In this section, we will denote by \({\mathbb M}_{m\times n}({\mathbb F}_q)\), or simply by \({\mathbb M}\) the space of all \(m\times n \) matrices with entries in the finite field \({\mathbb F}_q\). Note that \({\mathbb M}\) is a vector space over \({\mathbb F}_q\) of dimension mn. As stated in the Introduction, by a Delsarte rank metric code, or simply a Delsarte code, we mean a \({\mathbb F}_q\)-linear subspace of \({\mathbb M}\). We denote by \(\dim _{{\mathbb F}_q} C\), or simply \(\dim C\), the dimension of a Delsarte code C.
Following Shiromoto [19], we now associate to a Delsarte code C, (i) a family of subcodes of C indexed by subspaces of \(E={\mathbb F}_q^n\), and (ii) a (q, m)-polymatroid.
Definition 19
Let C be a Delsarte code.
-
(i)
Given any \(X\in \Sigma (E)\), we define C(X) to be the subspace of C consisting of all matrices in C whose row space is contained in X.
-
(ii)
By \(\rho ^{ }_C\) we denote the function from \(\Sigma (E)\) to \({\mathbf {N}_0}\) defined by
$$\begin{aligned} \rho ^{ }_C(X)=\dim _{{\mathbb {F}}_q}C-\dim _{{\mathbb {F}}_q}C(X^{\perp }) \quad \text { for } X \in \Sigma (E). \end{aligned}$$
Further, by P(C) we denote the (q, m)-polymatroid \((E, \rho ^{ }_C)\).
Remark 20
It is shown in [19, Proposition 3] that \(P(C)=(E, \rho ^{ }_C)\) is indeed a (q, m)-polymatroid. Note also that the conullity function \(\nu ^*_{C}\) of P(C) is given by
$$\begin{aligned} \nu ^*_C (X) = \dim C(X) \quad \text {for } X \in \Sigma (E). \end{aligned}$$
(5)
Demi-polymatroids associated to flags of Delsarte codes
Motivated by the work in [3, 4] on demi-matroids, we consider the following natural and useful extension of the notion defined in part (ii) of Definition 19.
Definition 21
By a flag of Delsarte codes we shall mean a tuple \(\mathsf {F} = (C_1, \dots , C_s)\) of subspaces of \({\mathbb M}= {\mathbb M}_{m\times n}({\mathbb F}_q)\) such that \(C_s \subseteq C_{s-1} \subseteq \cdots \subseteq C_1\). The rank function associated to a flag \(\mathsf {F} = (C_1, \dots , C_s)\) is the map \(\rho _{_{{\mathsf {F}}}}: \Sigma (E) \rightarrow {\mathbb {Z}}\) given by
$$\begin{aligned} \rho _{_{{\mathsf {F}}}}(X) = \sum _{i=1}^s(-1)^{i+1} \rho ^{ }_{C_i}(X) \quad \text {for } X\in \Sigma (E). \end{aligned}$$
(6)
The pair \((E, \rho _{_{{\mathsf {F}}}})\) is a (q, m)-demi-polymatroid, and it is denoted by \(P(\mathsf {F})\).
We will presently show that \(P(\mathsf {F})= (E, \rho _{_{{\mathsf {F}}}})\) is indeed a (q, m)-demi-polymatroid for any flag \(\mathsf {F}\) of Delsarte codes. First, we need a couple of auxiliary results.
Lemma 22
Let \(C_1, C_2\) be Delsarte codes in \({\mathbb M}= {\mathbb M}_{m\times n}({\mathbb F}_q)\) such that \(C_2\subseteq C_1\) and let \(\rho _i = \rho ^{ }_{C_i}\) for \(i=1, 2\). Then \(\rho _2(X) \le \rho _1(X)\) for all \(X\in \Sigma (E)\).
