Extended and generalized weight enumerators Relinde Jurrius Ruud - - PowerPoint PPT Presentation

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Extended and generalized weight enumerators Relinde Jurrius Ruud - - PowerPoint PPT Presentation

Extended and generalized weight enumerators Relinde Jurrius Ruud Pellikaan Eindhoven University of Technology, The Netherlands International Workshop on Coding and Cryptography, 2009 1/23 Outline Previous work Codes, weights and weight


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Extended and generalized weight enumerators

Relinde Jurrius Ruud Pellikaan

Eindhoven University of Technology, The Netherlands

International Workshop on Coding and Cryptography, 2009

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Outline

Previous work Codes, weights and weight enumerators Generalized weight enumerator Extended weight enumerator Matroids and the Tutte polynomial Overview of connections Application: MacWilliams relations Coset leader and list weight enumerator Further work

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Previous work

  • A. Barg

Codes and matroids, generalized WE

  • T. Britz

Codes and matroids, Tutte polynomial

  • C. Greene

Connection Tutte polynomial and weight enumerator

  • T. Helleseth

Extended WE, coset leader WE

  • G. Katsman and M. Tsfasman

Determination of WE

  • T. Kløve

Extended WE, generalized WE, MacWilliams relations

  • J. Simonis

Generalized WE, MacWilliams relations

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Codes, weights and weight enumerators

Linear [n, k] code Linear subspace C ⊆ Fn

q of dimension k.

Elements are called (code)words, n is called the length. Generator matrix The rows of this k ×n matrix form a basis for C. Support The coordinates of a word which are nonzero. Weight The number of nonzero coordinates of a word, i.e. the size of the support.

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Codes, weights and weight enumerators

Linear [n, k] code Linear subspace C ⊆ Fn

q of dimension k.

Elements are called (code)words, n is called the length. Generator matrix The rows of this k ×n matrix form a basis for C. Support The coordinates of a word which are nonzero. Weight The number of nonzero coordinates of a word, i.e. the size of the support.

Weight enumerator

The homogeneous polynomial counting the number of words of a given weight, notation: WC(X, Y ) =

n

  • w=0

AwXn−wY w.

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Codes, weights and weight enumerators

Example

The [7, 4] Hamming code over F2 has generator matrix G =     1 1 1 1 1 1 1 1 1 1 1 1 1     . The weight enumerator is equal to WC(X, Y ) = X7 + 7X4Y 3 + 7X3Y 4 + Y 7.

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Generalized weight enumerator

For a subcode D ⊆ C we define Support Union of the support of all words in D, i.e. all coordinates which are not always zero. Weight Size of the support.

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Generalized weight enumerator

For a subcode D ⊆ C we define Support Union of the support of all words in D, i.e. all coordinates which are not always zero. Weight Size of the support.

Generalized weight enumerators

The homogeneous polynomials counting for each dimension r = 0, . . . , k the number of subcodes of a given weight, notation: W r

C(X, Y ) = n

  • w=0

Ar

wXn−wY w

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Generalized weight enumerator

Example

The [7, 4] Hamming code has generalized weight enumerators W 0

C(X, Y )

= X7 W 1

C(X, Y )

= 7X4Y 3 + 7X3Y 4 + Y 7 W 2

C(X, Y )

= 21X2Y 5 + 7XY 6 + 7Y 7 W 3

C(X, Y )

= 7XY 6 + 8Y 7 W 4

C(X, Y )

= Y 7

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Extended weight enumerator

Extension code [n, k] code over some extensionfield Fqm generated by the words of C, notation: C ⊗ Fqm.

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Extended weight enumerator

Extension code [n, k] code over some extensionfield Fqm generated by the words of C, notation: C ⊗ Fqm.

Extended weight enumerator

The polynomial “counting the number of words in an extension code”, notation: WC(X, Y, T) =

n

  • w=0

Aw(T)Xn−wY w. Note that with T = qm we have WC(X, Y, qm) = WC⊗Fqm(X, Y ).

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Extended weight enumerator

For all subsets J ⊆ [n] define C(J) = {c ∈ C : cj = 0 for all j ∈ J} l(J) = dim C(J) BJ(T) = T l(J) − 1 Bt(T) =

  • |J|=t

Br

J

So C(J) is equivalent to the code C shortened on J.

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Extended weight enumerator

For all subsets J ⊆ [n] define C(J) = {c ∈ C : cj = 0 for all j ∈ J} l(J) = dim C(J) BJ(T) = T l(J) − 1 Bt(T) =

  • |J|=t

Br

J

So C(J) is equivalent to the code C shortened on J.

Extended weight enumerator

The extended weight enumerator can be written as WC(X, Y, T) = Xn +

n

  • t=0

Bt(T)(X − Y )tY n−t.

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Extended weight enumerator

Example

The [7, 4] Hamming code has extended weight enumerator WC(X, Y, T) = X7 + 7(T − 1)X4Y 3 + 7(T − 1)X3Y 4 + 21(T − 1)(T − 2)X2Y 5 + 7(T − 1)(T − 2)(T − 3)XY 6 + (T − 1)(T 3 − 6T 2 + 15T − 13)Y 7

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Extended weight enumerator

We considered three ways to determine the extended weight enumerator:

  • Brute force and Lagrange interpolation

Look at all words of k + 1 extension codes. Terribly slow.

  • Geometric approach

Using l(J) and Bt(T), also applicable for generalized WE. Much faster for WC(X, Y, T) instead of WC(X, Y ).

