Abstract
In this study, we explore maximum distance separable (MDS) self-dual codes over Galois rings with and odd r. Using the building-up construction, we construct MDS self-dual codes of length four and eight over with ( and ), ( and ), ( and ), ( and ), ( and ), and ( and ). In the building-up construction, it is important to determine the existence of a square matrix U such that , which is called an antiorthogonal matrix. We prove that there is no antiorthogonal matrix over with and odd r.
MSC:
94B05
1. Introduction
In coding theory, the minimum distance is very important because it indicates the ability to perform error correction on the codes. Therefore, maximum distance separable (MDS) codes have attracted much attention. However, self-dual codes have also been investigated because they are closely related to other mathematical structures such as block designs, lattices, modular forms, and sphere packings (see [1] as an example). Codes that contain both structures, which are called MDS self-dual codes, have been investigated. MDS self-dual codes have been studied over finite fields (see [2] as an example) and over finite rings (see [3] as an example). They have also been studied for Galois rings . For the case, the codes were investigated in [4], and for with any r or with even r, the codes were studied in [5]. To the best of our knowledge, MDS self-dual codes have not yet been studied for the case with odd r, and this case is the focus of our study. Specifically, we constructed several MDS self-dual codes over .
There are several construction methods for self-dual codes. One of the methods is the building-up construction. The method was first described in [6] and then developed in many papers (see [7] as an example). We note that the method was considered for with and odd r in [8]. In this paper, we used the building-up construction method which was described in [9] to construct MDS self-dual codes. For this method, it is very important to determine the existence of a square matrix U such that , which is called an antiorthogonal matrix [10,11]. There has been a study aimed at dealing with this problem [12]. In this study, we performed additional research on this problem.
This paper is organized as follows. In Section 2, we present basic facts regarding Galois rings, linear codes over , MDS codes, self-dual codes, and building-up construction. In Section 3, we discuss MDS self-dual codes over with and odd r, and we give our computational results for those codes. Specifically, we construct MDS self-dual codes of length four and eight over with ( and ), ( and ), ( and ), ( and ), ( and ), and ( and ). In Section 4, we review previously reported results showing the existence of antiorthogonal matrices, and we prove that there is no antiorthogonal matrix over with and odd r. All of the computations in this paper were performed using the computer algebra system Magma [13].
2. Preliminaries
In this section, we present basic facts regarding Galois rings, linear codes over Galois rings , MDS codes, self-dual codes, and building-up construction. We start with Galois rings.
2.1. Galois Rings
In this subsection, we present some well-known facts about Galois rings (see [14] as an example). Let p be a fixed prime and m be a positive integer. First, we consider the following canonical projection
which is defined by
The map can be extended naturally to the following map
which is defined by
This extended is a ring homomorphism with kernel .
Let be a polynomial in . Then, is called basic irreducible if is irreducible. A Galois ring is constructed as
where is a monic basic irreducible polynomial in of degree r. The elements of are residue classes of the form
where . The ring homomorphism induces a ring homomorphism
which is defined by
A polynomial in is called a basic primitive polynomial if is a primitive polynomial. It is a well-known fact that there is a monic basic primitive polynomial of degree m over and in . Let be a monic basic primitive polynomial in of degree r. Consider the following element
Then, the order of is . Teichmüller representatives are defined as follows.
Then, every element can be uniquely represented by the form
where . Using this notation, we define the following map
by
The following facts are known.
- is a ring automorphism of .
- fixes every element of .
- is of order r and generates the cyclic Galois group of over .
2.2. Linear Codes over
A linear code C of length n over is a submodule of , and the elements in C are called codewords. The distance between two elements is the number of coordinates in which differ. The minimum distance of a code C is the smallest distance between distinct codewords. The weight of a codeword in C is the number of nonzero . The minimum weight of C is the smallest nonzero weight of any codeword in C. If C is a linear code, then the minimum distance and the minimum weight are the same.
A generator matrix for a linear code C over is permutation equivalent to the following one in the standard form [15,16]:
where the columns are grouped into square blocks of sizes . The rank of C, denoted by , is defined to be the number of nonzero rows of its generator matrix G in a standard form. Therefore . We call in G the free rank of a code C. If , then C is called a free code. We say C is an linear code, if the code length is n, the rank of C is k, and the minimum weight of C is d. In this paper, we assume that all codes are linear unless we state otherwise.
