This paper extends a classical theorem on minimal weight codewords from Reed-Muller codes to a broader class of Reed-Muller type codes over products of finite fields, and discusses the structure of low weight codewords.
Contribution
It generalizes the minimal weight codeword characterization to Reed-Muller type codes over product fields and explores their low weight codeword structure.
Findings
01
Extended Delsarte-Goethals-Mac Williams theorem to new code classes
02
Characterized minimal weight codewords in these codes
03
Analyzed the structure of low weight codewords in affine and projective cases
Abstract
In 1970 Delsarte, Goethals and Mac Williams published a seminal paper on generalized Reed-Muller codes where, among many important results, they proved that the minimal weight codewords of these codes are obtained through the evaluation of certain polynomials which are a specific product of linear factors, which they describe. In the present paper we extend this result to a class of Reed-Muller type codes defined on a product of (possibly distinct) finite fields of the same characteristic. The paper also brings an expository section on the study of the structure of low weight codewords, not only for affine Reed-Muller type codes, but also for the projective ones.
Tables3
Table 1. Table 1: Second (or next-to-minimal) weights for G R M q ( n , d ) 𝐺 𝑅 subscript 𝑀 𝑞 𝑛 𝑑 GRM_{q}(n,d) and
P G R M q ( n , d ) 𝑃 𝐺 𝑅 subscript 𝑀 𝑞 𝑛 𝑑 PGRM_{q}(n,d) when
n ≥ 2 𝑛 2 n\geq 2 and q = 2 𝑞 2 q=2
Table 2. Table 2: Second (or next-to-minimal) weights for G R M q ( n , d ) 𝐺 𝑅 subscript 𝑀 𝑞 𝑛 𝑑 GRM_{q}(n,d) and
P G R M q ( n , d ) 𝑃 𝐺 𝑅 subscript 𝑀 𝑞 𝑛 𝑑 PGRM_{q}(n,d) when
n ≥ 1 𝑛 1 n\geq 1 and q = 3 𝑞 3 q=3
Table 3. Table 3: Second (or next-to-minimal) weights for G R M q ( n , d ) 𝐺 𝑅 subscript 𝑀 𝑞 𝑛 𝑑 GRM_{q}(n,d) and
P G R M q ( n , d ) 𝑃 𝐺 𝑅 subscript 𝑀 𝑞 𝑛 𝑑 PGRM_{q}(n,d) when
n ≥ 1 𝑛 1 n\geq 1 and q ≥ 4 𝑞 4 q\geq 4
c=\left\{\begin{array}[]{lcl}q&\textrm{ if }&k=n-1;\\
\ell-1&\textrm{ if }&k<n-1\textrm{ and }1<\ell\leq(q+1)/2;\\
&\textrm{ or }&k<n-1\textrm{ and }\ell=q-1\neq 1;\\
q&\textrm{ if }&k=0\textrm{ and }\ell=1;\\
q-1&\textrm{ if }&q<4,0<k<n-2,\textrm{ and }\ell=1;\\
q-1&\textrm{ if }&q=3,0<k=n-2\textrm{ and }\ell=1;\\
q&\textrm{ if }&q=2,k=n-2\textrm{ and }\ell=1;\\
q&\textrm{ if }&q\geq 4,0<k\leq n-2\textrm{ and }\ell=1;\\
\ell-1&\textrm{ if }&q\geq 4,k\leq n-2\textrm{ and }(q+1)/2<\ell.\end{array}\right.
c=\left\{\begin{array}[]{lcl}q&\textrm{ if }&k=n-1;\\
\ell-1&\textrm{ if }&k<n-1\textrm{ and }1<\ell\leq(q+1)/2;\\
&\textrm{ or }&k<n-1\textrm{ and }\ell=q-1\neq 1;\\
q&\textrm{ if }&k=0\textrm{ and }\ell=1;\\
q-1&\textrm{ if }&q<4,0<k<n-2,\textrm{ and }\ell=1;\\
q-1&\textrm{ if }&q=3,0<k=n-2\textrm{ and }\ell=1;\\
q&\textrm{ if }&q=2,k=n-2\textrm{ and }\ell=1;\\
q&\textrm{ if }&q\geq 4,0<k\leq n-2\textrm{ and }\ell=1;\\
\ell-1&\textrm{ if }&q\geq 4,k\leq n-2\textrm{ and }(q+1)/2<\ell.\end{array}\right.
ZX(f):={α∈X∣f(α)=0}
ZX(f):={α∈X∣f(α)=0}
Aff\/(X)={φ:X→X∣φ=ψ∣X with ψ∈Aff\/(n,Fq) and ψ(X)=X}.
Aff\/(X)={φ:X→X∣φ=ψ∣X with ψ∈Aff\/(n,Fq) and ψ(X)=X}.
G_{\alpha}=\alpha e_{k+1}+V_{k+1}=\left\{\mbox{{\boldmath$\beta$}}\in\mathbb{F}_{q}^{N}\mid\mbox{{\boldmath$\beta$}}=(\beta_{1},\ldots,\beta_{N})\textrm{ and }\beta_{k+1}=\alpha\right\}
G_{\alpha}=\alpha e_{k+1}+V_{k+1}=\left\{\mbox{{\boldmath$\beta$}}\in\mathbb{F}_{q}^{N}\mid\mbox{{\boldmath$\beta$}}=(\beta_{1},\ldots,\beta_{N})\textrm{ and }\beta_{k+1}=\alpha\right\}
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TopicsCoding theory and cryptography · Cooperative Communication and Network Coding · Islamic Finance and Communication
Full text
**An extension of Delsarte, Goethals and Mac Williams theorem on
minimal weight codewords to
a class of Reed-Muller type codes **
Cícero Carvalho and Victor G.L. Neumann111Both authors
were partially supported by grants from CNPq and FAPEMIG.
*Faculdade de Matemática
Universidade Federal de Uberlândia
Av. J. N. Ávila 2121, 38.408-902 - Uberlândia - MG, Brazil
Abstract.
In 1970 Delsarte, Goethals and Mac Williams published a seminal paper on
generalized Reed-Muller codes where, among many important results, they
proved that the minimal weight codewords of these codes are obtained through
the evaluation of certain polynomials which are a specific product of linear
factors, which they describe. In the present paper we extend this result to a
class of Reed-Muller type codes defined on a product of (possibly distinct)
finite fields of the same characteristic. The paper also brings an expository
section on the study of the
structure of low weight codewords, not only for affine Reed-Muller type
codes, but also for the projective ones.
1 Introduction with a hystorical survey
Let Fq a field with q elements, let K1,…,Kn be
a collection of non-empty subsets of Fq, and let
[TABLE]
Let di:=∣Ki∣ for i=1,…,n, so
clearly ∣X∣=∏i=1ndi=:m, and let
X={α1,…,αm}. It is not difficult to check that the
ideal of polynomials in Fq[X1,…,Xn] which vanish on X is
IX=(∏α1∈K1(X1−α1),…,∏αn∈Kn(Xn−αn)) (see e.g.
[25, Lemma 2.3] or [7, Lemma 3.11]). From this we get that
the evaluation morphism Ψ:Fq[X1,…,Xn]/IX→Fqm given by P+IX↦(P(α1),…,P(αm)) is
well-defined and
injective. Actually, this is an isomorphism of Fq-vector spaces because for
each i∈{1,…,m} there exists a polynomial Pi such that
Pi(αj) is equal to 1, if j=i, or [math], if j=i, so that Ψ is
also surjective.
Definition 1.1
Let d be a nonnegative integer.
The affine cartesian code (of order d) CX(d)
defined over the sets K1,…,Kn is the image, by Ψ, of the set of
the classes of all polynomials of degree up to d, together with the class of
the zero polynomial.
These codes appeared
independently in [25] and [17] (in [17] in a
generalized form). In the special case
where K1=⋯=Kn=Fq we have the well-known generalized Reed-Muller
code of order d. In [25] the authors prove that we may ignore,
in the cartesian product, sets with just one element and moreover may always
assume that 2≤d1≤⋯≤dn. They also determine the dimension
and the minimum distance of these codes.
For the generalized Reed-Muller codes, the classes of the polynomials whose
image are the codewords of minimum weight were first described explicity by
Delsarte,
Goethals and Mac Williams in 1970. This result started a series of
investigations of the structure of codewords of all weights, not only in
generalized Reed-Muller codes, but also in related Reed-Muller type codes.
In the present paper we extend the result of Delsarte, Goethals and Mac Williams
to affine cartesian codes, in the case where Ki is a field, for all i=1,…,n and K1⊂K2⊂⋯⊂Kn⊂Fq, but
before we describe the contents of the next sections of this work, we would
like to present a survey of results that pursued the investigation started by
Delsarte, Goethals and Mac Williams.
Reed-Muller codes are binary codes defined by Muller ([28]) and were
given a decoding algorithm by Reed ([29]), in 1954. In 1968 Kasami, Lin
and Peterson ([18]) introduced what they called the generalized
Reed-Muller codes, defined over a finite field Fq with q
elements, which coincided with Reed-Muller codes when q=2. Their idea was
to
consider the Fq-vector space Fq[X1,…,Xn]≤d
of all
polynomials in
Fq[X1,…,Xn] of degree less or equal than d, together
with the zero polynomial, for some
positive integer d, and define the generalized Reed-Muler code of order d
as
[TABLE]
where α1,…,αqn are the points of the affine space
An(Fq). Equivalently, using the fact that I=(X1q−X1,…,Xnq−Xn) is the ideal of
polynomials whose zero set is An(Fq), we have that
GRMq(d,n) is the image of the linear transformation
Ψ:Fq[X1,…,Xn]/I→Fqqn given by P+IX↦(P(α1),…,P(αqn)).