  • Deletion/contraction algorithm

Recursive algorithm, also used for matroids. Good for classifying codes up to a certain length.

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Connections (1)

We can write the extended weight enumerator in terms of the generalized weight enumerator: WC(X, Y, T) =

k

  • r=0

 

r−1

  • j=0

(T − qj)   W r

C(X, Y ).

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Connections (1)

We can write the extended weight enumerator in terms of the generalized weight enumerator: WC(X, Y, T) =

k

  • r=0

 

r−1

  • j=0

(T − qj)   W r

C(X, Y ).

Because we use WC(X, Y, T) instead of WC⊗Fqm(X, Y ) we also find the inverse: W r

C(X, Y ) =

1 r−1

i=0 (qr − qi) r

  • j=0

r j

  • (−1)r−jq(r

j) WC(X, Y, qj).

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Matroids

Matroid theory generalizes the notion of “linear independence”.

  • Vector space: linear independent vectors, basis
  • Graph: tree, minimal spanning tree
  • Matroid: independent set, basis

A matroid consist of a finite set E and a set of independent sets from 2E having some defining properties.

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Matroids

Matroid theory generalizes the notion of “linear independence”.

  • Vector space: linear independent vectors, basis
  • Graph: tree, minimal spanning tree
  • Matroid: independent set, basis

A matroid consist of a finite set E and a set of independent sets from 2E having some defining properties.

Example

A code can be viewed as a matroid by considering the columns of a generator matrix and their dependance in Fk

q.

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Tutte polynomial

A matroid has a rank function, notation r(A), associating a non-negative integer to every subset A of E.

Example

For matroid from a generator matrix G of a code, r(A) is the rank

  • f the submatrix formed by the columns of G indexed by A.

Furthermore, r(E) = k.

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Tutte polynomial

A matroid has a rank function, notation r(A), associating a non-negative integer to every subset A of E.

Example

For matroid from a generator matrix G of a code, r(A) is the rank

  • f the submatrix formed by the columns of G indexed by A.

Furthermore, r(E) = k.

Tutte polynomial

The Tutte polynomial is defined by tG(X, Y ) =

  • A⊆E

(X − 1)r(E)−r(A)(Y − 1)|A|−r(A).

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Connections (2)

The extended weight enumerator can be given in terms of the Tutte polynomial: WC(X, Y, T) = (X − Y )kY n−k tG X + (T − 1)Y X − Y , X Y

  • .

Due to the earlier connection, we have similar formulas for W r

C(X, Y ) and tG(X, Y ).

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Overview of connections

WC(X, Y ) WC(X, Y, T)

  • {W r

C(X, Y )}k r=0

  • tG(X, Y )
  • {W r

C(X, Y, T)}k r=0

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Application: MacWilliams relations

Duality for matroids

For a matroid G and its dual G∗ we have tG(X, Y ) = tG∗(Y, X).

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Application: MacWilliams relations

Duality for matroids

For a matroid G and its dual G∗ we have tG(X, Y ) = tG∗(Y, X). With this and the connections, the proofs of the MacWilliams relations for WC(X, Y, T) and W r

C(X, Y ) reduce to rewriting.

MacWilliams relations

For a code C and its dual C⊥ we have WC⊥(X, Y, T) = T −kWC(X + (T − 1)Y, X − Y, T).

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Cosets en weights

Coset Translation of the code by some vector y ∈ Fn

q .

Weight The minimum weight of all vectors in the coset. Coset leader A vector of minimum weight in the coset. Covering radius The maximum possible weight for a coset.

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Cosets en weights

Coset Translation of the code by some vector y ∈ Fn

q .

Weight The minimum weight of all vectors in the coset. Coset leader A vector of minimum weight in the coset. Covering radius The maximum possible weight for a coset. αi The number of cosets of weight i. λi The number of vectors of weight i which are of minimal weight in their coset, i.e. the number of possible coset leaders of weight i.

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Coset leader and list weight enumerator

Extended coset leader weight enumerator

αC(X, Y, T) =

n

  • i=0

αi(T)Xn−iY i.

Extended list weight enumerator

λC(X, Y, T) =

n

  • i=0

λi(T)Xn−iY i.

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Coset leader and list weight enumerator

Example

The [7, 4] Hamming code has extended coset leader and extended list weight enumerator αC(X, Y, T) = X7 + 7(T − 1)X6Y + 7(T − 1)(T − 2)X5Y 2 + (T − 1)(T − 2)(T − 4)X4Y 3, λC(X, Y, T) = X7 + 7(T − 1)X6Y + 21(T − 1)(T − 2)X5Y 2 + 28(T − 1)(T − 2)(T − 4)X4Y 3.

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Connections (3)

The extended coset leader weight enumerator αC(X, Y, T) does NOT determine

  • the extended coset leader weight enumerator αC⊥(X, Y, T)
  • f the dual code;
  • the extended list weight enumerator λC(X, Y, T);
  • the extended weight enumerator WC(X, Y, T).

This can be shown by counterexamples. Open question: does the extended list weight enumerator λC(X, Y, T) determine one of the above?

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Further work

  • Determination of αC(X, Y, T) and λC(X, Y, T) via

arrangements of hyperplanes and their characteristic polynomial

  • Generalized coset leader weight enumerator?
  • Connection with zeta-functions of codes and arrangements of

hyperplanes

  • Extend known theory to extended weight enumerator
  • Concrete computations for special classes of codes
  • Characterization of the various weight enumerators
  • Complexity issues / implementation
  • . . .
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