Coding theory: algebraic geometry of linear algebra David R. Kohel

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Coding theory: algebraic geometry of linear algebra David R. Kohel 1. Introduction. Let R be a ring whose underlying set we call the alphabet. A linear code C over R is a free R-module V of rank k, an embedding ι : V U in a free module U of rank n, and a choice of basis B = {e i } for U. The code is said to have block length n and dimension k. We will also assume that the cokernel W of ι is free over R. We will be slightly sloppy and identify the image of V in U with the code C. We define : U N by x = {i : x i 0}, where x = i x i e i U. We call x the weight of x, and define a distance function d(, ) : U U N by setting d(x, y) = x y. The minimum distance d of the code C is the minimum of d(x, y) for x and y in C. By the linearity of C, we have that d is the minimum weight of a nonzero codeword. We call a linear code C with parameters n, k and d a linear [n, k, d]-code. Consider the exact sequence of R-modules 0 V ι U π W 0 By means of choices of bases for V and W we can represent ι and π by matrices G and, the generator matrix and the parity check matrix, respectively. The main problems of study in coding theory are: 1. Good encoding and decoding algorithms for families of codes. 2. Proving the existence, or nonexistence, of linear [n, k, d]-codes over R of given parameters. 3. Construction of families of codes which are asymptotically good as n goes to infinity. 4. Computing the weight enumerator polynomials w(z) = w C (z) = i A i z i = x C q x, 1

for C lying in a family of codes. (In some families of algebraicgeometric codes, the codewords of a given weight are points on an algebraic variety and can be effectively computed.) 2. Equivalence of codes. Let C = (ι : U V, B) and C = (ι : U V, B ) be codes. An isomorphism of codes is an isomorphism ϕ : U U of R-modules which preserves weights and such that ϕ(ι(v )) = ι (V ). Note that ϕ(b) need not equal B ; the weight preserving condition only requires that the linear subspaces {R e i } are permuted. An automorphism of codes is an isomorphism of a code with itself. The automorphism group of C is a subgroup of the semidirect product of the permutation group S n and (R ) n. 3. Projective systems. Let M be a free R-module of dimension k and let S be a subset of n points (which need not be distinct) such that S lies in no hyperplane of V. We call the pair (M, S) a linear system over R, and set n = S, k = rank(m), d = n max S 1, where runs over all hyperplanes of M. We define an isomorphism of linear systems (M, S) and (M, S ) to be an R-module isomorphism M M taking S onto S. Theorem 0.1 The isomorphism classes of linear [n, k, d]-codes are in bijective correspondence with the isomorphism classes of (M, S) with parameters n, k and d. Before proving the theorem, we define a projective system by letting ( P = P(M) = M ) am /R, and P be the image of S in P. We call (P, P) a projective system, and define a R n = P, k = dim(p) + 1, d = n max P. We say that a code is nondegenerate if C is not contained in U i for any of the n canonical hyperplanes U i of U generated by {e 1,..., ê i,..., e n } B. 2

Theorem 0.2 The set of isomorphism classes of nondegenerate R-linear [n, k, d]-codes are in bijective correspondence with projective systems over R with parameters n, k, and d. Proof of Theorem 0.1. Let V = M and define V U = R n by ϕ (ϕ(p 1 ), ϕ(p 2 ),..., ϕ(p n )). Conversely, given a code (ι : U V, B), the basis B = {e i } determines a dual basis {e i } of U which restricts to elements of M = V. The second theorem follows easily. Note that the degeneracy of a code corresponding to (M, S) is just the multiplicity of (0, 0,..., 0) in S. Exercise. Set = n P and verify that w(z) = 1 + (q 1) z, where q is the size of the alphabet. Example. Let R = F 4 and let E be the elliptic curve given by Y 2 Z + Y Z 2 = X 3 in P 2. Then (0 : 1 : 0), (0 : 0 : 1), (0 : 1, 1), E(F 4 ) = (1 : α : 1), (α : α : 1), (α 2 : α : 1),, (1 : α 2 : 1),(α : α 2 : 1),(α 2 : α 2 : 1) where α is a generator for F 4. To turn this into a linear code, we make some ugly choices... We lift these points back to M = F 3 4 and set U = F9 4. Then with the basis {x, y, z} for V = M, we have V U given by the generator matrix 0 0 0 1 1 α α α 2 α 2 G = 1 0 1 α α 2 α α 2 α α 2. 0 1 1 1 1 1 1 1 1 We now determine directly that the weight enumerator polynomial for C is 1 + 4z 6 + 3z 8. In particular, the minimum distance is 6. Thus we have constructed a linear [9, 3, 6] code. 4. Duals of codes. 3