Kasami et al. proved that if d≥n(q−1) then we have
GRMq(d,n)=Fqqn hence the minimum distance
δGRMq(d,n)
of GRMq(d,n) is 1. For 1≤d<n(q−1) write d=k(q−1)+ℓ
with
0<ℓ≤q−1, then δGRMq(d,n)=(q−ℓ)qn−k−1
(see
[18, Thm. 5]). McEliece, studying quadratic forms defined over
Fq (see [26]) described the so-called weight enumerator
polynomial for GRMq(2,n), i.e. described all possible
weights for the codewords in GRMq(2,n), together with the number of
codewords
of each
weight, and also gave canonical forms for the polynomials whose classes
produced codewords of all weights.
In 1970 Delsarte, Goethals and Mac Williams published a
40 pages seminal paper which started the systematic study of the generalized
Reed-Muller codes
and
other codes related to them. Among the many important results in the paper,
there is a
description of the polynomials whose evaluation yields the codewords with
minimum
distance. To state their result, we recall that the affine group of
automorphisms of Fq[X1,…,Xn] is the one given by
transformations of the type Xt↦AXt+β, where X=(X1,…,Xn), A is a n×n invertible matrix with entries
in Fq and β∈Fqn.
Theorem 1.2
[13, Theorem 2.6.3]**
The minimal weight codewords of GRMq(d,n) come from the evaluation of
Ψ in classes f+I of polynomials f which, after a suitable action of
an affine automorphism of Fq[X1,…,Xn], may be written as
[TABLE]
where d=k(q−1)+ℓ with
0<ℓ≤q−1, α∈Fq∗ and β1,…,βℓ are distinct elements of Fq (in the case k=0 we
take the first product to be 1).
Since GRM codes arise from the evaluation of polynomials in points of an
affine space, there is also an algebraic geometry interpretation for the
codewords. In fact, the above theorem shows that the zeros of a minimal weight
codeword lie on a special type of hyperplane arrangement. More explicitly, we
have the following alternative statement (taken from [1]) for the
above result.
Theorem 1.3
Let V be an algebraic
hypersurface in An(Fq), of degree at most d, with
1≤d<n(q−1), which is not the whole An(Fq).
Then V has the maximal possible number of zeros if and only if
[TABLE]
where d=k(q−1)+ℓ with
0≤ℓ<q−1, the Vi,s and Wj are d distinct hyperplanes
defined on Fq such
that for each fixed i the Vi,s are q−1 parallel hyperplanes, the
Wj are ℓ parallel hyperplanes
and the k+1 distinct linear forms directing these hyperplanes are linearly
independent.
This result was the start of the search for the higher Hamming weights together
with the description (algebraic and geometric) of the codewords having these
weights, not only for GRMs but in general for all Reed-Muller type codes, like
the ones studied in this paper, for the GRMs alone the search is still ongoing.
In 1974 Daniel Erickson, a student of McEliece and Dilworth,
devoted his Ph.D. thesis to the determination of the
second lowest Hamming weight, also called next-to-minimal weight, of
GRMq(d,n) (see [14]). He succeeded in determining the values of
the second weight for
many values of d in the relevant range 1≤d<n(q−1). For the values
that he was not able to determine, following a suggestion by M. Hall, he
generalized some of the results of Bruen on blocking sets, which had appeared
in
[2], and made a conjecture relating the expected value for the
missing weights to the cardinality of certain blocking sets in the affine plane
A2(Fq). Also, instead of
working with the classes of polynomials in
Fq[X1,…,Xn]/I he worked with a fixed set of representatives
called “reduced polynomials” which he noted that were in a one-to-one
correspondence with the functions from Fqn to Fq. This
had an influence on the paper [22] and also the present text, as we
will comment later. Unfortunately Erikson’s results were not published, and
the quest for the next-to-minimal weights of GRM codes went on for many years
without his contributions.
In 1976 Kasami, Tokura and Azumi (see [19]) determined all the weights of
GRM2(d,n) (i.e.
Reed-Muller codes) which are less
than 25δGRM(d,2). They also determined canonical forms for the
representatives of the classes whose evaluation produces codewords of these
weights, together with the number of such words. In particular, the second
weight of Reed-Muller codes was determined. After this paper, there was not
much work done on the problem of determining the higher Hamming weights of
GRMq(d,n) during two
decades. Then, in 1996 Cherdieu and Rolland (see [12])
determined the second weight of
GRMq(d,n) for d in the range 1≤d<q−1, provided that q is large enough. They also proved that in
this case the zeros of codewords having next-to-minimal weight form an specific
type of hyperplane arrangement which they describe.
In the following year a work by Sboui (see [35]) proved that
the result by Cherdieu and Rolland holds when d≤q/2.
In 2008 Geil (see [15] and [16]) determined the second
weight of GRMq(d,n)
for
2≤d≤q−1 and 2≤n. Also, for d in the range (n−1)(q−1)<d<n(q−1), he
determined the first d+1−(n−1)(q−1) weights of GRMq(d,n).
His results completely determine the next-to-minimal weight of GRMq(d,2),
since in this case the relevant range for d is 1≤d<2q.
Geil’s theorems were obtained using results from Gröbner basis theory. In
2010 Rolland made a more detailed analysis of the weights also using Gröbner
basis theory results, and determined almost all
next-to-minimal
weights of GRMq(d,n) (see [34]). In fact, he succeeded in finding
the next-to-minimal weights for all values of d, in the range q≤d<n(q−1), that
can not be written in the form d=k(q−1)+1.
Finally, also in 2010, A. Bruen had his attention directed to Erickson’s thesis, and in a note (see
[3]) observed that Erickson’s conjecture was an easy consequence of
results that he, Bruen, had proved in 1992 and 2006 (see [4] and
[5]). This finally completed the determination of the next-to-minimal
weights
δGRMq(d,n)(2)
of GRMq(d,n), and now we know that for 1≤d<n(q−1), writing d=k(q−1)+ℓ
with
0≤ℓ<q−1, then δGRMq(d,n)=(q−ℓ)qn−k−1
and δGRMq(d,n)(2)=δGRMq(d,n)+cqn−k−2, where
[TABLE]
In 2012 the 1970’s theorem of Delsarte, Goethals and Mac Williams was the
subject
of a paper by Leducq (see [22]). In their paper, Delsarte et al. prove the theorem on the minimum distance in an Appendix entitled “Proof of
Theorem 2.6.3.”, which opens with the
sentence: “The authors hasten to point out that it would be very
desirable to find a
more sophisticated and shorter proof.” Leducq indeed provides a shorter
and less technical proof, treating the codewords as functions from
Fqn to Fq and using results from affine geometry. Some
of these results appear in the appendix of Delsarte et al. paper, and were
also used by Erickson in his work. In the following year, Leducq (see
[23]) completed the
work of previous researchers, with Sboui, Cherdieu, Rolland and Ballet among
them, and
proved that the next-to-minimal weights are only attained by codewords whose
set of zeros form certain hyperplane arrangements. In the same year
Carvalho (see [6]) extended Geils’s results of 2008 to
affine cartesian codes, also determining a
series of higher Hamming weights for these codes.
In 2014 a paper by Ballet and Rolland (see [1]) presented bounds on
the third and fourth Hamming weights of GRMq(d,n) for certain ranges of d. In the following year Leducq (see [24]), pursuing and developing
ideas from Erickson’s thesis, determined the third weight and characterized the
third weight words of GRMq(d,n) for some values of d.
In 2017 Carvalho and Neumann (see [9]) extended many of the
results of Rolland, in [34], to affine cartesian codes. They found
the second weight of these codes for all values of d which can not be written
as d=∑i=1k(di−1)+1, and they also prove that the weights
corresponding to such values of d are attained by codewords whose set of
zeros are hyperplane arrangements (yet they don’t prove that every word
attaining those next-to-minimal weights comes from hyperplane arrangements).
There is a “projective version” of the generalized Reed-Muller codes whose
parameters have been studied like those of GRMq(d,n) and to which they are
related. This version was introduced by Lachaud in 1986 (see [20]),
but one can find some examples of it already in [39].
Let γ1,…,γN be the points of
Pn(Fq), where N=qn+⋯+q+1. From e.g. [30] or
[27] we get that the homogeneous ideal Jq⊂Fq[X0,…,Xn] of the polynomials which vanish in all points of
Pn(Fq) is
generated by {XjqXi−XiqXj∣0≤i<j≤n}. We denote by Fq[X0,…,Xn]d
(respectively, (Jq)d) the Fq-vector subspace formed by the
homogeneous polynomials of degree d (together with the zero polynomial) in
Fq[X0,…,Xn] (respectively, Jq).
Definition 1.4
Let d be a positive integer and
let Θ:Fq[X0,…,Xn]d/(Jq)d→FqN be the
Fq-linear transformation given by Θ(f+(Jq)d)=(f(γ1)…,f(γN)), where we write the points of
Pn(Fq) in the
standard
notation, i.e. the first nonzero entry from the left is equal to 1. The
projective generalized Reed-Muller code of order d, denoted by PGRMq(n,d), is the
image of Θ.
