zsy [Options] [-G] Mode Inp Out
The Mode argument specifies the tensor product to be taken and the kind of symmetrization to be performed. Currently there are 4 Modes available:
Since the typical application of zsy is to generate new representations from existing ones, it will usually be used with square matrices. However, the input is not required to be square.
In the output, pairs and triples are numbered lexicographically. For example, E2 uses the following order: (1,2), (1,3), (2,3), (1,4), ... Notice that the symmetric square is never transitive but decomposes into the diagonal and the antisymmetric square. Here are some examples:
p = (1 5 4 3 2) e2(p) = (1 7 10 6 3)(2 8 4 9 5) s2(p) = (1 15 10 6 3)(2 11 14 9 5)(7 14 8 4 12) e3(p) = (1 5 8 10 4)(2 6 9 3 7)
The symmetric square of a matrix with r rows and c columns is a matrix with r(r+1)/2 rows and c(c+1)/2 columns, with entries given by the formulae
where the upper left is the r(r-1)/2 by c(c-1)/2 matrix of permanents. The program orders both the rows and the columns in lexicographical order, i.e. v1v2, v1v3, ... v1vn, v2v3, v2v4, ... v2vn, v3v4, ... v_{n-1}vn, v1v1, v2v2, ... vnvn with the assumption that vivj = vjvi, i.e. the action is on quadratic polynomials.
The symmetric square is, in general, irreducible except in characteristic 2. In that case there is a copy of the Frobenius square as an invariant submodule, as can be seen from the 2ab in the above formulae. Invariant subspaces in characteristic 2 correspond to special groups (i.e. groups of the form 2n×2m) on which the group given acts on the quotient 2n.
Here are some examples:
(1 2 1 3) (1 2 1 3 6 2) E2 (0 1 2 1) = (0 1 0 2 0 4) (mod 7) (1 2 2 3) (6 5 6 5 1 4)
(1 0 2 0 2) (1 0 1 4 0 1 0 0 0 0) E3 (1 1 2 1 2) = (1 4 3 4 0 3 2 1 3 4) (mod 5) (3 3 2 3 2) (1 2 2 3 2 3 1 3 4 2) (1 2 3 1 0) (4 0 4 0 2 0 4 2 1 3)
(1 2 1 5 5 7 0 2 2 3) (1 2 1 3) (4 3 6 6 12 9 1 4 2 9) S2 (0 1 2 1) = (1 2 1 6 5 8 0 2 4 3) (mod 13) (1 2 2 3) (4 2 6 4 12 6 1 4 1 9) (0 0 0 4 2 4 0 1 4 1) (4 4 6 8 12 12 1 4 4 9)
If the input is a matrix, the whole input matrix and one row of the result must fit into memory. In case of permutations both the input and the result must fit into memory.