge of with we give the weight , thereby obtaining a weighted complete graph .
Proposition 2.3**.**
Let . Then any weighted spanning tree of uniquely determines .
Proof. The weighted spanning tree has edges. Let be distinct vertices of with edges and where and . Then the weight of is and the weight of is . Since , the weight of the edge is also determined. Proceeding inductively like this, we see that the weights of all the edges of are determined, in particular the weights of the edges ; thus the first-order differences of , and thus itself (see Proposition 2.1), are determined.
Example 2.4**.**
Consider again and . The difference triangle is
[TABLE]
Consider the spanning weighted tree of of with (unweighted) edges whose weights are highlighted. Then is a path with an additional edge . A simple verification checks that the difference triangle is determined by the highlighted entries.
It is natural to ask which vectors in are discrete derivatives of permutations in .
Define, for an integral vector , the set
[TABLE]
Proposition 2.5**.**
Let be an integral vector. Then is the discrete derivative of some permutation in if and only if is a set of consecutive integers containing [math].
Proof. Assume for some . Then, by (3),
[TABLE]
for . So the numbers are
[TABLE]
Therefore consists of the numbers with subtracted from each, and this is a set of consecutive integers containing [math].
Conversely, let be a set of consecutive integers containing [math], so
[TABLE]
for some integer with . Let be the permutation
[TABLE]
Then , where the entry occurs in position . So the numbers () become
[TABLE]
and therefore , as desired.
For a permutation in , we call the set the sum-characteristic of . There are sets of consecutive integers containing 0, namely,
[TABLE]
and by Proposition 2.5 each of the sets in (5) is the sum-characteristic of a permutation in . The sum-characteristic of a permutation is uniquely determined by and thus is the sum-characteristic of permutations in . To see this, we observe that as in the proof of Proposition 2.5, the entries of the sum-characteristic are . Thus if two permutations have the same , then the entries are and hence their sum-characteristics are identical.
Let with discrete derivative . It follows from (1) that is a Costas permutation if and only if the integers in each of the sequences
[TABLE]
are distinct. Hence by Proposition 2.5, a Costas permutation of order exists if and only if there is a sequence of integers which, with 0, can be reordered to form a consecutive set of integers such that the integers in each of the sequences
[TABLE]
are distinct. Thus the existence of Costas permutations can be regarded as a problem within additive number theory.
Example 2.6**.**
Consider the permutation in Example 2.2, so and . Then, if , we get
[TABLE]
We now construct another permutation such that where . Let . Then , and, for instance, the permutation is such that .
We now consider some questions related to the signs and values of the discrete derivative of a permutation. It is easy to see that there is only one permutation having only positive discrete derivatives, namely the identity permutation corresponding to the identity matrix . Similarly, the anti-identity permutation corresponding to the backward identity matrix , where when and 0 otherwise (), is the only permutation with only negative derivatives. A permutation in is a Grassmannian permutation provided it has only one descent. Grassmannian permutations are the only permutations with only one negative entry in their discrete derivative. Henceforth we generally refer to a discrete derivative simply as a derivative.
We now consider permutations with only two distinct values in their discrete derivative. An example of a permutation all of whose whose derivative values are or is given in Example 2.2. Another similar example is where .
Let and be distinct integers. If for some there exists a permutation , such that , then we say that is a -pair. Let be a -pair. Then is also a -pair, and therefore we assume hereafter than . In fact, we may also assume because, the reverse of a permutation has the same derivative values as the original but with opposite signs.
Lemma 2.7**.**
Assume that and that is a -pair. Then and have opposite signs, and and are relatively prime.
Proof. The only permutation with all derivatives positive (and thus all equal to ), is the identity permutation, and the only permutation with all derivatives negative (and thus all equal to ), is the anti-identity permutation. So and have opposite signs. If , then each of differ from by a multiple of , an impossibility as is a permutation.
We next show that the conditions on and discussed above provide a characterization of -pairs.
Theorem 2.8**.**
Let and be relatively prime integers with . Then there exists an integer such that is a -pair corresponding to a permutation in .
Proof. We first treat the case when . Let . Then , so is a -pair corresponding to the permutation .
Next, let and let . Define for . Also let be (uniquely) defined by
[TABLE]
We show that is a permutation with the desired properties.