It is easy to check that if one chooses another representation for the
projective points the code thus obtained is equivalent to the code defined
above. It is also easy to prove that if d≥n(q−1)+1 then Θ is
an isomorphism, so the relevant range to investigate the parameters of PGRM
codes is 1≤d≤n(q−1).
Lachaud, in [20] presents some bounds for δPGRMq(n,d),
the minimum distance for
PGRMq(n,d), and determines the true value in a special case. Serre, in 1989
(see [37]), determined the minimum distance of PGRMq(n,d) when d<q. In 1990 Lachaud (see[21]) presents some properties that some
higher weights of PGRMq(n,d) must have, when d≤q and d≤n.
Let g∈Fq[X1,…,Xn] be a polynomial of degree d−1≥1 and let ω be the Hamming weight of Φ(g+I). Let
g(h) be the
homogenization of g with respect to X0, then the degree of X0g(h)
is d
and the weight of Θ(X0g(h)+(Jq)d) is ω. In particular
δPGRMq(n,d)≤δGRMq(n,d−1). When d=1 all the
codewords of PGRMq(n,d) have the same number of zeros entries (hence the
same weight), which is equal to the number of points of a hyperplane in
Pn(Fq), this also implies that for d=1 there are no
higher Hamming weights. In 1991 Sørensen (see [38]) proved that
δPGRMq(n,d)=δGRMq(n,d−1) holds for all d in the
relevant range. After this paper, similarly to what had happened with GRM
codes, the subject lay dormant for almost two decades. Then, in 2007 Rodier and
Sboui (see [31]), under the condition d(d−1)/2<q determined a
Hamming weight of PGRMq(n,d), which is not the minimal and is only achieved
by codewords whose zeros are hyperplane arrangements. In 2008 the same authors
(see [32]) proved that for q/2+5/2≤d<q
the third weight of PGRM is not only achieved by evaluating Θ in the
classes of totally
decomposable
polynomials but can also be obtained in this case from classes of some
polynomials
having an irreducible quadric as a factor. Also in 2008, Rolland (see
[33]) proved the
equivalent of Delsarte, Goethals and Mac Williams theorem for PGRM codes,
completely characterizing the codewords of PGRMq(n,d) which have minimal
weights, and proving that they only arise as images by Θ of classes of
totally
decomposable polynomials, which in a sense may be thought of as the
homogenization of the polynomials described by Delsarte et al. In 2009
Sboui ([36]) determined the second and third weights of
PGRMq(n,d) in the range 5≤d≤q/3+2. He proved that codewords
which have these weights come only from evaluation of classes of totally
decomposable polynomials and calculated the number of codewords having
weights equal to the minimal distance, or the second weight, or the third weight.
In the already mentioned paper of 2014 (see [1]), Ballet and Rolland
we find another proof of Rolland’s result on minimal weight codewords of PGRM.
They also present lower and upper bounds for the second weight of PGRMq(n,d).
Putting together the reasoning presented in the beginning of the preceding
paragraph and Sørensen’s result δPGRMq(n,d)=δGRMq(n,d−1), and writing δPGRMq(n,d)(2) for the second Hamming weight
of PGRMq(n,d), we get δPGRMq(n,d)(2)≤δGRMq(n,d−1)(2)
for
all 2≤d≤n(q−1)+1. In 2016 Carvalho and Neumann (see
[8]) determined the
second weight of PGRM2(n,d) for all d in the relevant range, and in 2018
(see [10]) they also determined the second weight of PGRMq(n,d), for q≥3 and
almost all values of d. For some values of d, in both papers, it happened
that δPGRMq(n,d)(2)<δGRMq(n,d−1)(2), and they
proved
that in all these cases the zeros of the codewords with weight
δPGRMq(n,d)(2) are not hyperplane arrangements.
They also observed that, writing d−1=k(q−1)+ℓ, with 0≤k≤n−1 and 0<ℓ≤q−1, in the case where q=3, k>0 and
ℓ=1 we have δPGRMq(n,d)(2)=δGRMq(n,d−1)(2) and there are codewords of weight δPGRMq(n,d)(2) whose
set of zeros are hyperplane arrangements and others which do not have this
property. The tables below show the current results for
δPGRMq(n,d)(2), where we write d−1=k(q−1)+ℓ as
above. The tables also present the values of
δGRMq(n,d−1)(2) so the reader can see the cases where one has
δPGRMq(n,d)(2)<δGRMq(n,d−1)(2).
A generalization of PGRM codes was introduced in 2017 by Carvaho, Neumann and
López (see
[11]), as the class of codes called “projective nested
cartesian codes”. They determined the dimension of these codes, bounds for the
minimum distance and the exact value of this distance in some cases.
In the present paper we extend Delsarte, Goethals and Mac Williams theorem to
the class of affine cartesian codes CX(d) defined
above, in the case where the sets
K1⊂⋯⊂Kn are subfields of Fqn.
Our main results are Proposition 3.1 , Proposition
3.2 and Theorem
3.5 which show that, as in the GRM
codes, the minimal weight codewords of CX(d) come from
the evaluation of
Ψ in classes f+I of polynomials f which, after a suitable action of
an automorphism group, may be written as the product of certain degree
one polynomials. In the next section we introduce the concept of code as an
Fq-vector space of functions (following [14] and
[22]) and define the relevant automorphism group for the main result.
We then study
the intersection of certain affine subspaces of
Fqn with X to find information on the structure of functions that
have “few” points in the support (see Corollary 2.11). Then, in
the beginning of
Section 3, we use these results to determine the structure of the functions (or
codewords) of minimal weight, for d within a certain range – in a sense, for
the lower values of d (see Proposition 3.1). Finally,
after exploring a little further the properties of the intersection
of certain hyperplanes with X, we prove our main result (see Theorem
3.5) which generalizes the result by
Delsarte,
Goethals and Mac Williams.
2 Preliminary results
Let CX(d) be the affine cartesian code as in Definition
1.1. We assume from now on that K1,…,Kn are fields and
that K1⊂K2⊂⋯⊂Kn⊂Fq. Recall that
∣Ki∣=di for i=1,…,n, so IX=(X1d1−X1,…,Xndn−Xn), and observe
that, since Ψ is an isomorphism, the code CX(d) is
isomorphic to the Fq-vector space of the classes of polynomials in Fq[X1,…,Xn]/IX of degree up to d (together with the zero
class).
It is well known that, given a subset Y⊂Fqn, any function f:Y→Fq is given by a polynomial P∈Fq[X1,…,Xn] (again,
this
is a consequence of the fact that given α∈Fqn there exists a
polynomial
Pα∈Fq[X1,…,Xn] such that Pα(α)=1 and
Pα(β)=0
for any β∈Fqn∖{α}). Denoting by
CX the
Fq-algebra of functions defined on X we clearly have an
isomorphism
Φ:Fq[X1,…,Xn]/IX→CX
hence for each function f∈CX there exists a unique polynomial
P∈Fq[X1,…,Xn] such that the degree of P in the
variable Xi is less than di for all i=1,…,n, and Φ(P+IX)=f.
Definition 2.1
We say that
P is the reduced polynomial associated to f and we define the degree of f as being the degree of P.
We denote by CX(d) the Fq-vector space formed by functions of
degree up to d, together with the zero function. We saw above that
CX is isomorphic to
Fq[X1,…,Xn]/IX, and hence to Fqm, and
clearly CX(d)⊂CX is isomorphic to the code
CX(d)⊂Fqm, so from now on we also call
CX(d) the affine cartesian code of order d. To study the
codewords of minimum weight we define the support of a function f∈CX as the
set
\{\mbox{{\boldmath\alpha}}\in\mathcal{X}\mid f(\mbox{{\boldmath\alpha}})\neq 0\} and we write
∣f∣ for its cardinality, which, in this approach, is the Hamming weight of f. Thus the minimum distance of CX(d) is
δX(d):=min{∣f∣∣f∈CX(d) and f=0}.
We denote by
[TABLE]
the set of zeros of f∈CX, and given functions g1,…,gs defined on Fqn we denote by Z(g1,…,gs) be the set
of common zeros, in Fqn, of these functions.
We write Aff\/(n,Fq) for the affine group of Fqn, i.e. the
transformations
of
Fqn of the type α⟼Aα+β, where
A∈GL(n,Fq)
and β∈Fqn.
Definitions 2.2
The affine group associated to
X is
[TABLE]
We say that f,g∈CX are X-equivalent if there exists
φ∈Aff\/(X)
such that f=g∘φ.
An affine subspace G⊂Fqn of dimension r is said to be
X-affine if there exists
ψ∈Aff\/(n,Fq) and
1≤i1<⋯<ir≤n such that ψ(X)=X and
ψ(⟨ei1,…,eir⟩)=G, where we write
{e1,…,en} for the canonical basis of Fqn. We denote by
xi the coordinate function xi(∑jajej)=ai where ∑jajej∈Fqn (and by abuse of notation we also denote by xi its
restriction to X) for all i=1,…,n.
Let f∈CX be a reduced polynomial of degree one, if
there exists
φ∈Aff\/(X) and i∈{1,…,n} such that xi∘φ=f on the points of X then we say that f is X-linear.
Let {i1,…,is}⊂{1,…,n} and j∈{1,…,n}, we define
Xi1,…,is:=Ki1×⋯×Kis,
and
Xj:=K1×⋯×Kj−1×Kj+1×⋯×Kn.