Proof
Note that the row space of any \(A\in {\mathbb M}\) consists of vectors \(\mathbf {v}A\) as \(\mathbf {v}\) varies over \({\mathbb F}_q^m\) (elements of \({\mathbb F}_q^m\) and \({\mathbb F}_q^n\) are thought of as row vectors); also note that \((\mathbf {v}A) \cdot \mathbf {u} = \mathbf {u}(\mathbf {v}A)^t = \mathbf {u}(A^t\mathbf {v}^t) \) for any \(\mathbf {u}\in {\mathbb F}_q^n\). Now let \(X\in \Sigma (E)\) and define
$$\begin{aligned} U = \{A \in {\mathbb M}_{m\times n}({\mathbb F}_q): \mathbf {u}A^t = \mathbf {0} \text { for all } \mathbf {u} \in X \}. \end{aligned}$$
Clearly, U is a subspace of \({\mathbb M}\) and \(C(X^\perp ) = C\cap U\) for any Delsarte code C. Also,
$$\begin{aligned} \frac{C_2}{C_2\cap U} \simeq \frac{C_2+U}{U} \subseteq \frac{C_1+U}{U} \simeq \frac{C_1}{C_1\cap U}. \end{aligned}$$
Hence \(\dim C_2 - \dim C_2 \cap U \le \dim C_1 - \dim C_1 \cap U\), which yields \(\rho _2(X) \le \rho _1(X)\). \(\square \)
Lemma 23
Let \(C_1, C_2\) be Delsarte codes in \({\mathbb M}= {\mathbb M}_{m\times n}({\mathbb F}_q)\) such that \(C_2\subseteq C_1\) and let \(X, Y\in \Sigma (E)\) be such that \(X\subseteq Y\). Then
$$\begin{aligned} \dim C_1(X) - \dim C_2(X) \le \dim C_1(Y) - \dim C_2(Y). \end{aligned}$$
Proof
Since \(C_2\subseteq C_1\) and \(X\subseteq Y\), it is clear from Definition 19 (i) that
$$\begin{aligned} C_1(X)\cap C_2(Y) = C_2(X) \quad \text {and} \quad C_1(X)+C_2(Y) \subseteq C_1(Y). \end{aligned}$$
Consequently, \(\dim C_1(X) + \dim C_2(Y)- \dim C_2(X) \le \dim C_1(Y)\), as desired. \(\square \)
Theorem 24
Let \(\mathsf {F} = (C_1, \dots , C_s)\) be a flag of Delsarte codes in \({\mathbb M}\) and let \(\rho _{_{{\mathsf {F}}}}\) be the rank function associated to \(\mathsf {F}\). Then \(P(\mathsf {F})=(E,\rho _{_{{\mathsf {F}}}})\) is a (q, m)-demi-polymatroid.
Proof
Let \(\rho _j :=\rho ^{ }_{C_j}\) for \(1\le j \le s\). First, suppose s is even, say \(s=2t\). Then for any \(X\in \Sigma (E)\),
$$\begin{aligned} \rho _{_{{\mathsf {F}}}}(X) = \sum _{i=1}^t \big ( \rho ^{ }_{2i-1}(X) - \rho ^{ }_{2i}(X)\big ). \end{aligned}$$
(7)
By Lemma 22, each summand is nonnegative, and so \(\rho _{_{{\mathsf {F}}}}(X) \ge 0\). In case \(s=2t+1\),
$$\begin{aligned} \rho _{_{{\mathsf {F}}}}(X) = \rho ^{ }_{2t+1}(X) + \sum _{i=1}^t\big ( \rho ^{ }_{2i-1}(X) - \rho ^{ }_{2i}(X)\big ). \end{aligned}$$
(8)
and once again \(\rho _{_{{\mathsf {F}}}}(X) \ge 0\), thanks to Remark 20 and Lemma 22. Next, if \(s>1\) and if \(\mathsf {F}' =(C_2, \dots , C_s)\) denotes the flag obtained from \(\mathsf {F}\) by dropping the first term, then by what is just shown \(\rho _{_{\mathsf {F}'}}(X) \ge 0\) for any \(X\in \Sigma (E)\). Hence,
$$\begin{aligned} \rho _{_{{\mathsf {F}}}}(X) = \rho ^{ }_1(X) - \rho _{_{\mathsf {F}'}}(X) \le \rho ^{ }_1(X) \le m \dim X \quad \text {for all } X\in \Sigma (E). \end{aligned}$$
