Deep Holes of Projective Reed-Solomon Codes
Jun Zhang, Daqing Wan, Krishna Kaipa

TL;DR
This paper explicitly constructs and classifies all deep holes in Projective Reed-Solomon codes with redundancy up to four, advancing understanding of their error structures using algebraic methods.
Contribution
It introduces three classes of deep holes for PRS codes and completely classifies all deep holes with redundancy at most four, extending prior classifications.
Findings
Three classes of deep holes explicitly constructed
Complete classification for PRS codes with redundancy ≤ 4
Advancement over previous work limited to redundancy ≤ 3
Abstract
Projective Reed-Solomon (PRS) codes are Reed-Solomon codes of the maximum possible length q+1. The classification of deep holes --received words with maximum possible error distance-- for PRS codes is an important and difficult problem. In this paper, we use algebraic methods to explicitly construct three classes of deep holes for PRS codes. We show that these three classes completely classify all deep holes of PRS codes with redundancy at most four. Previously, the deep hole classification was only known for PRS codes with redundancy at most three in work arXiv:1612.05447
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Taxonomy
TopicsCoding theory and cryptography · Quantum-Dot Cellular Automata · Educational Curriculum and Learning Methods
Deep Holes of Projective Reed-Solomon Codes††thanks:
The research of Jun Zhang was supported by the National Natural Science Foundation of China under Grant No. 11971321, and by Scientific Research Project of Beijing Municipal Education Commission under Grant No. KM201710028001. Jun Zhang is supported by Chinese Scholarship Council for his visit at the University of Oklahoma, USA. The research of Daqing Wan was supported by National Science Foundation. The research of Krishna Kaipa is supported by the Science and Engineering Research Board, Government of India, under Project EMR/2016/005578.
Jun Zhang Jun Zhang is with the School of Mathematical Sciences, Capital Normal University, Beijing 100048, China. Email: [email protected]
Daqing Wan Daqing Wan is with the Department of Mathematics, University of California, Irvine, CA 92697, USA. Email: [email protected]
Krishna Kaipa Krishna Kaipa is with the Department of Mathematics, Indian Institute of Science Education and Research, Pune, Maharashtra, 411008 India. Email: [email protected]
Abstract
Projective Reed-Solomon (PRS) codes are Reed-Solomon codes of the maximum possible length . The classification of deep holes –received words with maximum possible error distance– for PRS codes is an important and difficult problem. In this paper, we use algebraic methods to explicitly construct three classes of deep holes for PRS codes. We show that these three classes completely classify all deep holes of PRS codes with redundancy four. Previously, the deep hole classification was only known for PRS codes with redundancy at most three by the work [9].
I Introduction
Let denote the finite field of size and characteristic a prime number . Let denote the vector space of row-vectors or words . The Hamming metric on is the metric obtained by defining the distance between two words and to be the number of coordinates in which and differ:
[TABLE]
A linear code is a -dimensional linear subspace of with the induced metric. The minimum distance of is
[TABLE]
The error distance of any word to is defined to be
[TABLE]
The maximum error distance
[TABLE]
is called the covering radius of , and the words achieving maximum error distance are called deep holes of the code. The problem of determining the set of deep holes of a code, or of deciding whether a given word is a deep hole, are in general hard problems. These problems are also important from the perspective of the decoding problem for the code.
When is a Reed-Solomon code, the problem of determining the deep-holes of is an interesting and difficult combinatorial problem. This problem has received significant attention in recent literature, for example in the works [4] [5] and [9] [11] [12] [17] [18]. In this work, by a Reed-Solomon code we mean the following code:
Definition I.1**.**
Let be an ordered set of distinct elements of . The Reed-Solomon code of length , dimension and evaluation set is the code:
[TABLE]
Here is taken to be the coefficient of in , and the parameters and satisfy . Generalized Reed-Solomon (GRS) codes are obtained by applying a diagonal Hamming isometry to a Reed-Solomon code: in other words, any GRS code is of the form where is a Reed-Solomon code and is an invertible diagonal matrix over . Clearly, the set of deep holes of is \{xM\,|\,x\text{ is a deep hole of C}\}. Therefore, for the problem of determining the deep holes of GRS codes, it suffices to only treat Reed-Solomon codes.