Definition 2.3
Let j∈{1,…,n},
for every α∈Kj we have an evaluation homomorphism of Fq-algebras
given by
[TABLE]
We now present two results which we will freely use in what follows. The first
one states the value of the minimum distance of CX(d).
Theorem 2.4
[25, Thm. 3.8]**
The minimum distance δX(d) of CX(d) is 1,
if d≥∑i=1n(di−1), and for 1≤d<∑i=1n(di−1) we have
[TABLE]
where k and ℓ are uniquely defined by d=∑i=1k(di−1)+ℓ with 0<ℓ≤dk+1−1 (if k+1=n we understand that
∏i=k+2ndi=1, and if d<d1−1 then we set k=0 and
ℓ=d).
The second one is a very useful numerical result, closely related to the above theorem (the link between these two results is explained in [6]).
Lemma 2.5
[6, Lemma 2.1]**
Let 0<d1≤⋯≤dn and 1≤d≤∑i=1n(di−1) be integers. Let m(a1,…,an)=∏i=1n(di−ai), where
0≤ai<di is an integer for all i=1,…,n. Then
[TABLE]
where k and ℓ are uniquely defined by d=∑i=1k(di−1)+ℓ, with 0<ℓ≤dk+1−1 (if s<d1−1 then take k=0 and
ℓ=d, if k+1=n then we understand that ∏i=k+2ndi=1).
From Theorem 2.4 we get that the relevant range for d is 1≤d<∑i=1n(di−1) (the case d=0 is trivial and if d≥∑i=1n(di−1) we have CX(d)≅Fqm). In what follows we will always
assume that 1≤d<∑i=1n(di−1) and will also freely use
the decomposition d=∑i=1k(di−1)+ℓ, with 0<ℓ≤dk+1−1 (and 0≤k<n). In many places we
consider a nonzero function g
defined in Xi1,…,is⊂Fqs
which belongs to CXi1,…,is(d),
and we want to
estimate ∣g∣.
Applying Theorem 2.4
we
get that ∣g∣≥1 if d≥∑t=1s(dit−1)
while
if
d<∑t=1s(dit−1) then ∣g∣≥δXi1,…,is(d), and we find
δXi1,…,is(d) by a proper application of
the formula in Theorem 2.4.
Since
δXi1,…,is(d)=1 in the case
where d≥∑t=1s(dit−1), we can always write ∣g∣≥δXi1,…,is(d).
The following result shows that functions which are related by an
affine transformation have the same degree.
Lemma 2.6
Let φ∈Aff\/(X) and f∈CX with f=0,
then
degf=deg(f∘φ).
**Proof: ** Since φ∈Aff\/(X) we have that
φ(α)=Aα+β
where A∈GL(n,Fq)
and β∈Fqn. Let P∈Fq[X] be the reduced polynomial
associated to f, and let’s endow Fq[X] with a degree-lexicographic order.
Then the reduced polynomial associated to f∘φ is the remainder,
say Q, in the division of P(AX+β) by {X1d1−X1,…,Xndn−Xn}, where X
is a
column vector with entries equal to X1,…,Xn. Thus degQ≤degP(AX+β)≤degP, so that
deg(f∘φ)≤degf. Applying the argument
to
φ−1 we conclude that deg(f∘φ)=degf.
□
The next result, although simple, is the basis for many
important results that follow.
Lemma 2.7
Let f,h∈CX be nonzero functions.
There exists a function g∈CX such that f=gh if and only
if
ZX(h)⊂ZX(f), i.e. h is a factor of f if and only of f vanishes in ZX(h).
Moreover, if h is X-linear then degg=degf−1.
**Proof: **
If f=gh and h(\mbox{{\boldmath\alpha}})=0
then f(\mbox{{\boldmath\alpha}})=0, for all α∈X.
Assume now that
ZX(h)⊂ZX(f), and let g:X→Fq be defined by g(α)=0 if α∈ZX(h),
and g(α)=f(α)/h(α) if α∈X∖ZX(h), then clearly f=gh as functions of CX.
Let’s assume now that h∣f and that h is
X-linear, so that
h∘φ=xi for some i∈{1,…,n} and
φ∈Aff\/(X). Then f∘φ=(g∘φ)(h∘φ) and since from Lemma 2.6degf=deg(f∘φ) we may simply assume that h=xi.
Let P be the reduced polynomial associated to f and write P=Xi⋅Q+R, where Q,R∈Fq[X1,…,Xn]
and Xi does not appear in any monomial of R. Observe
that for any j∈{1,…,n}, the degree of Xj in any monomial of Q is
at most dj−1. Let g and t be the functions associated to Q and R, respectively,
so f=xig+t. We must have t=0, otherwise t(α)=0 for
some α=(α1,…,αn)∈X, hence taking
α~=(α~1,…,α~n), with
α~j=αj for j∈{1,…,n}∖{i} and
α~i=0 we get xi(α~)=0 hence
f(α~)=0 but t(α~)=0, a contradiction.
Since R is the reduced polynomial associated to t we get R=0, and since
Q is the reduced polynomial of g we get degg=degQ=degf−1.
□
Lemma 2.8
Let h be a nonzero function in CX(d)
such that for some i∈{1,…,n} and some φ∈Aff\/(X) we have h=xi∘φ. Then, for α∈Fq,
we get that
h−α is X-linear if and only if α∈Ki.
Moreover, let f∈CX(d), f=0 and let α1,…,αs be distinct elements of Ki such that ZX(h−αj)⊂ZX(f) for all j=1,…,s, then there exists
g∈CX(d−s) such that
f=g⋅j=1∏s(h−αj).
**Proof: **
Assume that α∈Ki and consider the affine transformation
φ~:Fqn→Fqn given by φ~(α)=φ(α)−αei for all α∈Fqn, then one can easily
check that φ~∈Aff\/(X) and xi∘φ~=h−α. On the other hand, suppose that h−α is X-linear, then h−α must vanish on some point of X. From h=xi∘φ we get
that h(X)⊂Ki so we must have α∈Ki.
Since h−α1 is
X-linear
and ZX(h−α1)⊂ZX(f) then from Lemma
2.7 we get that f=g1(h−α1) with g1∈CX(d−1). If s=1 we’re done, if s≥2 then
from ZX(h−α2)⊂ZX(f) and the fact that ZX(h−α1)∩ZX(h−α2)=∅ we get that ZX(h−α2)⊂ZX(g1). From the hypothesis
and Lemma
2.7 we get that g1=g2(h−α2) with g2∈CX(d−2), this proves the statement in the case where s=2 and
if s>2 the assertion is proved after a finite number of similar
steps.
□
If G is X-affine and there exists
ψ∈Aff\/(n,Fq) and
1≤i1<⋯<ir≤n such that ψ(X)=X and
ψ(⟨ei1,…,eir⟩)=G
then
XG:=Xi1,…,ir.
The following results states an important property of the
support of functions.
Lemma 2.9
Let f∈CX(d) be a nonzero function and let S be its
support.
Then for every X-affine subspace G⊂Fqn
of dimension r, with r∈{1,…,n−1}, either S∩G=∅ or
∣S∩G∣≥δXG(d).
**Proof: **
Since G is an X-affine subspace of dimension r there exists
an affine transformation ψ:Fq→Fq
such that ψ(X)=X and G=ψ(V) where
V=⟨ei1,…,eir⟩. Observe that ψ establishes
a bijection between the points of V∩ψ−1(S) and G∩S, we also
have that ψ−1(S) is the support of the function f∘ψ∣X
which belongs to CX(d) because degf=deg(f∘ψ∣X). This shows that, for simplicity, we may assume that
G=⟨ei1,…,eir⟩. Suppose that S∩G=∅ and let P be the reduced polynomial associated to f, then
f
induces a nonzero function f~ defined over XG=Xi1,…,ir⊂Fqr
whose reduced polynomial is P~(Xi1,…,Xis) obtained from
P by making Xi=0 for all i∈{1,…,n}∖{i1,…,is}. Clearly degf~≤d so that f~∈CXG(d),
also ∣S∩G∣=∣f~∣ and as a consequence of Theorem 2.4
we get ∣f~∣≥δXG(d).
□
Observe, in the next result, that if S is the support of a
function then, from
the above result, it already has property (2).
Proposition 2.10
Let 1≤d<∑i=1n(di−1) and write
d=∑i=1k(di−1)+ℓ as in Theorem 2.4. Let S⊂X be a nonempty set and
assume that S has the following properties:
For every X-affine subspace G⊂Fqn
of dimension r, with r∈{0,…,n−1},
either S∩G=∅ or
∣S∩G∣≥δXG(d).
*Then there exists an affine subspace H⊂Fqn, of dimension
n−1 and a transformation ψ∈Aff\/(n,Fq) such that ψ(X)=X,
ψ(Vk+1)=H where Vk+1 is the Fq-vector space generated by
{e1,…,en}∖{ek+1} (so, in particular, H is
X-affine) and S∩H=∅.
*
**Proof: **
We proceed by induction on n. When n=1 we have k=0, and from the hypothesis we get that ∣S∣<(1+d11)(d1−ℓ)≤d1−d11, hence
∣S∣≤d1−1 and S⫋K1⊂Fq. A [math]-dimensional
X-affine subspace is just an element of K1, so it is enough to take H
as a point of K1∖S.