Assume that for some with . This implies that
[TABLE]
and therefore
[TABLE]
Since , we see that and hence . This proves that is a permutation.
Next we consider the derivatives of . For each we consider two possibilities:
Case : for some . Then .
Case : and for some . The facts that and is obtained by reducing the ’s modulo implies that
[TABLE]
Note that Case 2 will occur for some as . In fact,
[TABLE]
as because .
This shows that , and we conclude that is a -pair and is a realization of .
In terms of permutation matrices, the proof just given constructs an permutation matrix with that realizes a -pair . The construction is easy to describe: for put a 1 in position and, row by row, move columns to the right computing column indices modulo , that is, move cyclically from row to row. For we do the same, but start in position . The following example illustrates this construction.
Example 2.9**.**
Consider , . Here 5 and 13 are relatively prime, so is a -pair. Then . The construction just discussed then gives the permutation
[TABLE]
whose corresponding permutation matrix is
[TABLE]
The double horizontal lines indicate where the derivative changes from positive to negative. So
[TABLE]
Our construction is a simple generalization of the standard full-cycle permutation matrix ( equals 1) on which the definition of a circulant matrix rests.
The inverse of is given by
[TABLE]
and
[TABLE]
Thus realizes the -pair . Since the permutation matrix corresponding to is the transpose of the permutation matrix (7), these differences result by cyclically considering the columns of (7).
Example 2.10**.**
Let , . Then and the construction above gives the following -realization of the -pair :
[TABLE]
The permutation is and its discrete derivative is . We have that and .
Corollary 2.11**.**
Let and be relatively prime integers with , and let be the permutation constructed in the proof of Theorem 2.8. Let be the inverse of modulo , and let . Then is a -pair corresponding to the permutation .
3 Local and global variation of a permutation
In this section we define the local and global variation of permutations and investigate some of their properties.
Let be a permutation of . Then
- (a)
The local variation of is given by
[TABLE]
the maximum absolute value of the derivative values of .
- (b)
The global variation of is given by
[TABLE]
the -norm of the discrete derivative.
The following proposition is clear.
Proposition 3.1**.**
For a permutation ,
[TABLE]
with equality on the lower end if and only if and equality on the upper end if and only if and are adjacent in .
Now consider a 1-Costas permutation whose derivative values are thus distinct. Then the lower bound is not attainable if . Since there are differences and they can be positive or negative, then
[TABLE]
In fact, if is even, the smallest values that the derivative could have are and either or . Thus (8) holds when is even. Next, assume that is odd. If , then the values of the derivative are and hence . Thus implying that , a contradiction. Thus if is odd, , and (8) is verified. For example, with , is a 1-Costas permutation with and hence .
We show how to construct -Costas permutations attaining the lower bound (8) on the local variation. Let . If is even, say , we define by
[TABLE]
If is odd, say , we define by
[TABLE]
Thus, the derivative of is
[TABLE]
where the signs alternate. Let be the permutation matrix corresponding to . For instance, and , and
[TABLE]
Recall that is the backward identity matrix defined in the introduction. Observe that, for each permutation matrix
[TABLE]
An example of a 1-Costas permutation attaining the lower bound above is with derivative . More generally we have the following proposition. In connection with the proof, it can be useful to consider the examples below.
Theorem 3.2**.**
Let be a positive integer. Then there exists a -Costas permutation with , the smallest possible value. Such a minimizing permutation depends on the parity of and is given by:
* is even, say n=2k$$: corresponds to the permutation matrix*
[TABLE]
* is odd, and with even corresponds to the permutation matrix*
[TABLE]
* is odd, and with odd corresponds to the permutation matrix*
[TABLE]
Moreover, in each case, attains the minimum value of for -Costas permutations, and this minimum value is when is even, and when is odd.
Proof. (i) Assume that is even, say for some positive integer . Consider the matrix in (9). If is even, the derivative of is
[TABLE]
If is odd, the derivative of is
[TABLE]
Thus, in either case, is -Costas, and .
(ii) Next, assume is odd and for some even positive integer . Consider the matrix in (10). Then
[TABLE]
so the derivative of is
[TABLE]
Thus, is -Costas and .
(iii) Assume for some odd , and consider the matrix in (11). Then
[TABLE]
so the derivative of is
[TABLE]
Thus, is -Costas and .