When , the Reed-Solomon codes are called projective Reed-Solomon codes and will be simply denoted as . These codes are also known in literature as doubly-extended Reed-Solomon codes. While the covering radius of Reed-Solomon codes of length is known to be , the situation with PRS codes is different. For , the covering radius is again and the deep holes of are easily determined. For , the covering radius is and the deep holes of are known (see §II for these facts). But for , the covering radius of is only known conjecturally:
Conjecture I.2**.**
For , the covering radius of is:
[TABLE]
This conjecture is equivalent to a well-known conjecture in finite geometry (see Conjecture II.5 in §II-A). Conjecture I.2 has been shown to be true for several values of for example . This brings us to our main problem:
Problem I.3**.**
Determine the set of deep holes for those for which Conjecture I.2 is true.
For , the problem has an easy solution as given in [9] (see §II for details). For , the problem is difficult and wide open. In [17], the following classes of deep holes of were identified:
Theorem I.4** ( [17]).**
Let and suppose . Let be the ordered evaluation set for . The words
[TABLE]
are distinct deep hole classes of .
The term deep hole class is defined in the next section. The automorphism group of a linear code also acts on the set of its deep holes. Using this fact, we show in §II-C that the group acts on the set of deep hole classes of . The orbits under of the deep hole classes given in Theorem I.4 above, give us new classes of deep holes of . This is the first result of this paper:
Theorem I.5**.**
Let and suppose . The set of words
[TABLE]
represent distinct classes of deep holes of . These classes are distinct from the classes of Theorem I.4.
We also show that the deep hole classes of Theorems I.4 and I.5 taken together have a nice geometric interpretation in terms of the tangent lines to the degree normal rational curve in .
The second result of this paper is a new class of deep holes of :
Theorem I.6**.**
Let and suppose . The words as runs over the rational functions of the form with a monic irreducible polynomial of degree , and a nonzero monic polynomial of degree at most , represent distinct classes of deep holes of . These classes are distinct from the classes of Theorems I.4 and I.5.
We also show that this construction has a geometric interpretation in terms of the degree normal rational curve in over a quadratic field extension of .
The third result of this paper is the complete classification of deep holes of for :
Theorem I.7**.**
The total number of deep hole classes of is . These are given by the deep hole classes of Theorem I.4, classes of Theorem I.5, and classes of Theorem I.6.
The rest of this paper is organized as follows. In §II-D we prove Theorems I.5 and I.6. The necessary tools and background are covered in §II-C and and §II-A. We prove Theorem I.7 in §III. The purpose of §II-B is to highlight the fact that the assertion which sometimes appears in literature– that MDS codes of minimum distance have covering radius or – has no known correct proof. This section is independent of the rest of the paper.
II Projective Reed-Solomon codes and their Covering Radii
We begin with some notation for PRS codes. We use the term words for row vectors, and a vector (of for some ) will mean a column vector. For any integer and , we define vectors
[TABLE]
For , it is understood that for all . Let be a fixed ordering of , and let . The matrix defined as:
[TABLE]
is a generator matrix for : for a message word the codeword is the evaluation of the polynomial at the ordered set of points . We recall that for a polynomial of degree at most , the value of is taken to be the coefficient of in . Any minor of is a Vandermonde determinant and hence is nonzero (here we use the fact that ). It is well known that a linear code satisfies (the Singleton bound), and equality holds in this bound if and only if every minor of a generator matrix of is nonzero. Such a code is called a maximum-distance-separable code (MDS code). Therefore is always an MDS code. Using the following well-known identity about sum of powers of elements in :
[TABLE]
it follows that for , the product is the zero matrix. Thus is a parity check matrix for , or equivalently is the dual code to .
