|
. This work has
been supported by the ANR-10-BLAN 0109 LEDA project.
Abstract
Let be an effective field of
characteristic zero. An effective tribe is a subset of
which is effectively stable under the
-algebra operations, restricted division,
composition, the implicit function theorem, as well as restricted
monomial transformations with arbitrary rational exponents. Given an
effective tribe with an effective zero test, we will prove that an
effective version of the Weierstrass division theorem holds inside the
tribe.
Keywords: Power series, algorithm, Weierstrass preparation, D-algebraic power series, tribe
There are two main aspects about effective computations with formal power series. On the one hand, we need fast algorithms for the computation of coefficients. There is an important literature on this subject and the asymptotically fastest methods either rely on Newton's method [1] or on relaxed power series evaluation [7].
On the other hand, there is the problem of deciding whether a given power series is zero. This problem is undecidable in general, since we need to check the cancellation of an infinite number of coefficients. Therefore, a related subject is the isolation of sufficiently large classes of power series such that most of the common operations on power series can be carried out inside the class, but such that the class remains sufficiently restricted such that we can design effective zero tests.
In section 2, we first recall the most common operations on
formal power series over a field of
characteristic zero: the
-algebra
operations, restricted division, composition, the resolution of implicit
equations, and so called restricted monomial transformations with
arbitrary rational exponents. A subset
of
which is stable under each of these operations will
be called a tribe. We will also specify effective counterparts of these
notions.
The main result of this note is presented in section 4: given an effective tribe with an effective zero test, we show that the tribe also satisfies an effective version of the Weierstrass preparation theorem [10], and we give an algorithm for performing Weierstrass division with remainder. Our result can for instance be applied to the tribes of algebraic power series and D-algebraic power series (see also [4, 5, 9]).
The fact that the collection of all D-algebraic power series satisfies the Weierstrass preparation theorem was first proved in a more ad hoc way by van den Dries [6]. The notion of a tribe also shares some common properties with the notion of a Weierstrass system, as introduced by Denef and Lipshitz [3] and used in [6]. Our main theorem can be regarded as a simpler, effective and more systematic way to prove that certain types of power series form Weierstrass systems.
The idea behind our main algorithm is very simple: given a series of Weierstrass degree
in
, we just compute the
solutions
of the equation
in
inside a sufficiently large field of
grid-based power series. This allows us to compute the polynomial
which we know to be the Weierstrass
polynomial associated to
.
Using the stability of the tribe under restricted monomial
transformations, we will be able to compute
as
an element of
.
The algorithms rely on our ability to compute with the auxiliary
grid-based power series . For
this reason, we briefly recall some basic facts about grid-based power
series in section 3, as well as the basic techniques which
are needed in order to compute with them.
Let be a field of characteristic zero and denote
where we understand that is naturally included
in
for each
.
So each element
is a power series in a finite
number of variables.
We say that is effective if its
elements can be represented by concrete data structures and if all field
operations can be carried out by algorithms. We say that
admits an effective zero test if we also have an
algorithm which takes
on input and which returns
true if
and
false otherwise.
If is effective, then a power series
is said to be computable if we have an effective
bound
for its dimension (so that
), together with an algorithm which takes
on input and produces the coefficient
of
on output. We will denote the
set of computable power series by
.
Let be a subset of
.
We will denote
for each
and say that
is effective if
. In this section, we will give
definitions of several operations on power series and the corresponding
closure properties that
may satisfy. From now
on, we will always assume that
is at least a
-algebra. It is also useful
to assume that
is inhabited in the
sense that
for all
.
For each
, we will denote
and
.
We say that
is stable under
differentiation if
for all
(whence
).
The above closure properties admit natural effective analogues. We say
that is an effective
-algebra if
is an
effective field, if the elements of
can be
represented by concrete data structures and the
-algebra operations can be carried out by
algorithms. We say that
is effectively
inhabited if there is an algorithm which takes
on input and which computes
.
We say that
is effectively stable under
differentiation if there exists an algorithm which takes
and
on input and which computes
.
