Issue |
Wuhan Univ. J. Nat. Sci.
Volume 29, Number 1, February 2024
|
|
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Page(s) | 38 - 44 | |
DOI | https://doi.org/10.1051/wujns/2024291038 | |
Published online | 15 March 2024 |
Mathematics
CLC number: O236.2
Three New Classes of Subsystem Codes
1
School of Mathematics and Physics, Hubei Polytechnic University, Huangshi 435003, Hubei, China
2
College of Arts and Science, Hubei Normal University, Huangshi 435003, Hubei, China
Received:
18
May
2023
In this paper, we construct three classes of Clifford subsystem maximum distance separable (MDS) codes based on Reed-Solomon codes and extended generalized Reed-Solomon codes over finite fields for specific code lengths. Moreover, our Clifford subsystem MDS codes are new because their parameters differ from the previously known ones.
Key words: Clifford subsystem codes / Reed-Solomon codes / generator matrices
Cite this article: LI Hui, LIU Xiusheng, HU Peng. Three New Classes of Subsystem Codes[J]. Wuhan Univ J of Nat Sci, 2024, 29(1): 38-44.
Biography: LI Hui, female, Master, Lecturer, research direction: algebraic coding. E-mail: HPhblg@126.com
Fundation item: Supported by Research Funds of Hubei Province (D20144401 and Q20174503)
© Wuhan University 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
0 Introduction
Subsystem codes protect quantum information by encoding it in a tensor factor of a subspace of the physical state space. They generalize all major quantum error protection schemes, and therefore are exceptionally versatile.
The subsystem codes are constructions of quantum codes combining the features of decoherence-free subspaces, noiseless subsystems, and quantum error-correcting codes. These codes can potentially provide attractive features, including streamlined syndrome calculation and a diverse range of easily implementable fault-tolerant operations. An subsystem code is a KR-dimensional subspace
of
, which is decomposed into a tensor product
of a K-dimensional vector space
and an R-dimensional vector space
such that all errors of weight less than
can be detected by
. The vector spaces
and
are respectively referred to as the subsystem
and the co-subsystem
. We also use bracket notation
to write the parameters of an
subsystem code in more straightforward form. For some background on subsystem codes, see the next section.
Aly et al[1-4] gave various methods to derive subsystem codes from classical codes over binary and non-binary fields and presented subsystem codes' families. In Ref.[5], Leng and Ma provided two methods to construct good non-binary subsystem codes. The first one is derived from quantum codes applied to non-narrow-sense BCH codes. The second one is derived from the technique of defining sets of classical cyclic codes. Recently, Qian and Zhang [6,7] constructed two new classes of subsystem maximum distance separable (MDS) codes using two classes of classical cyclic codes.
Inspired by these works, in this paper, we construct three classes of Clifford subsystem MDS codes based on linear codes, which have parameters as follows:
(i) , where
, and
.
(ii) , where
,
.
(iii) , where
.
We conclude this introduction with a description of each section in this paper. Section 1 revisits the fundamentals and results of linear codes and subsystem codes. In Section 2 details, we construct three classes of Clifford subsystem MDS codes using Reed-Solomon codes and extended generalized Reed-Solomon codes over . In Section 3, we compare the Clifford subsystem codes and give a summary of this work.
1 Preliminaries
In this section, we first recall some basic concepts and results about linear codes and subsystem codes necessary for the development of this work. We refer to Refs.[1, 4, 8] for more details.
Throughout this paper, let be the finite field with
elements, where
is a prime number and
is an integer. For a positive integer
, let
denote the vector space of all
-tuples over
. A linear
code
over
is a
-dimensional subspace of
. The Hamming weight
of a codeword
is the number of nonzero components of
. The Hamming distance of two codewords
, is
. The minimum Hamming distance
of
is the smallest Hamming distance between any two distinct codewords
. An
code is an
linear code with the minimum Hamming distance
.
Let . Let
be the vectors of an orthonormal basis of
, where the labels
are elements of
. Then
has the following orthonormal basis
.
If is a set, then
denotes the cardinality of the set
. We use the notation
to denote concatenation of
.
The symplectic weight of is defined as
.
The trace-symplectic product of two vectors and
in
is defined as
where denotes the dot product and
represents the trace from
to the subfield
, i.e.,
. The trace-symplectic dual of a code
is defined as
.
Consider , the unitary linear operators
and
in
are defined by
and
, respectively, where
is a primitive
-th root of unity.
Let .
Then is called the error group on
.
The weight of an error in
is defined as the number of
which are not equal to identity, and it is denoted by
. We can also associate with
a vector
. We have
Every nontrivial normal subgroup in
defines a subsystem code
. Let
be the centralizer of
in
and
the center of
. As a subspace, the subsystem code
defined by
is precisely the same as the stabilizer code defined by
. By Ref.[9], Theorem 4,
can be decomposed as
where
and
Since information is stored exclusively on subsystem , our concern is limited to errors that affect
. An error
in
is detectable by subsystem
if and only if
is contained in the set
. The distance of the subsystem code
is defined as
If , then we define the distance of the subsystem code
to be
. A distance
subsystem code
with
,
is often denoted as
or
if
and
. We assert that
is the gauge group of
and
is its stabilizer. The gauge group acts trivially on
.
The following theorem, as presented in Ref.[1], demonstrates the relationship between subsystem codes and classical codes.
Theorem 1 Let be a classical additive subcode of
such that
and let
denote its subcode
. If
and
, then there exists a subsystem code
such that
(1) ;
(2) .
The minimum distance of the subsystem is given by
(1) if
;
(2) if
. Thus, the subsystem
can detect all errors in
of weight less than
, and correct all errors in
of weight
.