This shows that \(P(\mathsf {F})\) satisfies (R1). Next, let \(X, Y\in \Sigma (E)\) with \(X \subseteq Y\). We will show that \(\rho _{_{{\mathsf {F}}}}(X) \le \rho _{_{{\mathsf {F}}}}(Y)\). To this end, observe that since \(\rho _{_{{\mathsf {F}}}}(X)\) (and likewise \(\rho _{_{{\mathsf {F}}}}(Y)\)) can be expressed as in (7) or (8), and since \(\rho ^{ }_{2t+1}\) satisfies (R2), it suffices to show that the difference \( \Delta _i:= \big ( \rho _{2i-1}(Y) - \rho _{2i}(Y) \big ) - \big ( \rho _{2i-1}(X) - \rho _{2i}(X) \big ) \) is nonnegative for each \(i=1, \dots , t\). But an easy calculation shows that for \(1\le i \le t\),
$$\begin{aligned} \Delta _i = \big ( \dim C_{2i-1}(X^{\perp })-\dim C_{2i}(X^{\perp }) \big )- \big (\dim C_{2i-1}(Y^{\perp })-\dim C_{2i}(Y^{\perp }) \big ), \end{aligned}$$
and by Lemma 23, this is nonnegative since \(Y^\perp \subseteq X^\perp \). Thus \(P(\mathsf {F})\) satisfies (R2).
To prove that \(P(\mathsf {F})\) satisfies (R4), note that the case \(s=1\) is trivial. Thus suppose \(s>1\) and let \(\mathsf {F}' =(C_2, \dots , C_s)\). Also, let
$$\begin{aligned} \rho ^*(X)= \rho _{_{{\mathsf {F}}}}(X^{\perp })+m\dim X-\rho _{_{{\mathsf {F}}}}(E) \quad \text {and}\quad \rho '(X) = \rho _{_{\mathsf {F}'}}(X) \quad \text {for } X\in \Sigma (E). \end{aligned}$$
Since \(\rho _{_{{\mathsf {F}}}}= \rho ^{ }_1 - \rho '\) and since \(\rho ^{*}_1\) satisfies (R1) while \(\rho '\) satisfies (R2), we see that
$$\begin{aligned} \rho ^*(X)= \big ( \rho _1(X^{\perp })+m\dim X -\rho _1(E) \big ) +\big ( \rho '(E)-\rho '(X^{\perp })\big ) \ge \rho _1^*(X) +0 \ge 0. \end{aligned}$$
Also, \(\rho ^*(X)= m\dim X+\big ( \rho _{_{{\mathsf {F}}}}(X^{\perp })-\rho _{_{{\mathsf {F}}}}(E) \big ) \le m\dim X\), since \(\rho _{_{{\mathsf {F}}}}\) satisfies (R2). Thus \(\rho ^*\) satisfies (R1). Finally, if \(X, Y\in \Sigma (E)\) with \(X \subseteq Y\), then we can write \(\rho ^*(Y)-\rho ^*(X) = \big (\rho _{_{{\mathsf {F}}}}(Y^{\perp })+m\dim Y - \rho _{_{{\mathsf {F}}}}(E)\big )- \big (\rho _{_{{\mathsf {F}}}}(X^{\perp })+m\dim X - \rho _{_{{\mathsf {F}}}}(E)\big )\) as
$$\begin{aligned}&m\big (\dim Y -\dim X\big )+\big (\rho _{_{{\mathsf {F}}}}(Y^{\perp })-\rho _{_{{\mathsf {F}}}}(X^{\perp })\big ) \\= & {} m\big (\dim X^{\perp }-\dim Y^{\perp })-\big (\rho ^{ }_1 (X^{\perp })-\ \rho ^{ }_1 (Y^{\perp }) \big ) +\big (\rho '(X^{\perp })-\rho '(Y^{\perp })\big ) \\= & {} \big ( \nu _1(X^{\perp })-\nu _1(Y^{\perp }) \big ) +\big (\rho '(X^{\perp })-\rho '(Y^{\perp }) \big ), \end{aligned}$$
where \(\nu _1\) denotes the nullity function of \((E, \rho ^{ }_1 )\). Thus, using Proposition 6 and the fact that \(\rho '\) satisfies (R2), we see that \(\rho ^*\) satisfies (R4). \(\square \)
Generalized weights of flags of Delsarte codes
Using Theorem 24 and Definition 10, we can talk about generalized weights of flags of Delsarte codes. The following observation makes them explicit.