Assume now that the statement is true for all n<N, and let S⊂X⊂FqN as in the hypothesis. For α∈Kk+1 let
[TABLE]
If for some α∈Kk+1 we get S∩Gα=∅ then we’re done, so assume from now on that S∩Gα=∅ for all
α∈Kk+1. If k=N−1 we have δX(d)=dN−ℓ
and
[TABLE]
a contradiction which settles this case.
Now we consider the case where k≤N−2.
Since Gα is X-affine we have
∣S∩Gα∣≥δXk+1(d)=(dk+2−ℓ)dk+3⋯dN for every α∈Kk+1.
Thus
dk+1δXk+1(d)≤∣S∣<(1+dk+11)δX(d)
and from the formulas for δXk+1(d) and
δX(d) we get dk+1(dk+2−ℓ)<(1+dk+11)(dk+1−ℓ)dk+2.
Hence
[TABLE]
so that dk+2<dk+12. Assume that
Kk+1⊊Kk+2, since this is a field extension
we must have dk+12≤dk+2, a contradiction which settles the case
k≤N−2 and dk+1<dk+2.
The last case is when k≤N−2 and dk+1=dk+2, and now we will apply the induction hypothesis. To do that, for α∈Kk+1, we
consider the bijection ξα:Gα→FqN−1 which
acts on an N-tuple α∈Gα by deleting the (k+1)-th entry
(which is equal to α).
Observe that ξα establishes a bijection between affine subspaces of
FqN contained in Gα and affine subspaces of FqN−1.
Clearly Xk+1⊂FqN−1 and we want to show
that
ξα(S∩Gα) has property (2) of the statement (with
Xk+1 in place of X). For this, let L⊂FqN−1
be an
r-dimensional
Xk+1-affine subspace. Then for some ψ~∈Aff\/(N−1,Fq),
given by α~↦A~α~+β~, with
A~∈GL(N−1,Fq)
and β~∈FqN−1, we have
ψ~(Xk+1)=Xk+1 and ψ~(L)=⟨e~i1,…,e~ir⟩, where
{e~1,…,e~N−1} is the canonical basis for
FqN−1.
We claim that ξα−1(L) is an X-affine subspace contained in
Gα and to see that let A be the matrix obtained from A~ by
adding an N×1 column of zeros as the (k+1)-th column, an 1×N line of zeros as the (k+1)-th line and changing the 0 at position (k+1,k+1) to 1. Let β be the N×1 vector obtained from
β~ by adding the entry −α at position k+1.
Then, defining ψ:FqN→FqN by α↦Aα+β we get that ψ∈Aff\/(N,Fq), and it is easy to check
that ψ(X)=X and that ψ(ξα−1(L))=⟨ej1,…,ejr⟩, with {j1,…,jr}⊂{1,…,n}∖{k+1}, js=is whenever is<k+1, and js=is+1
whenever is≥k+1, for all s=1,…,r, so that {dj1,…,djr}={di1,…,dir}. To show that
ξα(S∩Gα) has property (2) of the statement, with
Xk+1 in place of X, we observe that
[TABLE]
Now we prove that there exists α∈Kk+1 such that ξα(S∩Gα) also has property (1), with Xk+1 in place of
X. Indeed, if for all α∈Kk+1 we have
[TABLE]
then from ∣ξα(S∩Gα)∣=∣S∩Gα∣ we get
∣S∣≥dk+1(1+dk+21)(dk+2−ℓ)dk+3⋯dN=(1+dk+11)δX(d) (because dk+1=dk+2) which contradicts property (1).
Thus, for some α∈Kk+1 we get that ξα(S∩Gα)⊂Xk+1⊂FqN−1 satisfies properties (1) and
(2), and from
the induction hypothesis there exists an Xk+1-affine subspace
L⊂FqN−1 of dimension N−2 and ψ~∈Aff\/(N−1,Fq) such
that
ψ~(Xk+1)=Xk+1,
ψ(L) is the subspace generated by {e~1,…,e~N−1}∖{e~k+1} and ξα(S∩Gα)∩L=∅. From what we did above we get that
ξα−1(L) is an (N−2)-dimensional X-affine subspace of FqN
and there exists ψ∈Aff\/(N,Fq) such that
ψ(X)=X, ψ(ξα−1(L)) is the subspace generated by
{e1,…,eN}∖{ek+1,ek+2},
and (S∩Gα)∩ξα−1(L)=S∩ξα−1(L)=∅.
Thus ψ(ξα−1(L)) is the subvector space defined by Xk+1=0 and Xk+2=0, and
let G(γ1,γ2) be the hyperplane defined by the equation γ1Xk+1+γ2Xk+2=0, where (γ1:γ2)∈P1(Kk+1), observe that G(γ1,γ2)∩G(γ1′,γ2′)=ψ(ξα−1(L)) whenever (γ1:γ2)=(γ1′:γ2′). One may easily check that for every (γ1:γ2)∈P1(Kk+1) there exists a linear transformation that takes G(γ1,γ2) onto the subspace defined by Xk+1=0, so that H(γ1,γ2):=ψ−1(G(γ1,γ2)) is an X-affine subspace of dimension N−1. We claim that for some (γ1:γ2)∈P1(Kk+1) we must have S∩H(γ1,γ2)=∅. Indeed, if this is not true, then, since
H(γ1,γ2)∩H(γ1′,γ2′)=ξα−1(L)
(for any distinct pair (γ1:γ2),(γ1′:γ2′),∈P1(Kk+1)) and S∩ξα−1(L)=∅ we get
[TABLE]
a contradiction with property (1) which, using dk+1=dk+2, states that
[TABLE]
□
The next result combines previous results and
gives a first
step in the direction of the main result.
Corollary 2.11
Let f be a nonzero function in CX(d) such that
∣f∣<(1+dk+11)δX(d), then f is a multiple of a
function h of degree 1 which is X-equivalent to xk+1.
**Proof: **
Let S be the support of f, from the hypothesis we have that S has property (1) in the statement of Proposition 2.10 and from Lemma
2.9 we get that S also has property (2). Thus, there exists
an affine subspace H⊂Fqn, of dimension
n−1 and a transformation ψ∈Aff\/(n,Fq) such that ψ(X)=X,
ψ(Vk+1)=H with
V_{k+1}=\left\{\mbox{{\boldmath\alpha}}\in\mathbb{F}_{q}^{n}\mid\alpha_{k+1}=0\right\} and
S∩H=∅.
Hence ψ−1(S)∩Vk+1=∅, and noting that
ψ−1(S) is the support of
the function f∘ψ∣X∈CX(d)
we get that
ZX(xk+1)⊂ZX(f∘ψ∣X).
From Lemma 2.7 there exists
g∈CX(d−1) such that
f∘ψ∣X=gxk+1, hence
f=(g∘ψ∣X−1)⋅(xk+1∘ψ∣X−1)
and we can take h=xk+1∘ψ∣X−1.
□
Recall that we write d=∑i=1k(di−1)+ℓ, with 0<ℓ≤dk+1−1 (and 0≤k<n).
Lemma 2.12
Let f be a nonzero function in CX(d), and let h∈CX(d)
be such that h=xj∘φ, where j∈{1,…,n} and
φ∈Aff\/(X). If m is the number of α∈Kj such that
ZX(h−α)⊂ZX(f) then m≤d and
∣f∣≥(dj−m)δXj(d−m).
**Proof: **
Let f~=f∘φ−1, then f~∈CX(d), f=f~∘φ and
φ
establishes a bijection between the sets ZX(h−α) and
ZX(xj−α) for all α∈Kj, moreover we get that
ZX(h−α)⊂ZX(f) if and only if
ZX(xj−α)⊂ZX(f~). This shows that,
in the statement, we can take φ to be the identity transformation,
without loss of generality. Let α1,…,αm be the set of
elements α∈Kj such that ZX(xj−α)⊂ZX(f), from
Lemma 2.8 we get that f=g⋅i=1∏m(xj−αi), with g∈CX(d−m), and in particular m≤d.
Observe that for all α∈Kj\{α1,…,αm}
we get gα(j)=0, so that
[TABLE]
□
For our purposes it is important to know when a function
f∈CX(d) has minimal weight, i.e. when ∣f∣=δX(d). Taking into account the previous result, and using
its notation, we
investigate when (dj−m)δXj(d−m)≥δX(d) holds, and under which conditions equality holds.
Lemma 2.13
Let 1≤j≤k+1. If dj>dk+1−ℓ,
for 0<m<ℓ+(dj−dk+1) we have
[TABLE]
**Proof: **
Observe that we may write
[TABLE]
and note that
ℓ−m+dj−dk+1≤ℓ−m<ℓ<dk+1≤dk+2
so that δXj(d−m)=(dk+2−(ℓ−m+dj−dk+1))i=k+3∏ndi.
From δX(d)=(dk+1−ℓ)∏i=k+2ndi and
[TABLE]
we get
[TABLE]
□
Lemma 2.14
Let 1≤j≤k.
For 0<m<dj we have
(dj−m)δXj(d−m)≥δX(d), with equality if and only if
m=dj−1 or
both dj>dk+1−ℓ and m=ℓ+dj−dk+1.
**Proof: ** By Lemma 2.13, we may consider
max{1,ℓ+(dj−dk+1)}≤m≤dj−1.