For a linear code code , and a received word , the word where and has the same error distance as . We recall that for a vector space , the projective space denotes the set of equivalence classes of in which two nonzero vectors are equivalent if and only if they generate the same one dimensional subspace of .
Definition II.1**.**
For a linear code code , we will say that received words are equivalent if for some and . In particular non-codewords are equivalent if and only if they represent the same element of the projective space . Here is the quotient vector space of cosets of in . The term deep hole class will refer to the class of a deep hole of in .
We recall the following well-known characterization of covering radius of a linear code in terms of a parity check matrix.
Lemma II.2**.**
Let be a linear code with parity check matrix . The error distance of a received word equals the least number such that the syndrome can be expressed as a linear combination of columns of . In particular, the covering radius is the least integer such that any vector in can be expressed as a linear combination of some columns of . The word is a deep hole of if and only if can not be written as a linear combination of any columns of .
Definition II.3**.**
Let be a linear code. The term projective syndrome of a non-codeword will refer to the element of represented by . The map induces a bijective correspondence
[TABLE]
from the set of equivalence classes of non-codewords to the set of projective syndromes .
We use the notation for the subset of consisting of the projective syndromes of deep hole classes of . We note that the Problem I.3 is equivalent to determining the subset . In the literature on deep holes of RS codes, deep holes are often described by generating polynomials. This can be adapted to PRS codes and is closely related to our description in terms of projective syndromes: Let denote the set of polynomials of degree at most which are monic and for which the coefficient of is zero. The number of such polynomials is . To each such polynomial, we associate the word . If , we claim and represent different equivalence classes: if for some and , then there is a polynomial of degree at most (representing the codeword ) such that has roots, but degree at most . This forces . We note that
[TABLE]
Since is the coefficient of in , it follows that deg. Combining this with the fact that the coefficients of in and are zero, forces . Since are monic we get and hence . The deep hole class of is said to be generated by the polynomial . The relation between the projective syndrome syn and the polynomial is very simple: if generates the word , then the projective syndrome syn. This easily follows from the formula syn together with the identity (3). For example the projective syndromes of the words of Theorem I.4 are:
[TABLE]
and the corresponding generating polynomials are .
II-A Covering radius of PRS codes
We first discuss the possible values of covering radius for PRS codes. As mentioned above, the matrix is a parity check matrix for the code . Since has full rank, it follows from Lemma II.2, that . Next, we show that for , and for . We also determine the set of deep holes in each case:
- •
For , we have and hence every word is a deep hole: this is because .
- •
For , we have , and hence every non-codeword is a deep hole: here , and because a linear code satisfies if and only if .
- •
For , we have , and hence every non-codeword is a deep hole: here any syndrome in is proportional to one of the columns of the parity check matrix , and hence .
- •
For , we have : here the codewords are and hence the maximum possible distance of a received word from the code is . The deep holes are those received words of length which have the maximum possible number (namely ) of distinct coordinates.
On the other hand, for it is also known that : for the word , it can be shown that . A quick proof is as follows. The distance of from a codeword represented by a polynomial of degree at most , is at least because the polynomial can have at most roots. On the other hand for where are distinct elements of which add up to [math] (this is always possible, see [7], [17]), the distance of from the codeword represented by is exactly . For , we have if there exists a vector which cannot be expressed as a linear combination of any columns of (by Lemma II.2). If no such vector exists, then and hence . As mentioned in the introduction, a linear code is MDS if and only if every minor of a generator matrix of the code is nonzero. Since this property holds for , we can rewrite the above characterization of in the following way (originally due to Dür (1994)):
Lemma II.4**.**
[6]** For , we have or according as whether or not there exists a vector such that the matrix generates an MDS code, i.e. whether or not there exists a MDS code extending by one coordinate.