Lemma 25
Let \(\mathsf {F} = (C_1, \dots , C_s)\) be a flag of Delsarte codes. Then the conullity function \(\nu ^*_{_{\mathsf {F} }}\) of the associated (q, m)-demi-polymatroid \(P(\mathsf {F})=(E,\rho _{_{{\mathsf {F}}}})\) is given by
$$\begin{aligned} \nu ^*_{_{\mathsf {F} }}(X) = \sum _{i=1}^s(-1)^{i+1}\dim C_i(X) \quad \text {for } X\in \Sigma (E). \end{aligned}$$
Proof
For \(i=1, \dots , s\), let \(\rho ^{ }_i\) be as in (6) and let \(\nu ^*_i\) be the conullity function of the (q, m)-polymatroid \((E, \rho ^{ }_i)\). Then in view of (5) in Remark 20 we see that
$$\begin{aligned} \nu ^*_{_{\mathsf {F} }}(X) = \rho _{_{{\mathsf {F}}}}(E) - \rho _{_{{\mathsf {F}}}}(X^\perp ) = \sum _{i=1}^s(-1)^{i+1}\nu ^*_i(X) = \sum _{i=1}^s(-1)^{i+1}\dim C_i(X). \end{aligned}$$
for any \(X\in \Sigma (E)\). \(\square \)
The generalized weights of flags of Delsarte codes may be defined as follows.
Definition 26
Let \(\mathsf {F} = (C_1, \dots , C_s)\) be a flag of Delsarte codes in \({\mathbb M}\), and let \(K = \rho _{_{{\mathsf {F}}}}(E) = \sum _{i=1}^s(-1)^{i+1}\dim C_i\). Then for \(r=1, \dots , K\), the rth generalized weight of \(\mathsf {F}\) is denoted by \(d_r(\mathsf {F})\) or by \(d_{{\mathbb M},r}(C_1,\cdots ,C_s)\), and is defined by
$$\begin{aligned} d_r(\mathsf {F}) = \min \big \{\! \dim X : X\in \Sigma (E) \text { with } \sum _{i=1}^s(-1)^{i+1}\dim C_i(X) \ge r \big \}. \end{aligned}$$
In the case of singleton flags, i.e., when \(s=1\), the definition reduces to the following notion, first considered by Martínez-Peñas and Matsumoto [15, Definition 10], of the generalized weight of a Delsarte code C:
$$\begin{aligned} d_r(C) := \min \{ \dim X : X\in \Sigma (E) \text { with } \dim C (X) \ge r\} \quad \text {for } r=1, \dots , \dim C. \end{aligned}$$
(9)
This is related to, but distinct from Ravagnani’s definition (see Sect. 4.5 for details). In the case \(s=2\), generalized weights in Definition 26 coincide with the notion of Relative Generalized Matrix Weights, or RGMW profiles, as defined by Martínez-Peñas and Matsumoto [15, Definition 10].
Our definitions of generalized weights for (q, m)-demi-polymatroids and flags of Delsarte rank metric codes are of course compatible, and we record this below.