We call codes constructed using Theorem 1 as Clifford subsystem codes.
The subsequent lemma will play an essential role in constructing Clifford subsystem codes, as detailed in Ref. [2].
Theorem 2 Let be an
linear code such that subcode
is an
linear code and
. Then there exist
Clifford subsystem codes.
Theorem 3 (Singleton Bound for Clifford Subsystem Codes[10]) Let be a
Clifford subsystem code. Then
.
Definition 1[4] Let be a
Clifford subsystem code. If
attains Singleton bound for Clifford subsystem code, i.e.,
, it is termed a Clifford subsystem MDS code.
2 Constructions of Clifford Subsystem MDS Codes
In this section, we construct three classes of Clifford subsystem MDS codes employing cyclic codes and generalized Reed-Solomon codes over .
Throughout the following, we consistently assume that is a positive integer.
A linear code of length n over is cyclic if the code invariant under the automorphism
which
It is well-known that a cyclic code of length over
can be identified with an ideal in the residue ring
via the isomorphism
given by
. From that, the following fact is well-known and straightforward (see Ref.[8]).
Lemma 1 If is a cyclic code of length
over
, then there exists
such that
with
.
Let be an integer such that
, and let
be the smallest positive integer such that
. Then
is the
-cyclotomic coset module
containing
. Since
is coprime with
, the fundamental factors of
in
can be described by the
-cyclotomic cosets. Suppose that
be a primitive nth root of unity over some extension field of
, and let
be the minimal polynomial of
concerning
. Let
be a complete set of representatives of
-cyclotomic cosets. Then, the polynomial
factors uniquely into monic irreducible polynomial in
as
.
The defining set of the cyclic code is defined as
.
The defining set is a union of some
-cyclotomic co-sets and
.
Next, we recall some primary results of generalized Reed-Solomon codes (see Ref.[7]). Let be
distinct elements of
, and let
be
nonzero elements of
. For
between 1 and
, the generalized Reed-Solomon code
is defined by
where denote the vectors
, respectively.
2.1 Construction 1
Let and
. A Reed-Solomon code (RS code) is a cyclic code of length
generated by
denoted by , where
is a primitive element of
(see Ref.[11]).
Remark 1 It is easy to prove that . Thus, the defining set of
is given by
.
Lemma 2 Let be cyclic code with defining set
. Then the defining set of
is given by
. In particular,
.
Proof According to Ref.[6] (Exercise 239, Chapter 4), we have that . Thus,
Theorem 4 Let , and
. Then, there is a Clifford subsystem MDS code with parameters
.
Proof Let . Obviously, the defining set of
is given by
. By Remark 1, we have
}.
Since , we have
. Then, the first element in the defining set of
comes after the last element in
. Since
, we rewrite
as
. Then
. And
.
This means that is an MDS code with parameters
. It follows that
is an MDS code with parameters
.
By , we have
. Then, by Theorem 2, there exists a Clifford subsystem code
with parameters
.
Since , the Clifford subsystem code
with parameters
is MDS by Definition 1.
2.2 Construction 2
In this subsection, we construct a class of Clifford subsystem MDS codes by using generalized Reed-Solomon codes over .
Let , and let
be a nth root of unity, that is
and
for
. Take
and
with
; the generalized Reed-Solomon code
have the following generator matrix:
where .
The rows of the matrix under consideration will be denoted by
.
Thus for
. It is easy to check that
for
. We recall the following fact (see Ref.[12]).
Lemma 3 Let be a code generated by taking
consecutive rows of the matrix
. Then
is an MDS code with parameters
.
It is a routine to verify the following lemma.
Lemma 4 Let be the code with generator matrix
. Then
is a check matrix for
.
Theorem 5 Let . Then, there is a Clifford subsystem MDS code
with parameters
.
Proof For , let
The code generated by the matrix
is an MDS code with parameters
by Lemma 3. Taking
. Then, by Lemma 4,
is a generator of the matrix of code
with parameters
.
Let . Set
. Then, by
, the matrix
is a generator matrix for code
. Moreover, the code
is an MDS code with parameters
by Lemma 3. So, the code
is an MDS code with parameters
.
By Theorem 2, there exists a Clifford subsystem code with parameters
.
Since , the Clifford subsystem code
with parameters
is MDS by Definition 1.
2.3 Construction 3
In this subsection, we construct a class of Clifford subsystem MDS codes by utilizing the extended code of generalized Reed-Solomon codes over .
We note that the extended code of the generalized Reed-Solomon code given by
where stands for the coefficient of
. The following two results can be found in Ref.[7].
Lemma 5[13] The code is an MDS code with parameters
.
Lemma 6 [13] Let 1 be all-one word of length . If
, then the dual code of
is
.
Theorem 6 Let . Then, there is a Clifford subsystem MDS code with parameters
.
Proof Taking . Then,
is a generator matrix of the code
with parameters
.
Set . Then, by Lemma 6,
is a parity-check matrix of the code
.
Since ,
is a generator matrix for the code
with parameters
. It is easy to check that
is a linear code with parameters
.
Since ,
, which implies that
. Thus, by Theorem 2, there exists a Clifford subsystem code
with parameters
.
Since , the Clifford subsystem code
with parameters
is MDS by Definition 1.
3 Comparison and Conclusion
This paper presents three new families of Clifford subsystem MDS codes employing Reed-Solomon codes and extended Reed-Solomon codes over . Table 1 gives our general conclusions to compare those known results in Refs. [5-7]. The results show that the lengths of those known conclusions above Clifford subsystem codes studied in the pieces of literature are fixed or odd. However, the lengths of a class of Clifford subsystem codes derived from our construction are very flexible.
Clifford subsystem codes comparison
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All Tables
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