In finite geometry an (ordered) -arc in projective space is an ordered set of points of represented by vectors with the property that the matrix generates a MDS code. The standard degree normal rational curve in is the image of the embedding
[TABLE]
or equivalently where represents if , and if . To keep the notation simple, we use the same symbol for the class in of the vector . When , these points form a arc in because they represent the columns of the matrix . A -arc in is said to be complete if it is not a subset of a -arc in . Therefore, Lemma II.4 can be restated in finite geometry terms as:
Lemma II.4 restated: For , we have or according as whether the points of the degree normal rational curve in form a complete arc or not.
A well-known conjecture in finite geometry is:
Conjecture II.5**.**
For , the points of the degree normal rational curve in form a complete arc except when is even and .
We note that Conjecture I.2 mentioned in the introduction is just a restatement of Conjecture II.5. The conjecture is true if from the work of Seroussi and Roth [13]. This was improved to the range in [14]. Also, Conjecture II.5 is a special case of the famous MDS conjecture which states that for , the maximum possible length of a -dimensional MDS code is except when is even and . Therefore, Conjecture II.5 is true for a value of if the MDS conjecture is true for the same . Some values of for which the MDS conjecture is true are:
[1, Theorem 1.10]: 2. 2.
[15]: even, .
Some other values of for which the Conjecture II.5 has been proved (for example for odd) can be found in [9, §4].
For , Problem I.3 was solved in [9]:
Theorem II.6**.**
Let .
- •
If is even, then and . In other words, there is exactly one deep hole class and its projective syndrome is .
- •
If is odd, then . There are deep hole classes, and consists of all points of other than the points .
Briefly, the problem of finding all such that the matrix generates a MDS code is easily seen to have no solution if is odd, and if is even then must be for . Thus by Lemma II.4, if is odd, and if is even. Next, by Lemma II.2, is the syndrome of a deep hole if and only if
Case when is odd: cannot be expressed as a linear combination of one column of . In other words, the class of in consists of the points of other that . 2. 2.
Case when is even: the matrix generates a MDS code, which has the only solutions as noted above.
II-B Remarks on the Covering Radius of MDS codes
It is sometimes asserted in literature (for example [2], [7]) that the covering radius of any linear MDS code is either or . In this section we wish to emphasize that there is no known correct proof of this assertion, and hence it remains a widely believed conjecture. Let and denote a pair of generator and parity check matrices for . We recall that the covering radius of any linear code is at most .
Lemma II.7**.**
The following assertions are equivalent for an MDS code :
** 2. 2.
There exists a word such that the matrix generates a MDS code. 3. 3.
There exists a word such that the matrix generates a MDS code. 4. 4.
There exists a vector such that the matrix generates a MDS code extending by one coordinate.
Proof:
: We have if and only if there exists a word with error distance . This in turn is true if and only if no minor of the matrix is zero.
: Since every minor of is nonzero, it follows that every minor of the matrix is nonzero if and only if the same is true of the matrix .
: Suppose generates a MDS code. A parity check matrix for this code is . Since the dual code of an MDS code is MDS, it follows that the latter matrix generates an MDS code. Conversely suppose the matrix generates an MDS code. Since is full rank, there exists a word such that . The matrix also generates an MDS code as it is a parity check matrix for the code generated by . ∎
If the matrix generates a code, then the latter code is called a supercode containing . By Lemma II.7 it follows that if and only if cannot be embedded in an MDS supercode, or equivalently if cannot be extended to a MDS code. It is not true in general that any MDS code with can be embedded in a MDS supercode, because dually, it is not true that any MDS code for can be extended to a MDS code. In finite geometry terms there do exist complete arcs of length in for some . For instance several examples of complete -arcs in are known for some with (see [8, Tables 1,2]), which means that there do exist MDS codes for which cannot be embedded in a MDS supercode. Thus, Remark 1) of [7] is not accurate. For such codes , it is unlikely that , however there is no known proof that to the authors’ best knowledge.