Theorem 27
Let \(\mathsf {F}=(C_1,\cdots ,C_s)\) be a flag of Delsarte rank metric code and let \(P(\mathsf {F}) = (E, \rho _{_{{\mathsf {F}}}})\) be the corresponding (q, m)-demi-polymatroid. Then
$$\begin{aligned} \sum _{i=1}^{s}(-1)^{i+1}\dim C_i = {\mathrm{rank}}P(\mathsf {F}) \quad \text {and for } r=1, \dots , {\mathrm{rank}}P(\mathsf {F}), \quad d_r(\mathsf {F})=d_r(P(\mathsf {F})). \end{aligned}$$
Proof
This follows directly from the definitions and Lemma 25. \(\square \)
Duality of Delsarte rank metric codes
As indicated in the Introduction, the notion of dual for Delsarte rank metric codes is defined using the trace product. See for example [18, Definition 34]. We recall the basic definition below.
Definition 28
Let C be a Delsarte code. The trace dual, or simply the dual, of C is the Delsarte code \(C^{\perp }\) defined by
$$\begin{aligned} C^\perp = \{ N \in {\mathbb M}_{m\times n}({\mathbb F}_q): \mathrm {Trace}(MN^t) =0 \text { for all } M \in C\}, \end{aligned}$$
where \(N^t\) denotes the transpose of a \(m\times n\) matrix N and, as usual, \(\mathrm {Trace}(MN^t)\) is the trace of the square matrix \(MN^t\), i.e., the sum of all its diagonal entries.
There is a natural connection between duals of Delsarte codes and the duals of (q, m)-polymatroids. It is shown by Shiromoto [19] as well as Gorla et al. [10], and we record it below.
Theorem 29
[19, Proposition 11] Let C be a Delsarte code. Then
$$\begin{aligned} P(C^{\perp })=P(C)^*. \end{aligned}$$
The proof is quite short and natural and given in [19, Proposition 11], and also in [10, Theorem 8.1]. An immediate consequence is the following.
Corollary 30
Let C be a Delsarte code in \({\mathbb M}_{m\times n}({\mathbb F}_q)\) and let \(K=\dim C\). Then the generalized weights \( d_r(C) =\min \{\dim X : X \in \Sigma (E) \text { with } \dim C(X) \ge r\} \) of C (\(1\le r \le K\)) are related to the generalized weights \(d_s(C^\perp )\) of \(C^{\perp }\) (\(1\le s \le mn - K\)) via the “m-fold” Wei duality described in Theorem 17.
Proof
Follows from Theorems 17, 27, and 29. \(\square \)
We remark that Corollary 30 gives another proof of [15, Proposition 65].
Duality for flags of Delsarte rank metric codes
Now that we have associated a (q, m)-demi-polymatroid \(P(\mathsf {F})=(E,\rho _{_{{\mathsf {F}}}})\) to a flag \(\mathsf {F}\) of Delsarte codes, it seems natural to ask whether \(P(\mathsf {F})^*\) is also a (q, m)-demi-polymatroid associated to some flag of Delsarte codes. The answer is yes, and it involves, quite naturally, a dual flag.
Definition 31
By the dual flag corresponding to a flag \(\mathsf {F} = (C_1, \dots , C_s)\) of Delsarte codes, we mean the flag \(\mathsf {F}^{\perp } = (C_s^\perp , \dots , C_1^\perp )\) of Delsarte codes, where \(C_i^\perp \) is the trace dual of \(C_i\) for \(i=1, \dots , s\). Note that \(C_1^{\perp } \subseteq \cdots \subseteq C_s^{\perp }\) so that \(\mathsf {F}^\perp \) is indeed a flag in the sense of Definition 21. Note also that \((\mathsf {F}^{\perp })^{\perp }=\mathsf {F}.\)
The following result is an analogue of [3, Theorem 10].
