In my work on dynamical systems I have used Newton polygons as a practical tool but I never understood the theoretical basis for why they are helpful. Here I give a minimal theoretical discussion. I do not yet understand the link to the applications I just mentioned but at least it is a start. Consider a polynomial equation of the form . The polynomial
can be written in the form
. Suppose that
, i.e. that
. I look for a family
of solutions satisfying
. We have
. Intuitively the zero set of
is an algebraic variety which near the origin is the union of a finite number of branches. The aim is to get an analytic approximation to these branches. Substituting the ansatz into the equation gives
. If we compare the size of the summands in this expression then we see that summands have the same order of magnitude if they satisfy the equation
for the same constant
. Let
be the subset of the plane with coordinates
for those cases where
. For
the line
with equation
does not intersect
. If we increase
then eventually the line
will meet
. If it meets
in exactly one point then the ansatz is not consistent. A given value of
is only possible if the line meets
in more than point for some
. Let
be the set of points with coordinates
such that
and
for some
and let
be the convex hull of
. Then for an acceptable value of
the line
must have a segment in common with
. There are only finitely many values of
for which this is the case. A case which could be of particular interest is that of the smallest branch, i.e. that for which
takes the smallest value. Consider for simplicity the case that only two points of
belong to
. Call their coordinates
and
. Then the coefficient
is determined by the relation
. Further questions which arise are whether the formal asymptotic expansion whose leading term has been calculated can be extended to higher order and whether there is a theorem asserting the existence of a branch for which this is actually an asymptotic approximation. These will not be pursued here.