Theorem 2 of [7] asserts that any MDS code (except the cases when is even) has covering radius . Here, by Lemma II.7, one must clearly add the hypothesis that cannot be embedded in a MDS supercode, or equivalently cannot be extended to an MDS code of length (the additional hypothesis is not necessary if the MDS conjecture is true in dimension ). In the proof of this theorem, the authors assume that can be taken to be , for which the result is true by Lemma II.4. However, it is not true in general that every MDS code of length is PRS, and therefore we cannot conclude that . It is unlikely that but there is no proof yet.
II-C Automorphisms of PRS codes
The automorphism group of a linear code acts on the set of deep holes of the code, and hence can be a useful tool to determine the set of deep holes. We begin with some general notions concerning automorphisms of a linear code. We recall that the subgroup of consisting of Hamming isometries of is the group of monomial matrices (a monomial matrix is a product of a permutation matrix and a diagonal matrix). Since we are writing words of as row vectors, the action of on a word is . For a linear code , the automorphism group Aut of the code is the subgroup of consisting of those monomial matrices satisfying for all . Since is linear, the group of scalar matrices (where is the identity matrix) is contained in the center of Aut. Let denote the quotient group .
Given a pair of generator and parity check matrices for , we can define monomorphisms and defined as follows. For each the matrix is also a generator matrix for . The fact that also is in implies that is also a generator matrix for . Similarly, the fact that implies that for all . Therefore, is also a parity check matrix for . Since generator and parity check matrices are unique upto row equivalence, it follows that there exist matrices and such that and . Moreover, the matrices and are unique because and are full rank. We define
[TABLE]
The identities
[TABLE]
show that are group homomorphisms. Again, the fact that and are full rank implies that the only matrices satisfying and are the identity matrices. Therefore, and are monomorphisms. Finally, we use the same notation and for the induced monomorphisms and . Here denotes, as above the quotient group . Since carries to , it follows that Aut acts on the vector space of cosets of . The action of Aut on , induces an action of on the projective space of equivalence classes of non-codewords. The bijective correspondence (given in (4)) respects the action of :
[TABLE]
For and a received word , clearly the error distance . In particular acts on the set of deep holes of , and acts on the set of deep hole classes of .
We now return to the code . For , if , then the equation implies that preserves the set of points . Similarly, the equation implies that preserves the set of points . Here we have used the fact that for a monomial matrix , the columns of a matrix are obtained from the columns of by permutation and rescaling. We recall that there is a bijection given by where it is understood that for . The action of on the vector space induces an action of on the set of one dimensional subspaces of . Given and , we have . In terms of the identification , this is usually written as and referred to as a Möbius or fractional linear transformation.
Definition II.8**.**
For each , we define functions denoted as follows. For , the -th entry of is the coefficient of in the polynomial .
For example and,
[TABLE]
We collect some properties of the matrices :
[3, Proposition 2.6]: the map is a group homomorphism and the induced homomorphism (which we again denote by ) is a monomorphism. 2. 2.
[3, Proposition 2.5]): For each we have
[TABLE] 3. 3.
[3, Theorem 2.10]: For , the only elements of which preserve the set are
Thus for , the images of the monomorphisms and are precisely and . The group itself can be described as follows: The action of on gives a monomorphism from to the group of permutation matrices in defined by:
[TABLE]
By the identity (9), it follows that there exists a diagonal matrix such that the monomial matrix satisfies the property
[TABLE]
In particular,
[TABLE]
Since (from ) and are both monomorphisms, it follows that is an isomorphism from to .
For completenes, we write down the matrices :
[TABLE]
Since is also a parity check matrix for , it follows from the definition of the homomorphism that
[TABLE]
Therefore,
[TABLE]
Using this, the equation (6) for becomes:
[TABLE]
We summarize this in the following lemma:
Lemma II.9**.**
Let and be deep hole classes of . Then is in the orbit of if and only if there exists such that .
We end this section with a calculation of the orbit of
[TABLE]
which we need in the next section. We also use the same symbol for the vector .