Proposition 32
Let \(\mathsf {F}= (C_1, \dots , C_s)\) be a flag of Delsarte codes and \(\mathsf {F}^\perp \) the dual flag corresponding to \(\mathsf {F}\). Also let \(\nu ^*_{_{\mathsf {F} }}\) denote the conullity function of the (q, m)-demi-polymatroid \(P(\mathsf {F})=(E,\rho _{_{{\mathsf {F}}}})\) associated to \(\mathsf {F}\). Then
$$\begin{aligned} \rho _{_{\mathsf {F}^\perp }}= {\left\{ \begin{array}{ll} \rho _{_{{\mathsf {F}}}}^* &{} \text {if } s \text { is odd}, \\ \nu ^*_{_{\mathsf {F} }}&{} \text {if } s \text { is even}. \end{array}\right. } \end{aligned}$$
Proof
A proof can be given, following word for word the proof of the corresponding result, [3, Theorem 10], for linear block codes. \(\square \)
Proposition 32 identifies the dual (q, m)-demi-polymatroid of \(P(\mathsf {F})\) as that associated to the dual flag, when \(\mathsf {F}\) is a flag of odd length s. This includes the case \(s=1\) corresponding to Theorem 29. But what if s is even (and in particular, \(s=2\))? Also what about a version of Wei duality for the generalized weights of flags of Delsarte codes? These questions are answered below.
Theorem 33
Let \(\mathsf {F}= (C_1, \dots , C_s)\) be a flag of Delsarte codes and let \(\mathsf {G} = (C_1, \dots , C_s, \{\mathbf {0}\} )\) denote the flag of length \(s+1\) obtained by appending to \(\mathsf {F}\) the zero subspace to \(\mathsf {F}\) (regardless of whether or not \(C_s = \{\mathbf {0}\}\)). Then:
-
(a)
If s is odd, then \(P(\mathsf {F})^*=P(\mathsf {F}^{\perp })\), and the generalized weights of \(\mathsf {F}\) and \(\mathsf {F}^{\perp }\) are in Wei duality with each other as described in Theorem 17.
-
(b)
If s is even, then \(P(\mathsf {F})^*=P(\mathsf {G}^{\perp })\), and the generalized weights of \(\mathsf {F}\) and \(\mathsf {G}^{\perp }\) are in Wei duality with each other as described in Theorem 17.
Proof
Part (a) follows from Theorems 17, 24, and 27 together with Proposition 32. Part (b) follows from part (a) by noting that \(\rho _{_{\mathsf {G}}}=\rho _{_{{\mathsf {F}}}}\). \(\square \)
Corollary 34
Let \(C_1, C_2\) be distinct Delsarte codes in \({\mathbb M}_{m\times n}({\mathbb F}_q)\) with \(C_2\subseteq C_1\), and let \(K=\dim C_1-\dim C_2\). Then the relative generalized weights
$$\begin{aligned} d_r =\min \{\dim X : X \in \Sigma (E) \text { with } \dim C_1(X) - \dim C_2(X) \ge r\} \end{aligned}$$
are related to the relative generalized weights
$$\begin{aligned} d_r^{\perp } =\min \{\dim X : X \in \Sigma (E) \text { with } \dim {\mathbb M}(X) - \dim C_2^{\perp }(X)+\dim C_1^{\perp }(X) \ge r\} \end{aligned}$$
via the “m-fold” Wei duality described in Theorem 17, for \(r=1, \dots , K\).
Proof
If s is even and \(\mathsf {F}= (C_1, \dots , C_s)\) and \(\mathsf {G}\) are as in Theorem 33, then
$$\begin{aligned} \rho _{_{{\mathsf {F}}}}^*=\rho _{_{\mathsf {G}}}^*=\rho _{_{\mathsf {G}^\perp }} = {\rho _{_{\{0\}^\perp }}} - {\rho _{_{C_{s}^\perp }}} + \cdots + (-1)^s {\rho _{_{C_{1}^\perp }}} = {\rho _{_{{\mathbb M}}}} - {\rho _{_{C_{s}^\perp }}} + \cdots + {\rho _{_{C_{1}^\perp }}} . \end{aligned}$$
In particular, if \(s=2\), then \( \rho _{_{{\mathsf {F}}}}^* = {\rho _{_{{\mathbb M}}}} - {\rho _{_{C_{2}^\perp }}} + {\rho _{_{C_{1}^\perp }}}. \) Thus, the desired result follows from Theorem 33 in view of Eq. (5) in Remark 20. \(\square \)
Another definition of generalized weights
Ravagnani has given another definition in [18, Definition 23] of generalized weights of (single) Delsarte codes that is based on the following notion of optimal anticodes.