In this case we write
[TABLE]
and we observe that 0<ℓ+dj−1−m≤dk+1−1,
so that δXj(d−m)=(dk+1−(ℓ+dj−1−m))∏i=k+2ndi. From
[TABLE]
we get
[TABLE]
with equality if and only if
m=dj−1 or
both ℓ+dj−dk+1>0 and m=ℓ+dj−dk+1.
□
Lemma 2.15
For 0<m<dk+1 we have
(dk+1−m)δXk+1(d−m)≥δX(d), with equality if and only if
m=ℓ or both m=dk+1−1 and dk≥dk+1−ℓ.
**Proof: **
By Lemma 2.13, we may consider
ℓ≤m≤dk+1−1.
In this case
we write
[TABLE]
where
[TABLE]
hence ℓ≤dk+1−1.
We want to prove that
[TABLE]
and from k≥k+1 we get k+1∈{k+2,…,n}, so that
[TABLE]
Thus we must verify that
[TABLE]
Let M be the function defined by
[TABLE]
where ai is a nonnegative integer less than di, for i=k+1,…,k+1, and
ak+1+⋯+ak+1≤ℓ+m.
We have studied this function in [6] and [9].
From ℓ+m=∑i=k+1k(di−1)+ℓ and
[6, Lemma 2.1] we get dk+1−ℓ is the minimum of M so
that inequality (2.1) holds. To find out when (2.1)
is an equality we will use
results from [9], and for that we define a tuple
(ak+1,…,ak+1) to be
normalized if whenever di−1<di=⋯=di+s<di+s+1
we have ai≥ai+1≥⋯≥ai+s.
From [9, Lemma 2.2] we get that the normalized tuples which
reach the minimum of M are exactly of the type:
Type 2 is only possible if
dk+1−ℓ≤dj<dk+1, we also note that
if ℓ=dk+1−1 then types 1 and 2 are the same so
we also assume in type 2 that ℓ<dk+1−1.
Thus we have equality in (2.1) if and only if the tuple
(ℓ,0,…,0,m), when normalized, is equal to (dk+1−1,…dk−1,ℓ) or
(dk+1−1,…,dj−(dk+1−ℓ),…,dk+1−1).
In the first case, since we don’t have any zero entries in
(dk+1−1,…dk−1,ℓ) we must have
k+1=k and the tuple (ℓ,m) when normalized is
equal to (dk−1,ℓ),
thus we must have either (ℓ,m)=(dk−1,ℓ) or (m,ℓ)=(dk−1,ℓ).
If (ℓ,m)=(dk−1,ℓ) then m=ℓ, and if (m,ℓ)=(dk−1,ℓ), then m=dk−1 and
from the
definition of normalized tuple we also must
have dk=dk+1.
On the other
hand if m=ℓ, from
d=∑i=1k(di−1)+ℓ
we get
[TABLE]
so we must have k=k−1 and ℓ=dk−1,
hence (ℓ,m)=(dk−1,ℓ).
And if m=dk−1=dk+1−1, from
d=∑i=1k(di−1)+ℓ
we get
[TABLE]
so we must have k=k−1 and ℓ=ℓ,
hence (m,ℓ)=(dk−1,ℓ).
The upshot of this is that
(ℓ,m) when normalized is
equal to (dk−1,ℓ)
if and only if
m=ℓ
or both m=dk+1−1
and dk=dk+1.
In the second case, since we may have at most only one zero entry in
[TABLE]
we must have
k+1=k
or k+2=k.
If k+1=k
then the above tuple is an ordered pair,
and since it is a type 2 tuple we must
have that dk<dk+1 and that this pair is (dk−(dk+1−ℓ),dk+1−1). Since dk<dk+1 the tuple
(ℓ,m) is already
normalized, and if (ℓ,m)=(dk−(dk+1−ℓ),dk+1−1)
then m=dk+1−1 and ℓ=dk−(dk+1−ℓ) so that
dk−(dk+1−ℓ)>0. On the other
hand if m=dk+1−1 and dk−(dk+1−ℓ)>0, from
d=∑i=1k(di−1)+ℓ
we get
[TABLE]
so we must have k=k−1 and ℓ=dk−(dk+1−ℓ), hence (ℓ,m)=(dk−(dk+1−ℓ),dk+1−1).
If k+2=k then we must have dk<dk+1 so the
tuple (ℓ,0,m) is already normalized, and if
(ℓ,0,m)=(dk−1−1,dk−(dk+1−ℓ),dk+1−1) then
dk=dk+1−ℓ and m=dk+1−1. On the other hand if
m=dk+1−1 and dk−(dk+1−ℓ)=0 from
d=∑i=1k(di−1)+ℓ
we get
[TABLE]
so we must have k=k−2 and ℓ=dk−1−1, hence (ℓ,0,m)=(dk−1−1,dk−(dk+1−ℓ),dk+1−1).
Thus we have equality in (2.1) if and only if
m=ℓ or both m=dk+1−1 and dk≥dk+1−ℓ.
□
Proposition 2.16
*Let f be a nonzero function in CX(d), and let h∈CX(d)
be such that h=xj∘φ, where
φ∈Aff\/(X)
and 1≤j≤k+1.
Let m>0 be the number of α∈Kj
such that
ZX(h−α)⊂ZX(f).
Let g=f∘φ−1,
then
∣f∣=δX(d) if and only if
∣gα(j)∣=δXj(d−m)
whenever gα(j)=0, with
α∈Kj
and m satisfies one of the following:
If 1≤j≤k then
m=dj−1 or
both m=ℓ+dj−dk+1 and dj>dk+1−ℓ.
If j=k+1 then
m=ℓ or both m=dk+1−1 and dk≥dk+1−ℓ.*
**Proof: **
Let j∈{1,…,k+1}.
As in the beginning of the proof of Lemma 2.12 we may assume that
φ is the identity, so that h=x_{{\color[rgb]{1,0,1}j}}. From the proof of Lemma
2.12 we get
[TABLE]
and equality holds if and only if
|f_{\alpha}^{({\color[rgb]{1,0,1}j})}|=\delta_{\mathcal{X}_{\widehat{{\color[rgb]{1,0,1}j}}}}(d-m)
whenever f_{\alpha}^{({\color[rgb]{1,0,1}j})}\neq 0, with
α∈Kj.
From the two previous Lemmas we know that
δXj(d−m)≥δX(d) and
we also know when equality holds.
□
As mentioned in the paragraph preceding Lemma 2.13 we
are investigating
when (dj−m)δXj(d−m)≥δX(d) holds, and under which conditions equality holds.
Now we treat the case where m=0.
Lemma 2.17
Let 1≤j≤k+1. We have
[TABLE]
with equality if and only if dj=dk+1−ℓ or dj=dk+2.
**Proof: **
If dj≤dk+1−ℓ we may write
[TABLE]
so that δXj(d)=(dk+1−(ℓ+dj−1))i=k+2∏ndi.
From
[TABLE]
we get
[TABLE]
with equality if and only if dj=dk+1−ℓ.
If dj>dk+1−ℓ we may write
[TABLE]
so that δXj(d)=(dk+2−(ℓ+dj−dk+1))i=k+3∏ndi.
From
[TABLE]
we get
[TABLE]
with equality if and only if dj=dk+2.
□
Proposition 2.18
Let f∈CX(d) and suppose that
dj<dk+1−ℓ
for some 1≤j≤k. If ∣f∣=δX(d) then
the number of α∈Kj
such that
ZX(xj−α)⊂ZX(f)
is dj−1 and for α∈Kj such that
fα(j)=0 we have
∣fα(j)∣=∣f∣=δX(d)=δXj(d−(dj−1)).
**Proof: **
Let m be the number of α∈Kj such that
ZX(xj−α)⊂ZX(f).
By Lemma 2.12 we have
∣f∣≥(dj−m)δXj(d−m).
As dj<dk+1−ℓ and ∣f∣=δX(d),
from Lemma 2.17 we get m>0 and
from Lemma 2.14 we have
m=dj−1 and
δXj(d−(dj−1))=δX(d).
We conclude by observing that
for the only element α∈Kj such that
fα(j)=0 we have
∣f∣=∣fα(j)∣.
□
3 Main results
As in the preceding section we continue to write d as in the statement of
Theorem 2.4, namely d=∑i=1k(di−1)+ℓ, with 0<ℓ≤dk+1−1 (and 0≤k<n).
The next result describes the minimal weight codewords of affine cartesian
codes for the lowest range of values of d, meaning the case when k=0.
Proposition 3.1
Let 1≤d<d1, the minimal weight codewords of CX(d)
are X-equivalent to the functions
[TABLE]
with σ∈Fq∗, αi∈K1 and
αi=αj for 1≤i=j≤ℓ.
**Proof: **
Let f∈CX(d) be such that ∣f∣=δX(d).
From Corollary 2.11 we get that f has a degree one factor
h which is X-equivalent to x1.
Let m≤d=ℓ be the number of distinct elements α∈K1 such
that
ZX(x1−α)⊂ZX(f).
As m≤d, from
Proposition 2.16 (2) we have ∣f∣=δX(d) if and only if
m=ℓ.
Now the result follows from Lemma 2.8.
□
Now we
describe the minimal weight codewords for the case where
ℓ=dk+1−1 and 0≤k<n.
Proposition 3.2
The minimal weight codewords of CX(d), for
d=i=1∑k+1(di−1), 0≤k<n,
are X-equivalent to the functions of the form
[TABLE]
with σ∈Fq∗.
**Proof: **
We will prove the result by induction on k, and we note that
the case k=0 is already covered by Proposition 3.1, so
we assume k>0 and that the result holds for k−1.