Lemma II.10**.**
Let , and let be as above.
if and is odd, the orbit of has size and its stabilizer is the group . 2. 2.
if and , the orbit of has size and its stabilizer is the group . 3. 3.
if and , the orbit of has size and its stabilizer is the group . 4. 4.
if and is even, the orbit of has size and its stabilizer is the whole group . 5. 5.
* is in the -orbit of if and only if . In case , the orbit of has size , and its stabilizer is the group .*
Proof:
For , we have by Definition II.8:
[TABLE]
In order to determine when this equals , we consider the cases and separately. First suppose . The first and last components of (12) imply , i.e. either or . In the former case which equals if and only if . If , then . This proves the assertions 1) and 2). Now suppose . If , we have . If , using the fact that , we can write
[TABLE]
This equals if and only if . This proves the assertions 3) and 4).
If , then for . If , then it is clear from (12) that, for every in the -orbit of , the last entry of is zero. In particular, is not in the -orbit of . Also, for , we have
[TABLE]
Thus stabilizes if and only if and . Therefore, the stabilizer of is the group . This proves assertion 5). ∎
II-D New deep holes of PRS codes
In this section we obtain the two new deep hole classes of given in Theorem I.5 and Theorem I.6. We throughout assume in this section.
Proof of Theorem I.5
Assuming , we need to show that the words
[TABLE]
represent distinct deep holes classes of , and that these are distinct from the deep holes of Theorem I.4. The -th component of is
[TABLE]
Expanding as , we have:
[TABLE]
Summing the last equation over all , we get:
[TABLE]
where we have used the identity (3), and the fact that . Therefore, the -th component of is
[TABLE]
In other words:
[TABLE]
where .
For , it follows from (8) that:
[TABLE]
where each of the components of this equation are polynomial identities in with . Differentiating this polynomial identity with respect to gives
[TABLE]
Using this in (13), we get
[TABLE]
Further, using (7) we get:
[TABLE]
Thus the projective syndrome is in the -orbit of . Since is the syndrome of the deep hole , it follows from Lemma II.9 that are deep holes.
Next we show that the words represent distinct deep hole classes. Suppose the projective syndromes . In view of (15), we may assume (i.e. ). If , then the expression shows that , and hence . Next, suppose . Since , the last two components of are zero, but the last two components of , namely
[TABLE]
cannot both be zero. This contradiction shows that the projective syndromes and are distinct if .
Next we show that the deep hole classes represented by are distinct from the the classes of Theorem I.4. The fact that implies that the first two components of are zero, but the first two components of cannot both be zero. This shows that the deep hole classes of the words are distinct from the classes of Theorem I.4.
We recall from Lemma II.10, that is in the orbit of provided . If , then the orbits of and are distinct, and the latter orbit contains . Combining this with the fact that is in the orbit of , we conclude:
The deep holes of Theorems I.4 and Theorem I.5 put together form:
in case , the orbit of 2. 2.
in case , the orbits of and of sizes and respectively.
Remark: In terms of the the standard degree normal rational curve in , the projective tangent line to the curve at for each has points with -coordinates given by itself and the points . If , then these points are and . As shown above, the tangent lines have no pairwise intersection when . Thus the geometric interpretation of the syndromes of the deep hole classes in Theorems I.4 and I.5, is that these consist of those points with -coordinates which are not on the curve, but are in the union of the tangent lines to the curve.
Proof of Theorem I.6
For each in the set of monic irreducible quadratic polynomials over , and for each , let be the word in defined by
[TABLE]
Assuming , we must show that words given by represent distinct deep hole classes of for , and that these are distinct from the classes of Theorems I.4 and I.5. We begin with two lemmas.
Lemma II.11**.**
The projective syndrome of the word is
[TABLE]
where is a root of in a quadratic extension of , and
[TABLE]
Proof:
Let be a root of , and let denote the nontrivial automorphism of over . We have:
[TABLE]
Using this in (16), we get:
[TABLE]
where
[TABLE]
Using the partial fraction expansions
[TABLE]
we get
[TABLE]
Multiplying by does not change the projective syndrome. Therefore,
[TABLE]
where is as defined in (17). ∎
Lemma II.12**.**
The group preserves the set of words of the form .
