You evaluate it over ZZ[x1,...,xn] rather than GF(2)[x1,...,x4].

Anyways, it simply can't be *that* slow in any case: even: the
(theoretically ) maximum number of monoms that can be in any
expansion is less than a few thousands, so the upper limit
for a naively implemented Gaussian elimination is in the
order of seconds. However the matrix is even much simpler than
that and even the inverse is computed immediately.

On 12/17/09, [email protected] <[email protected]> wrote:
> And another observation:
>
>  maxima returns answer immediatelly (with a lag necessary to start
>  maxima)
>  m is the original matrix from x.py
>
>  sage: m._maxima_().determinant().expand().sage()
>  x0^2*x2^2*x3^2*x7^2 - 2*x0*x1*x2*x3*x4*x5*x6*x7 + x1^2*x4^2*x5^2*x6^2
>
>
>  Anyway, the answer is different from expected one. I do not konw which
>  one is correct.
>
>  Robert
>
>
>
>  On 17 pro, 11:40, "[email protected]" <[email protected]> wrote:
>  > perhaps problems expanding polynomials? even determinant of submatrix
>  > (0,0,5,5)  is suprisingly slow.
>  >
>  > workaroud is to replace polynomials in your matrix by variables.
>  >
>  > var('x0 x1 x2 x3 x4 x5 x6 x7 a1 a2 a3 a4 a5 a6 a7 b1 b2 b3 b4 b5 b6
>  > b7')
>  > m=matrix([[      0, a1, a2, a3, a4, a5, a6, a7],
>  > [b1,       0,      x0,       0,       0,       0,       0,       0],
>  > [b2,      x0,       0,      x6,       0,       0,       0,       0],
>  > [b3,       0,      x6,       0,      x3,       0,       0,       0],
>  > [b4,       0,       0,      x3,       0,      x4,       0,       0],
>  > [b5,       0,       0,       0,      x4,       0,      x2,       0],
>  > [b6,       0,       0,       0,       0,      x2,       0,      x1],
>  > [b7,       0,       0,       0,       0,       0,      x1,       0]])
>  > m
>  >
>  > m.det()  gives answer immediatelly and you can substitute back for a's
>  > and b's.
>  >
>
>
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