Let f∈CX(d) be such that ∣f∣=δX(d).
From Corollary 2.11 we get that f has a degree one factor
h such that
h=xk+1∘φ, for some
φ∈Aff\/(X).
Let m>0 be the number of α∈Kk+1
such that
ZX(h−α)⊂ZX(f).
From Proposition 2.16 (2) we get
m=dk+1−1 (since ℓ=dk+1).
In particular fα(k+1)=0 for only one value of
α∈Kk+1, and without loss of generality, we may assume
that φ is the identity transformation and α=0.
Hence, from Lemma 2.8 we get
[TABLE]
for some g∈CX(d−(dk+1−1)).
Let P and Q be the reduced polynomials associated to f and g,
respectively. Then
[TABLE]
is in the ideal IX=(X1d1−X1,…,Xndn−Xn). Write
Q=Q1+Xk+1Q2, where Q1 and Q2 are reduced polynomials
and
Xk+1 does not appear in any monomial of
Q1. Then P−(1−Xk+1dk+1−1)Q1
is in IX, and
writing g1 for the function associated to Q1, we get
f=(1−xk+1dk+1−1)g1. Since
deg(Q1)=d−(dk+1−1) we have
g1∈CXk+1(d−(dk+1−1)), and from
d−(dk+1−1)=i=1∑k(di−1),
δX(d)=δXk+1(d−(dk+1−1))
and ∣f∣=∣g1∣ we see that g1 is a minimal weight codeword of CXk+1(d−(dk+1−1))
so we may apply
the induction hypothesis to g1, which concludes the proof of the
Proposition.
□
Lemma 3.3
*Let d=i=1∑k+1(di−1), 0≤k<n
and let g∈CX(d) be
such that ∣g∣=δX(d). Let
h∈CX(d−s), where 0<s≤d1−1.
If f=g+h then ∣f∣≥(s+1)δX(d) or
∣f∣=sδX(d).
From the above Proposition there exists
φ∈Aff\/(X)
such that g∘φ−1=σ∏i=1k+1(1−xidi−1),
with σ∈Fq∗.
Let f=f∘φ−1,
if
∣f∣=sδX(d)
then, for each 1≤j≤k+1,
the number of elements α∈Kj
such that
ZX(xj−α)⊂ZX(f)
is either
dj−1 or dj−s.
*
**Proof: **
As in the proof of Lemma 2.12 we may assume that φ is the
identity transformation, so we identify f with f and g∘φ−1 with g.
We will make an induction on n.
If n=1 then k=0, d=d1−1, j=1 and ∣g∣=1. Since
h∈CX(d1−(s+1)) and ∣K1∣=d1 we have
∣h∣≥s+1, and a fortiori
∣f∣≥s.
If ∣f∣=s then there are d1−s elements α∈K1 such that
ZX(x1−α)⊂ZX(f).
We will do an induction on n, so we assume that the result is true for n−1 and let j∈{1,…,k+1}.
From the hypothesis on g
and using the notation established in Definition 2.3
we may write
g=(1−xjdj−1)g0(j), where
g0(j)∈CXj(d−(dj−1)) is a function of minimal weight.
We also write
[TABLE]
Let’s assume that h0(j)=0, since
δXj(d−(dj−1))=∏i=k+2ndi=δX(d) and
δX(d−s)=(dk+1−(dk+1−1−s))∏i=k+2ndi
we get
[TABLE]
which proves the Lemma in this case.
Assume now that h0(j)=0, and let
m
be the number of elements α∈Kj
such that
ZX(xj−α)⊂ZX(h).
Let’s assume that
f0(j)=0, in this case
m is also the number of elements α∈Kj
such that
ZX(xj−α)⊂ZX(f)
since g=(1−xjdj−1)g0(j).
If m=dj−1 then from Lemma 2.8 we have h=(1−xjdj−1)h, with h∈CX(d−(dj−1)−s).
As in the end of the proof of Proposition 3.2 we may assume
that h∈CXj(d−(dj−1)−s) so that
h=h0(j). We now apply the induction hypothesis
to f0(j)=g0(j)+h0(j) and we get
[TABLE]
If ∣f0(j)∣=sδXj(d−(dj−1)) then,
from the induction hypothesis, we get that for i=j there are di−1
or di−s values of α∈Ki such that ZXj(xj−α)⊂ZXj(f0(j))
and from f=g+h=(1−xjdj−1)g0(j)+(1−xjdj−1)h0(j)=(1−xjdj−1)f0(j) we get the statement of the Lemma for the case
where h0(j)=0, f0(j)=0 and m=dj−1. Still assuming that
h0(j)=0 and f0(j)=0, we now treat the case where
0≤m<dj−1. From Lemma 2.8 we know that
h=∏i=1m(xj−αi)h, where α1,…,αm∈Kj∗ and h∈CX(d−s−m) so h0(j)=βh0(j),
with β∈Kj∗ and we get h0(j)∈CXj(d−s−m) (note that we also get
hα(j)∈CXj(d−s−m) for all α∈Kj∗∖{α1,…,αm}). Thus, from
f0(j)=g0(j)+h0(j) we get that the degree of f0(j) is at most
max{d−(dj−1),d−(s+m)}. We now consider the following cases.
Assume that dj−1<s+m, so we have that the degree of
f0(j)=g0(j)+h0(j) is at most d−(dj−1).
From h0(j)∈CXj(d−(s+m)) and writing
d−(s+m)=d−(dj−1)−(s+m−(dj−1)), we observe that
0<s+m−(dj−1)=s−(dj−1−m)<d1−1, so we may
apply the induction hypothesis on f0(j) and we get, in
particular, that ∣f0(j)∣≥(s+m−(dj−1))δXj(d−(dj−1))=(s+m+1−dj)δX(d).
From ∣f∣=∣f0(j)∣+∑α∈Kj∗∣hα(j)∣
and the fact that ∣hα(j)∣≥δXj(d−(s+m)) for all α∈Kj∗∖{α1,…,αm} we get
∣f∣≥(s+m+1−dj)δX(d)+(dj−m−1)δXj(d−(s+m)).
We claim that
[TABLE]
and to prove this fact we have to consider the cases where j≤k and
j=k+1. We will do the case j≤k since the proof of the other case is
similar to this one. So let j≤k, then
[TABLE]
so
[TABLE]
Thus
[TABLE]
which proves the Lemma in this case.
2. 2.
Assume now that dj−1≥s+m, in this case
deg(g0(j)+h0(j))≤d−(s+m), and we have
[TABLE]
We now consider the case f0(j)=g0(j)+h0(j)=0, so in particular
degh0(j)=degg0(j)=d−(dj−1). On the other hand degh0(j)≤d−(s+m), so we get s+m≤dj−1.
Let λ=((−1)m∏i=1mαi)−1, then, using Lemma 2.8 we get
that there exists a function h such that
[TABLE]
Observe that deg(h−λ(∏i=1m(xj−αi))h0(j))≤d−s hence
degh≤d−(s+m+1).
Assume that s+m<dj−1 hence s+m+1≤dj−1.
From
[TABLE]
Recall that
[TABLE]
and hα(j)=λ(∏i=1m(α−αi))(h0(j)+αhα(j))=0 for dj−(m+1) values of α∈Kj∗. Observe that
degh0(j)=d−(dj−1)≤d−(s+m+1) and
since degh≤d−(s+m+1) we get
deghα(j)≤d−(s+m+1), when hα(j)=0. Then
[TABLE]
If s+m=dj−1 then deghα(j)=d−(dj−1) whenever
α∈Kj∗ and hα(j)=0. In this case
[TABLE]
and equality holds if and only if ∣fα(j)∣=∣hα(j)∣=δXj(d−(dj−1)),
for all fα(j)=0. Observe that in this case the number of elements
α∈Kj
such that
ZX(xj−α)⊂ZX(f)
is
m+1=dj−s.
Still under the assumption that s+m=dj−1 we must prove that
if ∣f∣>sδX(d) then
∣f∣≥(s+1)δX(d). From the above reasoning we know that if
∣f∣>sδX(d) then there exists
α∈Kj∗ such that hα(j)=0 and
∣hα(j)∣>δXj(d−(dj−1))=δX(d). We recall that
[TABLE]
that h0(j)=−g0(j) is a function, or codeword, of minimal
weight in
CXj(d−(dj−1)) and that
deg(hα(j))≤d−(s+m+1)=d−(dj−1)−1.
From the induction hypothesis, with s=1, we get from
∣hα(j)∣>δXj(d−(dj−1))
that
∣hα(j)∣≥2δXj(d−(dj−1)).
Hence, from ∣f∣=∑α∈Kj∗∣hα(j)∣ we get
[TABLE]
which completes the proof of the Lemma.
□
Lemma 3.4
Let f∈CX(d), where
d=i=2∑k+1(di−1), 1≤k<n. If
there exist α1,α2∈K1, α1=α2,
∣fα1(1)∣=∣fα2(1)∣=δX1(d) then there
exists φ∈Aff\/(X) such that x1=x1∘φ
and
gα1(1)=gα2(1),
where g=f∘φ.
**Proof: **
From Proposition 3.2 we may assume without loss of generality that
[TABLE]
with σ∈Fq∗.