Finally, we consider . When is even, the derivatives are
[TABLE]
so clearly the minimum value of is then attained among -Costas permutations. When is odd, the derivatives are
[TABLE]
which is the minimum value of among -Costas permutations as some derivative is at least in absolute value due to (8).
We now give three examples illustrating the three cases in Theorem 3.2.
Example 3.3**.**
Let , so . Then the matrix in (9) is
[TABLE]
where the rows of are in the reverse order of those of . The derivative is computed as , and .
Example 3.4**.**
Let , so . Then the matrix in (10) is
[TABLE]
The derivative is computed as , and .
Example 3.5**.**
Let , so . Then the matrix in (11) is
[TABLE]
The derivative is computed as , and .
We now determine the extreme values of the global variation for general permutations. Clearly, and this minimum is attained only for the identity and the anti-identity permutations. The problem of maximizing is more complex. Define
[TABLE]
It is convenient to treat the even and odd cases separately.
Let be even, say , and let be a permutation. We say that is mid-alternating if for all the consecutive entries of satisfy either (i) , , or (ii) , .
Example 3.6**.**
Let , so . The permutation is mid-alternating, and the corresponding permutation matrix is
[TABLE]
Of two 1’s in consecutive rows, one is to the left of the double-vertical line and one is to the right.
Theorem 3.7**.**
Let be even, and let . Then if and only if is mid-alternating and . Moreover, .
Proof. Let be a permutation. In the expression for we replace each by times the sign of this difference. This gives
[TABLE]
where (resp. ; ) are those such that is larger than both and (resp., smaller; in between), and .
Note that as and cannot both belong to . Similarly, . It therefore follows from (12) that an upper bound on is the sum of twice the largest integers in with the next largest integer , and subtracting twice the sum of the smallest integers in with the next smallest integer . In fact, here we replace some of the zeros in (12) corresponding to by the difference of th largest and the th smallest number in , where , so this difference is positive. Thus is bounded by where
[TABLE]
[TABLE]
Note, for clarity, that because of the factor of 2 in both and , each is the sum of integers taken from An elementary computation gives that
[TABLE]
and, as was arbitrary, we have shown that .
In order that , for a specific permutation , it follows from our bounding argument that , and therefore the signs of the derivatives must alternate (as consecutive entries cannot both be 2, or both be ). Moreover, each of () must be more that and each of () must be less than or equal to . In addition, since it is and that enter only once in the computation of , we must have where, if , then , then and so forth, while if , then , then , and so forth, that is, must be mid-alternating.
The permutation in Example 3.6 satisfies the conditions of Theorem 3.7, so .
We turn to the case when is odd, say , and let be a permutation. We say that is mid-alternating if for all the consecutive entries of satisfy either (i) , , or (ii) , .
The following result may be shown using the same type of arguments as in the proof of Theorem 3.7, so we therefore omit the proof.
Theorem 3.8**.**
Let be odd, and let . Then if and only if is mid-alternating and equals either or . Moreover, .
Example 3.9**.**
The permutation satisfies the conditions of Theorem 3.8, and . The corresponding permutation matrix is
[TABLE]
4 Other properties of the discrete derivative
We observe that , and this minimum is attained for the identity and anti-identity permutations. Now we determine .
Theorem 4.1**.**
[TABLE]
Proof. Define . We initially prove that .
Let , and define . Assume . Let be the permutation matrix corresponding to . Let be the row of the unique 1 in column . Then has at least one adjacent row, say it is row (the argument is similar if it is row , or both). Row has a unique 1, say in column . But then
[TABLE]
a contradiction.
Therefore and
[TABLE]
It remains to construct a permutation with .
If is even, say , let
[TABLE]
Then , so , as desired.
If is odd, say , let
[TABLE]
Then , so , as desired.
Let be the permutation matrix corresponding to the extreme permutation constructed in the proof of Theorem 4.1. Note that when is even
[TABLE]
Example 4.2**.**
The extreme permutation matrices and are given by
[TABLE]
Here . The permutation in Example 2.2 also attains . *
Next we discuss an analogue of convexity for the discrete derivative. We say that a permutation and its corresponding permutation matrix are convex provided its derivatives are increasing, i.e.,
[TABLE]
This is equivalent to
[TABLE]
For instance, both the identity matrix and the backward identity matrix are convex. A class of convex permutation matrices are obtained by a modification of the matrix defined before Proposition 3.2. Let be obtained from by a plane rotation of the matrix by a counter-clockwise rotation of degrees. For example,
[TABLE]
which corresponds to the permutation with derivative . Then we see that is a convex permutation matrix for every .