Definition 35
By an optimal anticode we mean an \({\mathbb {F}}_q\)-linear subspace \({\mathcal {A}}\) of \({\mathbb M}_{m\times n}({\mathbb F}_q)\) such that \(\dim _{{\mathbb {F}}_q} {\mathcal {A}} =m\! \left( \mathrm {maxrank}({\mathcal {A}})\right) \), where \(\mathrm {maxrank}({\mathcal {A}})\) denotes the maximum possible rank of any matrix in \({\mathcal {A}}\).
Here is Ravagnani’s definition of generalized weights of Delsarte codes.
Definition 36
Let C be a Delsarte code of dimension K. For \(r=1, \dots , K\), define
$$\begin{aligned} a_r(C)=\frac{1}{m}\min \left\{ \dim _{{\mathbb {F}}_q}{\mathcal {A}} : {\mathcal {A}} \text { an optimal anticode such that }\dim _{{\mathbb {F}}_q}({\mathcal {A}} \cap C)\ge r\right\} . \end{aligned}$$
A relationship between the two notions of generalized weights (given in equation (9) and Definition 36) is stated below.
Theorem 37
Let C be a Delsarte code. Then for each \(r=1, \dots , \dim C\),
$$\begin{aligned} a_r(C)=d_r(C) \text { if } {m > n}, \quad \text {whereas} \quad a_r(C) \le d_r(C) \text { if } m=n. \end{aligned}$$
Further, if \(C^T\) denotes the Delsarte code in \({\mathbb {M}}_{n\times m}({\mathbb F}_q)\) consisting of transposes of the matrices in C, then \(a_r(C)=d_r(C^T)\) if \(m < n\).
Proof
For a proof in the case \(m > n\) or \(m=n\), see [15, Theorem 9] (or alternatively, [10, Proposition 2.11]). For the case \(m<n\), see [9, Theorem 5.18].
When \(m=n\), both [18, Corollary 38] and Corollary 30 are still valid, but the \(a_r\) and the \(d_r\) are not necessarily the same. An example where they are different is given by Martínez-Peñas and Matsumoto [15, Section IX,C]. A precise relationship between the two notions of generalized weights in this case of square matrices is given in [9, Theorem 5.18]. We will discuss a (q, m)-demi-polymatroid version of this below, and deduce the said relationship as a consequence.
First note that if \(m=n\) and if \(C \subseteq {\mathbb M}_{m\times n}({\mathbb F}_q)\) is a Delsarte rank metric code, then so is \(C^T:=\{M^t: M \in C\}\), and thus, we obtain two (q, m)-polymatroids \(P(C) = (E, \rho ^{ }_C)\) and \(P(C^T) = (E, \rho ^{ }_{C^T})\) as in part (ii) of Definition 19.
Proposition 38
Assume that \(m=n\). Let \(C \subseteq {\mathbb M}_{m\times n}({\mathbb F}_q)\) be a Delsarte rank metric code. Consider \(E={\mathbb {F}}_q^n\) and define \(\rho :\Sigma (E)\rightarrow {\mathbb {N}}_0\) by
$$\begin{aligned} \rho (X)=\min \{\rho ^{ }_{C}(X), \; \rho ^{ }_{C^T}(X)\} \quad \text {for } X\in \Sigma (E). \end{aligned}$$
Then \(P=(E,\rho )\) is a (q, m)-demi-polymatroid and its conullity function is given by
$$\begin{aligned} \nu ^*(X)=\max \{\dim C(X), \; \dim C^T (X)\} \quad \text {for } X\in \Sigma (E). \end{aligned}$$
Moreover, the generalized weights of P are given by
$$\begin{aligned} d_r(P)=\min \{d_r(P(C)), \; d_r(P(C^T)) \} \quad \text {for } r=1, \dots , \rho (E). \end{aligned}$$
Consequently, m-fold Wei duality as in Theorem 17 holds for Ravagnani’s generalized weights \(a_r(C)\).