Since f∈CX(d) there exists
f^∈CX(d−1) such that
f=fα1(1)+(x1−α1)f^
so that
fα2(1)=fα1(1)+(α2−α1)f^α2(1). Since
∣fα2(1)∣=δX1(d),
we get from Lemma 3.3 (with s=1) that
for each 2≤j≤k+1 the number of elements α∈Kj such that
ZX1(xj−α)⊂ZX1(fα2(1))
is
dj−1. Thus for each 2≤j≤k+1 there exists
βj∈Kj such that fα2(1) is a multiple of
∏α∈Kj∖{βj}(xj−α). From the equality of
the reduced polynomials
[TABLE]
we get, by successively applications of Lemma 2.8, that
[TABLE]
for some τ∈Fq∗.
Observe that from
(α2−α1)f^α2(1)=fα2(1)−fα1(1)
and f^∈CX(d−1)
we must have τ=σ.
If βj=0 for all 2≤j≤k+1 then
fα1(1)=fα2(1). Otherwise
consider a function
φ∈Aff\/(X) such that x1∘φ=x1 and
[TABLE]
for all 2≤j≤k+1.
Let
g=f∘φ, if x1=α1 then
xj∘φ=xj, and if
x1=α2 then
xj∘φ=xj+βj for all
2≤j≤k+1. Thus
[TABLE]
and
[TABLE]
hence
gα1(1)=gα2(1).
□
Now we prove the main result of this paper, which generalizes the theorem by
Delsarte,
Goethals and Mac Williams on minimal weight codewords of GRMq(d,n) to
the minimal weight codewords of CX(d).
Theorem 3.5
Let
d=i=1∑k(di−1)+ℓ, 0≤k<n and
0<ℓ≤dk+1−1,
the minimal weight codewords of
CX(d)
are X-equivalent to the functions of the form
[TABLE]
for some 1≤j≤k+1 such that dk+1−ℓ≤dj,
where 0=σ∈Fq and α1,…,αdj−(dk+1−ℓ)
are disticnt elements of Kj (if dj=dk+1−ℓ we take the second product as being equal to 1).
**Proof: **
If k=0 the d<d1 and the result follows from Proposition 3.1.
We will do an induction on k, so let’s assume that the result holds for k−1.
If ℓ=dk+1−1, then the result
follows from
Proposition 3.2.
Let ℓ<dk+1−1 and let f∈CX(d)
be a minimal weight codeword, i.e. ∣f∣=δX(d).
From Corollary 2.11f has a factor which is X-equivalent
to xk+1. Let 1≤j≤k+1 be least integer such that
f has a factor which is
X-equivalent to xj and
and let’s assume without loss of generality that xj−α is a factor of f for some α∈Kj. Let
m>0
be the number of elements of α∈Kj
such that
ZX(xj−α)⊂ZX(f).
From Proposition 2.16 we get m=dj−1 or
m=dj−(dk+1−ℓ).
If m=dj−1 then, after applying an X-affine transformation if necessary, we write
[TABLE]
for some g∈CX(d−(dj−1)), and as in the
proof of Proposition 3.2 we show that actually
we may write f as
[TABLE]
with g1∈CXj(d−(dj−1)).
In the case where 1≤j≤k,
since m=dj−1 we get from Lemma 2.14 that
δX(d)=δXj(d−(dj−1))
and from ∣f∣=∣g1∣ we see that g1 is a minimal weight codeword of CXj(d−(dj−1)), then
we may apply the induction hypothesis to get the result.
In the case where j=k+1, from Proposition 2.16 we also get
dk−(dk+1−ℓ)≥0 (besides m=dk+1−1) so from
Lemma 2.15 we get δX(d)=δXk+1(d−(dk+1−1))
and from ∣f∣=∣g1∣ we see that g1 is a minimal weight codeword of CXk+1(d−(dk+1−1)). Writing d−(dk+1−1)=∑j=1k−1(dj−1)+(dk−(dk+1−ℓ)) we see that, as above, we can apply the
induction hypothesis to g1, either because dk−(dk+1−ℓ)>0 or
because we get the result from Proposition
3.2 if dk=dk+1−ℓ.
Now we assume that
m=dj−(dk+1−ℓ)<dj−1. From
Proposition 2.16
we see that there are dk+1−ℓ elements in
Kj (say, β1,…,βdk+1−ℓ) such that
for all i∈{1,…,dk+1−ℓ} we get
∣fβi(j)∣=δXj(d),
with
[TABLE]
while ∣fβi(j)∣=0 for the other elements of Kj (say, i∈{dk+1−ℓ+1,…,dj}).
We treat first the case j=1. From Lemma 3.4, there exists
ψ∈Aff\/(X) such that
x1=x1∘ψ,
and gβ1(1)=gβ2(1), where g=f∘ψ,
and without loss of generality we assume that f=g. Observe that
ZX(xi−βi)⊂ZX(f−fβ1(1))=ZX(f−fβ2(1)) for i=1,2, so from Lemma
2.8 we may write
[TABLE]
with h∈CX(d−2).
If dk+1−ℓ=2, then from
fβ1(1)=fβ2(1) and equation
(3.1)
we may write
[TABLE]
and the result follows from applying Proposition 3.2 to
fβ1(1)∈CX1(d).
If dk+1−ℓ>2 then for all
2<t≤dk+1−ℓ we get
[TABLE]
If hβt(1)=0 then from Lemma 3.3 (taking s=2),
we get ∣fβt(1)∣≥2δX1(d), a contradiction.
Hence
fβ1(1)=fβt(1) for all
1≤t≤dk+1−ℓ, and from equation (3.1) we may write
[TABLE]
with fβ1(1)∈CX1(d).
Again, the result follows from applying Proposition 3.2 to
fβ1(1), which concludes the case j=1.
Assume now that j>1 and
let X1,j:=K2×⋯×Kj−1×Kj+1×⋯×Kn. Then for all α∈K1 we get
ZX(x1−α)⊂ZX(f)
and from
Proposition 2.18 we get
d1≥dk+1−ℓ.
From equation (3.1) we get
∣fβt(j)∣=∣fβt(j)∣,
so Proposition 2.16 implies
∣fβt(j)∣=δXj(d) for all t=1,…,dk+1−ℓ.
Thus, in particular,
fβ1(j) is Xj-equivalent
to a function of the form (1−x1d1−1)g1, where
g1∈CX1,ji=2,i=j∑k+1(di−1),
and ∣g1∣=δX1,j(∑i=2,i=jk+1(di−1)), so we may assume
[TABLE]
Using Lemma 2.7 there exists h∈CX(d−1) such that
f=fβ1(j)+(xj−β1)h, and evaluating both sides at βt, with t∈{2,…,dk+1−ℓ}, we get
fβt(j)=fβ1(j)+(βj−β1)hβt(j).
We now may apply Lemma 3.3 (replacing f by fβt(j), g by fβ1(j), h by
(βj−β1)hβt(j)), and using that
∣fβt(j)∣=δXj(d) we may conclude that there are d1−1 elements α in K1 such that
ZXj(x1−α)⊂ZXj(fβt(j)).
From Lemma 2.8, for every 1≤t≤dk+1−ℓ, there exists
αt∈K1 such that
[TABLE]
(here we are using that ((x1−αt)d1−1−1)(x1−αt)=x1d1−x1)
where, as in Proposition 3.2,
gt∈CX1,j
is a minimal weight function of degree
i=2,i=j∑k+1(di−1).
Note that from (3.2) we get α1=0. We also note that if there exists α∈K1, distinct from αt for all t∈{1,…,dk+1−ℓ} then all functions
fβt(j)
vanish in x1=α, hence
ZX(x1−α)⊂ZX(f)⊂ZX(f),
a contradiction with the assumption j>1.
Thus
for all α∈K1 there exists 1≤t≤dk+1−ℓ
such that α=αt, hence
d1≤dk+1−ℓ and a fortiori d1=dk+1−ℓ.
For each t∈{1,…,d1} let
[TABLE]
and let
[TABLE]
Clearly, for d1<t≤dj, from the definition of u and (3.1) we get uβt(j)=0=fβt(j). For t∈{1,…,d1} we get
[TABLE]
Thus we conclude that u=f. Letting x1=αt,
for all 1≤t≤d1 we get
[TABLE]
Observe that
ht(xj)s=d1+1∏dj(xj−βs) does not vanish only when
xj=βt, so ∣fαt(1)∣=∣gt∣.
From
[TABLE]
and
[TABLE]
we get
[TABLE]
Thus we get f∈CX(d), where
d=i=2∑k+1(di−1) and
∣fα1(1)∣=∣fα2(1)∣=δX1(d).
From Lemma 3.4, there exists
θ∈Aff\/(X) such that x1=x1∘θ
and fα1(1)=fα2(1), where f=f∘θ,
and without loss of generality we assume that f=f. Observe that
ZX(x1−αi)⊂ZX(f−fα1(1))=ZX(f−fα2(1)) for i=1,2, so from Lemma
2.8 we may write
[TABLE]
with f∈CX(d−2).
If d1=2, then f=fα1(1). If d1>2 then for
all t∈{3,…,d1} we get
fαt(1)=fα1(1)+(αt−α1)(αt−α2)fαt(1).
If fαt(1)=0 then from
Lemma 3.3 (taking s=2),
we get ∣fαt(1)∣≥2δX1(d), a contradiction.
Hence we must have
fαt(1)=fα1(1) for all
1≤t≤d1
and
the result follows from applying Proposition 3.2 to
f=fα1(1)∈CX1(d).
□
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