We say that is stable under restricted
division if
whenever
and
are such that
.
If
is effective, then we say that
is effectively stable under restricted division
if we also have an algorithm which computes
as a
function of
, whenever
. Here we do not assume
the existence of a test whether
(the behaviour
of the algorithm being unspecified if
).
More generally, given
, we
say that
is stable under restricted division
by
if
whenever
, and that
is effectively stable under restricted division by
if this division can be carried out by algorithm.
Given , we let
denote the evaluation of
at
. Given
and
with
,
we define the composition
of
and
to be the unique power series
with
We say that a power series domain is stable
under composition if
for any
and
with
. If we also have an algorithm for the computation
of
, then we say that
is effectively stable under composition.
We notice that stability under composition implies stability under
permutations of the . In
particular, it suffices that
for
to be inhabited. Stability under composition also implies
stability under the projections
with
If is also stable under restricted division by
(whence under restricted division by any
), then this means that we may
compute the coefficients
of the power series
expansion of
with respect to
by induction over
:
Similarly, we obtain stability under the differentiation: for any and
, we
have
Let with
and
. Assume that the matrix formed by
the first
columns of the scalar matrix
is invertible. Then the implicit function theorem implies that there
exist unique power series ,
such that the completed vector
with
satisfies
. We
say that a power series domain
satisfies the
implicit function theorem (for
implicit
functions) if
for the above solution of
, whenever
. We say that
effectively satisfies the implicit function theorem if we also
have an algorithm to compute
as a function of
.
We claim that satisfies the implicit function
theorem for
implicit functions as soon as
satisfies the implicit function theorem for one
implicit function and
is stable under restricted
division and composition. We prove this by induction over
. For
the statement is
clear, so assume that
. Since
is invertible at least one of the
must be non zero. Modulo a permutation of rows we may
assume that
. Applying the
implicit function theorem to
only, we obtain a
function
with
.
Differentiating this relation, we also obtain
for each . Setting
, this yields in particular
Now consider the series . For
each
, we have
In particular,
By the induction hypothesis, we may thus compute series
such that
for all
.
Setting
, we conclude that
and
for all .
Consider an invertible matrix
with rational coefficients. Then the transformation
is called a monomial transformation, where is
considered as a column vector. For a power series
whose support
satisfies
, we may apply the monomial transformation to
as well:
We say that is stable under restricted
monomial transformations if for any
and
invertible matrix
with
, we have
.
We say that
is effectively stable under
restricted monomial transformations if we also have an algorithm to
compute
as a function of
and
. Notice that we do
not require the existence of a test whether
in this case (the behaviour of the algorithm being unspecified whenever
).
If has positive integer coefficients, then we
always have
and
is
trivially stable under the monomial transformation
whenever
is stable under composition.
We say that the -algebra
with
is a local
community if
is stable under composition,
the resolution of implicit equations, and restricted division by
. We say that
is a tribe if
is also stable under
restricted monomial transformations. Effective local communities and
tribes are defined similarly.
A power series is said to be algebraic
if it satisfies a non trivial algebraic equation over the polynomial
ring
. Setting
, this is the case if and only if the module
is a
-vector
space of finite dimension. Using this criterion, it is not hard to prove
that the set
of algebraic power series is a
tribe (and actually the smallest tribe for inclusion). Assume that
is an effective field. Then an effective algebraic
power series
can be effectively represented as
an effective power series together with an annihilator
. It can be shown that
is an effective tribe for this representation.
A power series is said to be
D-algebraic if it satisfies a non trivial algebraic
differential equation
for each
, where
is a non zero
polynomial in
variables with coefficients in
. We denote by
the set of D-algebraic power series. If
is an effective field, then effective D-algebraic power series may again
be represented through an effective power series and differential
annihilators
of the above form. In [9],
one may find more information on how to compute with D-algebraic power
series, and a full proof of the fact that
is an
effective tribe (the proof being based on earlier techniques from [4, 5]).