Proof
It is obvious that \(\rho \) satisfies (R1) and (R2) of Definition 1, since we know that each of \(\rho _C\) and \(\rho _{C^T}\) satisfies these properties. So, in order to prove that P is a (q, m)-demi-polymatroid, it remains to show that (R4) is satisfied, which means that \(\rho ^*\) satisfies (R1) and (R2). To this end, let \(X\in \Sigma (E)\). Then
$$\begin{aligned} \nonumber \rho ^*(X)= & {} \rho (X^{\perp }) +m\dim X-\rho (E) \nonumber \\= & {} \min \{ \rho ^{ }_{C}(X^{\perp }), \; \rho ^{ }_{C^T}(X^{\perp }) \} +m\dim X- \dim C \nonumber \\= & {} \min \{ \dim C - \dim C(X), \; \dim C - \dim C^T (X) \}+m \dim X -\dim C. \end{aligned}$$
It follows that
$$\begin{aligned} \rho ^*(X) = m\dim X - \max \{\dim C(X), \; \dim C^T(X)\} . \end{aligned}$$
(10)
This implies that \(\rho ^*(X) \le m\dim X\). Moreover, it also implies that \(\rho ^*(X) \ge 0\), because from (5) and Proposition 6 we see that both \(m\dim X - \dim C(X)\) and \(m\dim X - \dim C^T(X)\) are nonnegative. Thus, \(\rho ^*\) satisfies (R1). Next, we show that \(\rho ^*\) satisfies (R2). Fix \(X, Y\in \Sigma (E)\) with \(X \subseteq Y\). In view of (10), the difference \(\rho ^*(Y)-\rho ^*(X)\) can be written as
$$\begin{aligned} m(\dim Y - \dim X ) - \big (\max \{\dim C(Y),\dim C^T(Y)\} - \max \{\dim C(X),\dim C^T(X)\} \big ). \end{aligned}$$
Since the expression above is symmetric in C and \(C^T\), we may assume without loss of generality that \(\max \{\dim C(Y),\dim C^T(Y)\} = \dim C(Y)\). Now, in case \(\max \{\dim C(X),\dim C^T(X)\} = \dim C(X)\), we see that
$$\begin{aligned} \rho ^*(Y)-\rho ^*(X) = m(\dim Y - \dim X ) - (\dim C(Y) - \dim C(X) ) = \rho _{C}^*(Y)-\rho _{C}^*(X), \end{aligned}$$
which is nonnegative since \(\rho _{C}^*\) satisfies (R1), thanks to Proposition 2. In case \(\max \{\dim C(X),\dim C^T(X)\} = \dim C^T(X)\), then \( \dim C^T(X) \ge \dim C(X)\), and so
$$\begin{aligned} \rho ^*(Y)-\rho ^*(X) = m(\dim Y - \dim X ) - (\dim C(Y) - \dim C^T(X) ) \ge \rho _{C}^*(Y)-\rho _{C}^*(X), \end{aligned}$$
which is again nonnegative. Thus, \(\rho ^*\) satisfies (R2). This proves that \(P=(E,\rho )\) is a (q, m)-demi-polymatroid. The desired formula for the conullity function of P is immediate from (10). This, in turn, shows that
$$\begin{aligned} d_r(P)=\min \left\{ d_r(P(C)), \; d_r(P(C^T))\right\} \quad \text {for } r=1, \dots , \rho (E). \end{aligned}$$
Indeed, the inequality \(d_r(P) \le \min \{d_r(P(C)), \; d_r(P( C^T )) \}\) is clear from the definition and equation (5). For the other inequality, it suffices to consider \(X_0\in \Sigma (E)\) with \(\max \{\dim C(X_0), \; \dim C^T (X_0)\} \ge r\) such that \(d_r(P) = \dim X_0\).
The last assertion about Wei duality for Ravagnani’s generalized weights \(a_r(C)\) is an immediate consequence of Theorem 17 because we know from [9, Theorem 38] that \(a_r(C) = \min \{d_r(P(C)), \; d_r(P(C^T )) \}\) for \(1\le r \le \dim C = \rho (E)\). \(\square \)