> The last element of that Groebner basis is a univariate polynomial in
> x2, so it is relatively easy to analyze its solutions.  There is one
> triple root at x2=0, and then four others which are presumably the
> four you are thinking of.  Once you have a value for x2, you can
> substitute it into the other Groebner basis equations to find x1.

Indeed, you're right, my preferred solution is in there!  I looked to
see if the first element was in one variable and when it wasn't, I
didn't think to look at the others.  doh!  Now, I can copy and paste
the appropriate basis element  to turn it into something I can pass to
solve(), but there must be a better (more programmatic) way to coerce
it:

sage: B[2]
x2^7 + 4*x2^6 - 6*x2^5 - 20*x2^4 + 5*x2^3
sage: type(B[2])
<type
'sage.rings.polynomial.multi_polynomial_libsingular.MPolynomial_libsingular'>
sage: foo = x2^7 + 4*x2^6 - 6*x2^5 - 20*x2^4 + 5*x2^3 ; foo
x2^7 + 4*x2^6 - 6*x2^5 - 20*x2^4 + 5*x2^3
sage: type(foo)
<type 'sage.symbolic.expression.Expression'>

> ... phcpack ...

My equations are actually first order condtions of the Lagrangian from
a constrained optimization problem.  I've been trying to solve them
symbolically so I know I've found all the solutions (not just the one
closest to my starting value).  That is, up til now I've been loath to
apply numerical optimization methods to the problem directly.  But
using phcpack on the FOC's seems to find all the solutions so that
might be a numerical method that's OK in this case.

Thanks!

Doug

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