In what follows, we will only consider commutative monoids. A
monomial monoid is a multiplicative monoid
with an asymptotic partial ordering
which is
compatible with the multiplication (i.e.
and
). We denote by
the set of infinitesimal elements in
and by
the set of bounded
elements in
. We say that
has
-powers
if we also have a powering operation
such that
and
for all
and
.
A monomial monoid is said to be
effective if its elements can be represented by effective data
structures and if we have algorithms for the multiplication and the
asymptotic ordering
. Since
this implies the existence of an effective
equality test. A monomial group
is said to be
effective if it is an effective monomial monoid with an
algorithm for the group inverse. We say that
is
an effective monomial group with
powers
if we also have a computable powering operation.
A subset is said to be grid-based if
there exist finite sets
and
such that
If is actually a group which is generated (as a
group) by its infinitesimal elements, then we may always take
.
If is an effective monomial monoid, then a
grid-based subset
is said to be
effective if the predicate
is
computable and if finite sets
and
with (1) are explicitly given.
Let be a field of characteristic zero. Given a
formal series
with
,
the set
will be called the support of
. We say that the formal
series
is grid-based if its support is
grid-based and we denote by
the set of such
series. A grid-based series
is said to be
infinitesimal or bounded if
resp.
, and we
denote by
resp.
the sets of such series.
In [8, Chapter 2] elementary properties of grid-based
series are studied at length. We prove there that
forms a ring in which all series
with
are invertible. In particular, if
is a totally ordered group, then
forms a field.
Given a power series
and grid-based series
, there is also a natural
definition for the composition
.
Given a grid-based series the maximal elements
of
for
are called
dominant monomials for
.
If
has a unique dominant monomial, then we say
that
is regular, we write
for the dominant monomial of
,
and call
the dominant coefficient of
. If
is totally ordered, then any non zero grid-based series in
is regular.
Assume that and
are
effective. Then a grid-based series
is said to
be effective if its support is effective and if the map
is computable. It can be shown that the set
of computable grid-based series forms an effective
-algebra.
Given an “infinitesimal” indeterminate , the set
is a monomial
monoid for the asymptotic ordering
,
and
coincides with
.
Similarly,
coincides with the field of Laurent
series
and
with the
field of Puiseux series in
over
. If
is algebraically
closed, then so is
.
Given monomial monoids , one
may form the product monomial monoid
with
for all
.
Then
coincides with the set of power series
, whereas
coincides with the set of Laurent series
.
Given monomial monoids , one
may also form the set
whose elements
are ordered anti-lexicographically:
if there exists an
with
and
for all
.
The set
should naturally be interpreted as
(which it is isomorphic to
). The set
is a field which
contains
, and this inclusion
is strict if
(notice also that
). If
is algebraically
closed, then
is again an algebraically closed
field (and again, we have
).
From now on, we will assume that is a monomial
group which is generated as a group by its infinitesimal elements. Given
a series
, a Cartesian
representation for
is a Laurent series
together with monomials
such
that
. Given several series
, and Cartesian
representations for each of the
,
we say that these Cartesian representations are compatible if
they are of the form
for
and
. In [8,
Proposition 3.12] we show that such compatible Cartesian representations
always exist.
In [8, Chapter 3], we give constructive proofs of several
basic facts about Cartesian representations and -based series to be introduced below. These
constructive proofs can easily be transformed into algorithms, so we
will only state the effective counterparts of the main results. First of
all, in order to keep the number of variables
in
Cartesian representations as low as possible, we may use the following
effective variant of [8, Lemma 3.13]:
Lemma
Let be a local community. We will say that
is L-based if
admits
a Cartesian representation of the form
with
,
and
. The set
of all such series forms a
-algebra
[8, Proposition 3.14]. If
,
and
are effective, then
any grid-based series in
is computable.
Moreover, we may effectively represent series in
by Cartesian representations, and
is an
effective
-algebra for this
representation.