Proof:
We know from (10) that
[TABLE]
where , and . Since , the same is true for , and hence any element of is of the form for some . In particular any element of is represented by one of the elements
[TABLE]
Thus we may take for some . ∎
Next we show that the are deep holes of when . By Lemma II.2, we must show that is not in the -span of columns of . Consider the matrix
[TABLE]
where is a listing of . We know that any columns of this matrix are linearly independent over . In particular
[TABLE]
is not in the -span of columns of , as was to be shown. Moreover for , we have , and hence any four columns of are linearly independent over . This shows that if then their projective syndromes
[TABLE]
(where ) are distinct. This proves that the words of (16) represent distinct deep hole classes of .
Next, we show that the deep hole classes of Theorems I.4 and I.5 are distinct from those of Theorem I.6. The projective syndromes of the former deep hole classes are in the -orbit of or , where as by Lemma II.12, the projective syndromes of words in the -orbits of the latter deep hole classes are of the form . Since we have assumed . i.e , it follows that the first two coordinates of are zero. However the first two coordinates of , namely are both zero only if which is not the case.
Remark: Consider the standard normal rational curve of degree in projective space over an extension field of . Let be two distinct points on the curve such that not both of them have -coordinates. Let be a point on the secant line joining . Since any columns of the matrix are linearly independent over , it follows in particular, that cannot be written as a -linear combination of columns of . Thus provided has -coordinates. For to have -coordinates, must be an even power of so that there is a quadratic extension of in , and we must have where is the nontrivial automorphism of over . Thus the geometric interpretation of the syndromes of the deep hole classes is as follows: there are pairs of distinct points on the curve, and on the secant line joining , there are points with coordinates.
III Complete deep holes of
In this section, we will show that the deep holes constructed in Theorems I.4, I.5 and I.6 form all the deep holes of . Since for has been treated in §II-A, we assume . Since Conjecture I.2 is true for when , it follows that provided i.e. , which is the case here. For , even the problem of just determining the number of deep hole classes (not necessarily determining all of them) is very difficult for . If , this reduces to the problem of determining the number of points of which are not in the span of any columns of . For , we can calculate this number:
Theorem III.1**.**
There are classes of deep holes of .
Proof:
The number of deep hole classes of is
[TABLE]
There are points in which are in the span of less than two columns of (namely ). For each of the pairs of columns , there are points which are in the span of these two columns but are not in . Since any columns of are linearly independent, a point of which is not in , cannot be in the span of two different pairs of columns of . Therefore, the number of deep hole classes of is
[TABLE]
∎
We have shown in Theorem I.5 that the deep hole classes constructed in this theorem are distinct from the deep hole classes constructed in Teorem I.4. We have also shown in Theorem I.6, that the deep hole classes constructed in this theorem are distinct from the deep hole classes of Theorems I.4 and I.5. Since
[TABLE]
we conclude that all deep hole classes of have been found.
IV Conclusion
The foremost open problem about deep holes for Projective Reed-Solomon (PRS) codes, is to determine the covering radius of these codes – i.e. to settle Conjecture I.2, or equivalently Conjecture II.5. This is a special and important case of the well known MDS conjecture. For dimensions in which Conjecture I.2 is known to be true, the next important problem is to determine the deep holes of the code . This is a difficult problem. The oldest known deep holes of are those generated by the polynomial . By applying the full automorphism group of to these deep holes we obtained in this work the deep holes of Theorems I.4 and I.5. In Theorem I.6, we obtained new deep holes of using some words having error distance from the the -linear code . We determined the number of deep holes of and showed in Theorem I.7, that the above two constructions account for all the deep holes of . For it seems increasingly difficult to enumerate the deep holes of . The case will be discussed in a forthcoming work.
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