2.3. MDS Codes
It is known (see [17] as an example) that for a (linear or nonlinear) code C of length n over any finite alphabet A,
Codes meeting this bound are called MDS codes. Further, if C is a linear code over a ring, then
Codes meeting this bound are called maximum distance with respect to rank (MDR) codes [16,18]. The presence of MDR codes does not imply MDS codes. See the following example.
Example 1.
Let C be a linear code generated by over . Then, , , and . Therefore, C is an MDR code. Because , C is not an MDS code.
The following lemma states the necessary and sufficient condition for MDS codes.
Lemma 1.
A linear code C is MDS if and only if C is MDR and free.
Proof.
(⇒) If C is not free, then . Therefore, , so C should be free, and . Thus, C is MDR.
(⇐) Let . Then, . Because , we have . Therefore, C is MDS. □
The following theorem states that the weight distribution of MDS codes over of code length n is uniquely determined.
Theorem 1
([16] Theorem 5.10). Let C be an MDS code over of code length n and minimum weight d. For , denote by the number of words of weight w in C. Then,
2.4. Self-Dual Codes and Building-Up Construction
Next, we define the usual inner product: for ,
For a code C of length n over , let
be the dual code of C. If , we say that C is self-orthogonal, and if , then C is self-dual.
Many construction methods are employed for self-dual codes. Among them, the building-up construction method has been extensively used. In this study, we use the method for constructing MDS self-dual codes over Galois rings. In the following theorem, we state the method.
Theorem 2
([9]). Let R be a finite chain ring, let be a self-dual code over R of length n with , and let be a generator matrix for . Let be an integer and let X be an matrix over R such that . Let U be an matrix over R such that , and let 0 be an zero matrix. Then, the matrix
generates a self-dual code C of length over R.
2.5. MDS Self-Dual Codes
In this study, we are interested in MDS self-dual codes that are MDS and self-dual. MDS self-dual codes over were constructed using Reed–Solomon codes [4].
Theorem 3
([4]). Let , and . Then, there exists an MDS self-dual code over R with parameters , which is an extended RS code.
Kim and Lee investigated the existence of MDS self-dual codes of length n over , where with any r or with even r [5]. The computational results are summarized in Table 1. They constructed many MDS self-dual codes over .
Table 1.
Existence of MDS self-dual codes of length n over [5].
The following theorem is very important in the computation of the minimum distance of a linear code over .
Theorem 4
([16] Corollary 4.3). If C is a free code over , then , where and is the image of c under the projection of onto , extended coordinatewise from the projection of to its residue field .
3. MDS Self-Dual Codes over Galois Rings
In the previous section, we saw that MDS self-dual codes over were studied for , and with any r or with even r. However, to the best of our knowledge, MDS self-dual codes over for with odd r has not been extensively studied. In this section, we study these codes, and we start with the following theorem.
Theorem 5.
Let C be a free self-dual code of length n over for with odd r. Then, n should be a multiple of four.
Proof.
Let G be a generator matrix of C. Because C is free, we assume that
where I is the identity matrix and , i.e., U is a antiorthogonal matrix. From Table 2, should be even. Therefore, n should be a multiple of four. □
Table 2.
Existence of antiorthogonal matrix U over .
Corollary 1.
Let C be an MDS self-dual code of length n over for with odd r. Then, n should be a multiple of four.
Proof.
From Lemma 1, C is free. Therefore, the result follows from Theorem 5. □
We used the building-up construction in Theorem 2 to construct MDS self-dual codes over for various ps and ms of length four and eight, respectively. The computation results are summarized in Table 3. In the following example, we give a detailed explanation for constructing MDS self-dual codes over of length four and eight.
Table 3.
Existence of MDS self-dual codes of length n over .
Example 2.
Let be a self-dual code of length four over , where , with generator matrix
The minimum weight of is 3, so is an MDS self-dual code. Let
and
where . Then, and . From the building-up construction in Theorem 2, we have
where
Then, G generates a self-dual code C of length eight over . The projection of G to its residue field is as follows:
where in the residue field . Let be the code generated by over the residue field . The minimum weight of is 5, so the minimum weight of C is also 5 based on Theorem 4. Therefore, C is an MDS self-dual code.
The codes in Table 3 were constructed in the same way as in Example 2. In the following, we give , , U, and X for each code.
- : , , .
- : , , .
- : , , .
- : , , .
- : , , .
- : , , .
4. Antiorthogonal Matrices over Galois Rings
In the previous section, we described the use of the building-up construction method [9] to construct MDS self-dual codes. In the construction, it is very important to verify the existence of a square matrix U such that , which is called an antiorthogonal matrix [10,11]. There has been previous research on this problem [12]. In this section, we review this study and further investigate this problem.