A Cartesian representation of
is said to be faithful if for each dominant monomial
of
, there
exists a dominant monomial
of
with
. We have the following
effective counterpart of [8, Proposition 3.19]:
Proposition
Faithful Cartesian representations are a useful technical tool for various computations. They occur for instance in the proof of the following effective counterpart of [8, Proposition 3.20]:
Proposition
Solving power series equations
Assume now that is an effective field with an
effective zero test and an algorithm for determining the roots in
of polynomials in
.
Let
be an effective local community over
and
an effective totally
ordered monomial group. We notice that a grid-based series in
can also be regarded as an ordinary power series in
. We are interested in finding all
infinitesimal solution of a power series equation
where . The Newton polygon
method from [8, Chapter 3] can be generalized in a
straightforward way to power series equations instead of polynomial
equations and the effective counterpart of [8, Theorem
3.21] becomes:
Theorem
Given with
,
we may also consider
as an element of
. Let
be
the dominant of
for this latter representation.
The valuation of
in
is
called the Weierstrass degree of
.
If
is algebraically closed, then it can be shown
that the number of solutions to the equation in Theorem 4
coincides with the Weierstrass degree, when counting with
multiplicities.
Let be an effective field with an effective zero
test. We may consider its algebraic closure
as
an effective field with an effective zero test, when computing non
deterministically (we refer to [2] for more details about
this technique, which is also called dynamic evaluation).
Let be an effective tribe over
with an effective zero test. It is convenient to represent elements of
by polynomials
,
where
. The algebraic number
is effectively represented using an annihilator
and we may always take
such that
. It is a routine
verification that
forms again an effective tribe
for this representation.
Consider a series ,
represented as
, where
is given by an annihilator of degree
. Then we notice that we can compute a
representation for
as a element of
. Indeed, whenever
for
some
, then this means that
there exists a monomial
such that the
coefficient
of
in
is a polynomial of non zero degree in
. On the other hand,
, which means that we can compute an annihilator for
of degree
.
Repeating this reduction a finite number of times, we thus reach the
situation in which
, so that
.
Let still be an effective tribe over
with an effective zero test. Given
, we recall that
is said to
have Weierstrass degree
in
if
, but
. In that case, the Weierstrass
preparation theorem states that there exists unit
and a monic polynomial
of degree
such that
. The
polynomial
is called the Weierstrass
polynomial associated to
.
We claim that
and that there exists an algorithm
to compute
(and therefore the corresponding unit
, since
is effectively stable under restricted division):
Theorem
of Weierstrass degree
on input and computes its
Weierstrass polynomial
as an element of
.
Proof. Consider the effective totally ordered monomial
group with
-powers.
We have a natural inclusion
.
Now consider
. By theorem 4, we may compute all infinitesimal solutions
to the equation
in
(we
recall that there are
such solutions, when
counting with multiplicities, since
is
algebraically closed). Now consider
and let be the Weierstrass polynomial associated
to
. Since
also admits the infinitesimal roots
when
considered as an element of
,
we have
when considering
as an element of
. It follows
that
Now consider a Cartesian representation for
with
. By
Proposition 3, we may take
to be
infinitesimal. Since
are infinitesimal and
, Lemma 1 also shows
that we may assume without loss of generality that
. Completing the
with
additional elements if necessary, this means that we may compute an
invertible matrix
such that
for all
. In other words,
with
.
Since
and
is effectively
closed under restricted monomial transformations, we conclude that
.
Assume that has Weierstrass degree
in
and let
. The Weierstrass division theorem states that there
exists a quotient
and a remainder
in
with
and . We claim that
and
once again belong to
and that there exists an algorithm to compute them:
Theorem of
Weierstrass degree
and
on input and computes the quotient and remainder of the Weierstrass
division of
by
as
elements of
.
Proof. Let be the distinct
solutions of
when considered as an equation in
, and let
be the multiplicity of each
,
so that
. For each
, we compute the polynomials
Using Chinese remaindering, we next compute the unique
such that
for each
and
. It is easily verified that
coincides with the remainder of the Weierstrass
division of
by
.
In particular,
and we may obtain
as an element of
in the same way
as in the proof of Theorem 5. We obtain the quotient
of the Weierstrass division by performing the
restricted division of
by
.
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