Let be a subpermutation matrix, i.e., a -matrix with at most one 1 in every row and column. If contains a total of 1’s, then corresponds to a subsequence of a permutation of . Define I_{k}(P)=\{i:p_{ij}=1\;\mbox{\rm for some j\leq k}\}, the set of rows containing a 1 in the first columns. An interval in a set is a set of consecutive integers for some , and its length is .
Lemma 4.3**.**
If is a convex permutation matrix of order , then is an interval of length for each .
Proof. Let be the permutation corresponding to . For the statement is clearly true. So, assume and that is not an interval. Then there are with and the submatrix consisting of the first columns of has a 1 in rows and , but not in row . This clearly implies that there must exist an such . So, the derivative is not increasing, and is not convex, a contradiction. Therefore, is an interval.
Note that the converse of the implication in Lemma 4.3 is not true; for instance, consider the permutation matrix
[TABLE]
Then is an interval of length for each , but is not convex.
Let be an subpermutation matrix. Let . We say that is -convex if (i) each of the first columns contains exactly one 1, (ii) is an interval, say equal to , and (iii) for where is the unique column in containing a 1 in row . Now, let be such a subpermutation matrix which is -convex and where columns are all zero. Define the following (possibly empty) set of cardinality at most 2:
(i) Let if , and the matrix obtained from by putting a 1 in position is -convex (this means that the derivative in row is less that the derivative in row );
(ii) Let if , and the matrix obtained from by putting a 1 in position is -convex (this means that the derivative in row is less that the derivative in row ).
It follows from Lemma 4.3 that if is a convex permutation matrix, then is also -convex for each . We use this property to construct convex permutation matrices of order by the following algorithm.
[TABLE]
Lemma 4.4**.**
If Algorithm does not terminate prematurely, i.e., Step a does not occur, then the resulting permutation matrix is convex. Any convex permutation matrix may be constructed by Algorithm .
Proof. We may assume . Consider Algorithm 1, and let . For , we get
[TABLE]
Thus, after the step for , the resulting matrix is -convex. It is not hard to see that the conditions on the set assure that, when this set is nonempty for each , the final matrix constructed will be a permutation matrix with increasing derivatives and therefore it is convex.
Next, let be a convex permutation matrix. We need to show that may be constructed by Algorithm 1 by suitable choice of the element in Step 3b in each iteration. Assume that Algorithm 1, after iterations, has constructed a matrix whose first columns coincide with those of (for this is clear). Thus, and are equal, say equal to . Moreover, as is also an interval, the unique 1 in column of must be in row or , so assume first it is in row . Since is convex, satisfies which means that , and therefore, in Algorithm 1, we can let column of have its 1 in row . A similar construction works when the 1 in column of is in row . Thus, in any case, the first columns of equal the corresponding columns of . So, by induction, we may obtain by suitable such choices in Algorithm 1.
Theorem 4.5**.**
The set of convex permutations of order consists of
* identity,*
* ,*
* ,*
* ,*
and the permutations obtained by reversing the order in each of these permutations.
Proof. We consider Algorithm 1, and construct a convex matrix and corresponding permutation . By symmetry, we may assume
[TABLE]
for some , and with maximal with this property. We discuss different cases.
Case : . Then and .
Case : . Then and .
Case : . Then it is easy to see that, by convexity, that the only possibility is . This gives the permutation .
Case : . Then (17) holds and . Then , otherwise and then and which contradicts convexity. By the algorithm, . This, however, by checking the derivatives (at the boundary of the interval), that as . Thus, there is no convex permutation matrix in this case.
Case : . Then by checking the possible derivatives at the boundary of the interval for each , one derives that and then , etc. The only possibility is then that and we obtain the matrix .
Example 4.6**.**
The convex permutation matrices of order are the following 4 matrices
[TABLE]
and
[TABLE]
and those additional 4 obtained by reordering rows in the opposite order. **
5 Coda
In this concluding section, we discuss 1-Costas permutations and some additional properties of permutations involving their derivatives.