4.1. Review of Previous Research
We start with the definition of an antiorthogonal matrix. Massey introduced antiorthogonal matrices over finite fields.
Definition 1
([10]). A square matrix U over a finite field is said to be antiorthogonal if .
He characterized self-dual codes using antiorthogonal matrices.
Theorem 6
([10]). Let C be a linear code over a finite field with a generator matrix , where I is the identity matrix. Then, C is self-dual if and only if P is antiorthogonal.
Using the antiorthogonal matrix, he constructed linear codes with complementary duals (LCD codes) [10]. Definition 1 and Theorem 6 can be stated for Galois rings instead of finite fields. Therefore, it is very important to verify the existence of antiorthogonal matrices over Galois rings . Han performed a study on the problem [12]. We review the research below.
Suppose that . Then, is a square. In other words, there is an element such that . Let , where I is the identity matrix for a fixed value . Then, U is an antiorthogonal matrix. Therefore, there exists an antiorthogonal matrix U over for all .
Suppose that . We consider two cases: r is even and r is odd. First, suppose that r is even. Then, is a square. From a similar argument to that above, there exists an antiorthogonal matrix U over for all . Second, suppose that r is odd. Then, is not a square but a two-square sum. If U is an antiorthogonal matrix, then . Therefore, and . So, a should be even. Because is a two-square sum, there exist such that . Let
Then, . This proves that there is a antiorthogonal matrix U. For , where , let
Then, . Therefore, we conclude that there exists an antiorthogonal matrix U over if and only if a is even.
Suppose that . If , then . Therefore, is a square. By a similar argument to that above, there exists an antiorthogonal matrix U over for all . Now, suppose that . If , then is neither a square nor a two-square sum, and it is proven that there exists an antiorthogonal matrix U over if and only if a is a multiple of four, i.e., [19]. Now suppose that . We consider two cases: r is even and r is odd. First, suppose that r is even. Then, is not a square but is a two-square sum [12]. From a similar argument to that above, there exists an antiorthogonal matrix U over if and only if a is even.
From the above, the remaining case is that , , and . We know that is not a square. Using a similar argument to that above, we know that if U is an antiorthogonal matrix, then a should be even. Because and there is a antiorthogonal matrix U over , there is an antiorthogonal matrix U over R for all . Therefore, our question is as follows. The first question is “Is a two-square sum?” The second question is “Is there an antiorthogonal matrix U over for ?”
4.2. Nonexistence of a Antiorthogonal Matrix U over , and Odd r
In this subsection, we prove that is not a two-square sum in with and odd r, and we then conclude that there is no antiorthogonal matrix U over with and odd r. We start with the following lemma.
Lemma 2
([12]). If is a two-square sum in , then is a two-square sum in for all .
Corollary 2.
If is not a two-square sum in , then is not a two-square sum in for all .
The following lemma is the core part of our results.
Lemma 3.
Let r be an odd positive integer. Then, is not a two-square sum in .
Proof.
Let be the Teichmüller representatives in in Section 2. Then, every element can be uniquely represented by the form for some . Suppose that is a two-square sum in and for some . Let for some . Then, . Therefore . We know that is not a square. Therefore, and . Thus, and for some .
From the above, we have
Then, . Therefore, , where is the automorphism of in Section 2. We have and . Therefore,
From Equations (53) and (54), we have . Therefore, is a root of the equation . We applied the map in Section 2 to and the equation . Then, we have in . Thus, ( in . Let . Then, is a root of in . Therefore, contains the splitting field of over . In other words, contains . This means that r should be even. This leads to a contradiction and the result follows. □
Now, we state the main results of this subsection.
Theorem 7.
Let r be an odd positive integer. Then, is not a two-square sum in for all .
Proof.
From Corollary 2 and Lemma 3, we have the result. □
Theorem 8.
Let r be an odd positive integer. Then, there is no antiorthogonal matrix over for all .
Proof.
Suppose that there is a antiorthogonal matrix U over . Let
Then, . This contradicts Theorem 7. Therefore, we have the result. □
In Table 2, we summarize the results so far for the existence of an antiorthogonal matrix U over . The only remaining problem is for , , , and . We state this as a research problem as follows.
Research Problem: Determine the existence or nonexistence of an matrix U such that in , where , , , and .
Funding
This research was funded by the 2019 Professor Education and Research Promotion Program of KoreaTech.
Acknowledgments
The author wishes to thank the reviewers for valuable remarks which helped to improve this article.
Conflicts of Interest
The author declares no conflict of interest.
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