The dual of a linear code C is defined to be the linear subspace C = {x U : x y = 0 for all y C}. The block length of the dual code is still n, and the dimension of the code is n k. The MacWilliams identity relates the weight enumerator polynomials of C and C. We have ( ) w C (z) = q k 1 z w C 1 (q 1)z The weight enumerator polynomial of C in the example above is then w C (z) = 1 + 5z 3 + 11z 4 + 24z 5 + 8z 6 + 11z 7 + 4z 8, and C is a linear [9, 6, 3]-code. Notice that in this example the sum k + d is equal to n. For any linear code we have the following general bound. Theorem 0.3 (Singleton bound) For any linear [n, k, d]-code k + d n + 1. Proof. Consider any k 1 points in P(V ) = P k 1. Necessarily they lie in a hyperplane. Thus by definition of a projective system, k 1 max P = n d. 5. Line bundles on X In order to prove the following theorem, we introduce line bundles on a variety X. Theorem 0.4 Let X be a curve, let T be a subset of X(R) of cardinality n, and let L be a line bundle on X of degree a. Let s 1,..., s k be a basis for the global sections of L, and assume that the induced morphism ϕ : X P k 1 is an embedding. Then the projective system (P k 1 (R), P), where P = ϕ(t ), determines a linear [n, k, d]-code with parameters In particular, k + d n + 1 g. k a g + 1 and d n a. 4

Note 1. Our elliptic curve example was such an example with a = 3, g = 1, and P = E(F 4 ) of cardinality 9. Note 2. A line bundle L satisfying the conditions of the theorem is said to be very ample. Let O X be the sheaf of functions on X, i.e. for each open subset U of X, O X (U) is the ring of rational polynomial maps U R. A sheaf F of O X -modules is defined to be a sheaf on X such that for each open subset U of X, the group L(U) is an O X (U) module, and for each inclusion of open sets V U the homomorphism L(U) L(V ) is compatible with the ring homomorphism O X (U) O X (V ), i.e. L(U) L(V ) becomes a homomorphism of O X (U)-modules. A line bundle L (or invertible sheaf) is defined to be a sheaf of O X - modules on X such that there exists a covering of X by open sets U such that L U is isomorphic to O X U. In short, a line bundle is defined by the conditions that 1. For each open set U in a covering of X, L(U) is isomorphic to an O X (U)-module. 2. The inclusions L(U V ) L(U) and L(U V ) L(V ) determine how the modules glue together. Sketch of proof. The theorem is proved with the following steps. 1. The dimension k of L(X) over R is at least a g + 1 by the Riemann- Roch theorem. 2. The global sections s 1,..., s k of L(X) determine an embedding as follows. For each set U in a cover of X, fix an isomorphism L(U) = O X (U). Then we can define X ϕ P k 1. P (s 1 (P ) : : s k (P )). Since changing the isomorphism is equivalent to multiplying each s i by a unit in O X (U), this gives a well-defined map to P k 1. 3. Apply the equivalence of projective systems and codes. The minimum distance of the code is defined to be d = n max T. 5

Over an algebraically closed field R, by Bezout s theorem the cardinality of ϕ(x(r)), counted with multiplicity, is equal to a for any hyperplane. Over general R we may get lucky and a may be smaller, but we have a lower bound d n a. 6