For permutations one may consider properties similar to Lipschitz properties of functions defined on the real line. We say that a permutation , and the corresponding permutation matrix , is -Lipschitz if
[TABLE]
Since we only consider permutations, the only values of interest here are . It is easy to verify that (18) is equivalent to to the simplified condition that (), or, equivalently, . The only permutations that are -Lipschitz are the identity and the anti-identity permutations. An interesting question is to characterize permutations that are -Lipschitz, for a given . We believe this can at least be done for .
Checking if a given permutation of order has the -Costas property is easily done: compute all the derivatives, requiring arithmetic operations, and then sort these number ( operations suffice).
Every permutation matrix with the -Costas property may be constructed, starting with the zero matrix, by a simple algorithm which, however, may result in failure:
Place a 1 in some position in the first row. 2. 2.
for ,
- (a)
determine the permitted positions in row , i.e., those positions that are (i) not in a column already occupied by a 1, and (ii) not in any -line in rows with two 1’s, and (iii) not in any parallelogram in rows with three 1’s,
- (b)
choose, if possible, a permitted position in row and place a 1 there.
If the algorithm does not stop before ones have been placed, the resulting matrix is a permutation matrix satisfying the -Costas property.
Since the derivative of an -Lipschitz permutation of order can have at most values, an -Lipschitz permutations cannot have the -Costas property if is large enough.
The table in Figure 1 below gives the values of for . In the table, is the fraction of the permutation matrices that have the 1-Costas property. A table of the number of Costas permutations of order for can be found in [9].
Question 5.1**.**
Is a decreasing function of ? It is likely that .
A centrosymmetric permutation of order is a permutation such that for . The corresponding centrosymmetric permutation matrix is characterized by the property that it is invariant under a 180 degree rotation. The permutation in Example 2.2 is centrosymmetric and has a palindromic discrete derivative.
Example 5.2**.**
Let and with corresponding permutation matrix
[TABLE]
Then and are centrosymmetric. The difference triangle is
[TABLE]
Thus except for those repeats (highlighted) which follow from the centrosymmetric property, the difference triangle has no other repeats in its rows. Denoting as , the entries in the center of the difference triangle are .* *
We define a Costas-centrosymmetric permutation to be a centrosymmetric permutation whose difference table has no repeats other than those required by the centrosymmetric property. Note that the required repeats are of the form . Equivalently, we consider only the differences where . Example 5.2 is a Costas-centrosymmetric permutation.
The Costas permutation of order appears in [4]. Reversing the second half of this permutation gives the Costas-centrosymmetric permutation . In [4] its “anti-reflective symmetry” is noted.
If we take the Costa-centrosymmetric permutation of order 8 with difference triangle
[TABLE]
and reverse the last half to get , we do not get a Costas permutation since row 1 of its difference triangle already gives a repeat:
[TABLE]
This leads to the following question:
Question 5.3**.**
Let where is an even integer. Define a Costas half- permutation of order to be a sequence such that consists of one integer from each of the pairs for and each of the rows of its corresponding difference triangle does not have any repeats? Note that to construct a Costas half-permutation of order one has to choose an integer in each pair and then order them in some way.* *
Example 5.4**.**
Let . Then choosing one integer from each of the pairs , namely, , we get a Costas half-permutation:
[TABLE]
**
A more general question is:
Question 5.5**.**
Let and be positive integers with . Define a Costas -subpermutation of order to be a sequence of distinct integers taken from whose difference table does not contain a repeat in any row. For each positive integer , let be the largest integer such that there is a Costas -subpermutation of order . Thus with equality if and only if there exists a Costas permutation of order . Investigate this parameter . Find the best constant such that for all . Clearly, if there exists a Costas permutation of order , then for all , .* *
Rather than applying the Costas property to a sequence of integers taken from , one can attach signs to a permutation. Let be a signed permutation of order , that is, where is a permutation of . Then is a Costas-signed permutation provided the difference triangle of (note: not the difference triangle of ) does not have any repeats in its rows. Allowing negative signs makes it easier to satisfy the Costas property of no repeats in a row.
Example 5.6**.**
Let and . Then the difference triangle is
[TABLE]
so that this is a Costas-signed permutation of order .
- *
Question 5.7**.**
Does there exists a Costas-signed permutation of order for every positive integer ? For each integer , find a construction for a Costas-signed permutation of order .* *
Finally we note that higher dimensional Costas permutations have been investigated; see e.g. [8] and the references therein.
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