1. Introduction
Let
denote the algebra of polynomials in
d variables with complex coefficients. A projector
P on
is a linear idempotent operator on
. Such a projector is called an ideal projector if
is an ideal in
. An ideal projector is called a Lagrange projector if
is a radical ideal in
. If the range of
P is
N-dimensional, then
P is a Lagrange projector if and only if there exist
N distinct points
such that
or equivalently
for all
and all
. The last equivalence shows that Lagrange projectors interpolate at nodes
and therefore present a natural extension of the classical Lagrange interpolation theory to the multivariate setting.
The notion of an ideal projector was first introduced by Birkhoff in [
1]. Since then, it was further studied, and connections to different branches of mathematics were explored (see [
2,
3,
4,
5,
6,
7,
8,
9,
10,
11]). In this paper, we consider exclusively finite dimensional ideal projectors.
In one variable, every Hermite interpolation projector is the limit of a sequence of classical Lagrange interpolation projectors. That allows us to extend the definition of the Hermite interpolation projectors to the multivariate setting as follows.
Definition 1. An ideal projector P is called a Hermite projector if there exist a sequence of Lagrange projectors on the range of P such thatfor every . We do not specify type of convergence because and belong to the same finite-dimensional space; hence, all forms of convergence are equivalent. In one variable setting, the ideal projectors are the same as classical Hermite projectors (see for example [
10]). The natural question arises as to whether, in the multivariate setting, the same is true, i.e., is any ideal projector necessarily a limit of Lagrange projectors? Rather surprisingly, the resulting answer is positive in two variables (cf. [
4]) but negative in three or more variables (cf. [
12]). The question of a description of those ideal projectors that are Hermite was raised by Carl de Boor in [
3]. Some partial results regarding this question were obtained in [
8,
9] and, in the very different language of algebraic geometry, in [
13,
14]. In this paper, we make a contribution to this problem by examining the primary decomposition of Hermite projectors.
Every finite-dimensional ideal projector
P can be written as a finite (direct) sum of ideal projectors
where
are ideal projectors such that the ideals
form the primary decomposition of the ideal
. That is
and, for each
, the variety
consists of exactly one point.
The main result of this paper is
Theorem 1. P is Hermite if and only if each is Hermite.
Based on the above theorem, as an application, we will show the existence of a symmetric ideal projector (in three or more variables) that is not Hermite (see Theorem 7). Finally, we will showcase some problems in matrix theory (see Problem 2) that are related to the main result.
2. Preliminaries
Let
denote the algebraic dual of
, i.e., the space of all linear functionals on
. For an ideal
, let
denote the affine variety associated with
J:
The ideal
J has a finite codimension (0-dimensional) if and only if the set
is finite (cf. [
15]). Moreover,
and
if and only if the ideal
J is radical i.e.,
Let
denote a subspace of
of all functionals that vanish on
J. Hence
For
, we use
to denote the point evaluation functional:
It is easy to see that for any
N-dimensional Lagrange interpolation projector
P, the variety
is consisting of exactly
N distinct points. Assuming
, we have
Below, we will review relations between ideal projectors and the sequence of commuting matrices.
Let
P be an
N-dimensional ideal projector and let
G be its range. Hence,
and
is an ideal of codimension
N in
. Thus,
is an
N-dimensional algebra. For each coordinate
of
, we define a multiplication operator (
matrix)
associated with
P by
where
represents a class equivalence in
. The set
forms a sequence of commuting matrices that are associated with the projector
P. In fact, such a sequence uniquely defines
P (see [
4] for details). The matrices
represent the operators defined on
G by
The matrices
were introduced by Hans Stetter (cf. [
11,
16,
17]) who discovered the main relation between common eigenvalues (eigentuples) of these matrices and the variety
.
Definition 2. A d-tuple of complex numbers is called an eigentuple for if there exists a non-zero vector such thatLet denote the set of all eigentuples of the commuting matrices . Theorem 2 ([
17])
. . Theorem 3 (cf. [
4])
. Suppose that we have a sequence of ideal projectors onto the same space G and let be multiplication operators associated with while is the multiplication operators on G associated with P. Then, if and only if . Next, we prove an extension of Theorem 5.2.1 in Artin [
18] to the set of commuting matrices. Our proof is substantially different than the one presented there.
Theorem 4. Let and be a d-tuple of operators on an N-dimensional space G. Assume that . Then, the sets are uniformly bounded and all accumulation points of are in .
Proof. Let
, hence
Assume without loss of generality that
. Then
and since
converges, the norms
are uniformly bounded, which proves the first part of the theorem. Now, passing to a subsequence if necessary, we may assume that
. Then,
. The sequence
is uniformly bounded in a finite-dimensional space
G; hence, it is compact. Passing to a subsequence if necessary, we may assume that
and
. Finally, since
are finite-dimensional operators, the convergence is uniform. Therefore
In addition,
, hence
. □
Combining the above with the Theorem 2, we obtain:
Corollary 1. Let P be an N-dimensional Hermite projector and be a sequence of Lagrange projectors such that . If and . Then, there exists a constant C such that for all k and n. Additionally, are the only possible limit points of the set .
Now, we will recollect a few facts regarding the convergence of ideal projectors. The main idea is that such a convergence depends only on their respective kernels. For more details and proofs, see [
12].
Theorem 5 (cf. [
12])
. Let and P be ideal projectors onto a finite-dimensional space . Then, if and only if for every functional , there exists a sequence of functionals such that in the weak-⋆ topology. i.e., If each is a Lagrange projector, then is spanned by N point evaluation functionals , and each can be written as their linear combination. Using the above theorem, we obtain the following.
Corollary 2. An N-dimensional ideal projector P is Hermite if and only if every is the weak-⋆ limit of linear combinations of N point evaluation functionals. That is, there exists sets , each consisting of N distinct points such that for every for some coefficients and for all . 3. The Main Result
The main goal is to prove Theorem 1. One side is easy to establish and can be shown as follows. Let
P be an
N-dimensional ideal projector and assume that
has a primary decomposition
where the ideals
have codimensions equal to
, respectively. Since
we have
. Take any
. Then,
for some
. If each
is the kernel of a Hermite projector then, by Corollary 2, there exists sets
consisting of
distinct points such
It follows that
and therefore,
F is a weak-⋆ limit of a linear combination of
N point evaluations. By Corollary 2,
P is Hermite.
The main result of this section is a proof of the converse statement. The main idea is as follows. Assume
P is Hermite,
and
has a primary decomposition
. By Corollary 2, there exists sets
such that (
6) holds. Let
. We will decompose
so that all accumulation points of
are away from
. For every functional
(in particular, every functional
), we have
for some coefficients
and for all
. The main part of the proof is to show that the above implies that
Thus, in (
7), we can eliminate all point evaluations that do not accumulate at
, and the number of points remaining is equal to
. Hence, by Corollary 2, the projector
is Hermite.
To carry the proof in detail, we need a few preliminary results. First, we will produce a multivariate analog of Lagrange fundamental polynomials that seems to be new.
Proposition 1. Let be a finite set of m points in and take such that and lie in the interior of a ball of radius R. Let Then, there exists a constant and polynomial of degree at most m such thatand(here, denotes the supremum of the polynomial ω over the ball ). Proof. Let
denote the Hermitian inner product in the space
. Consider the following polynomial
Since is a linear polynomial in , is a polynomial of degree at most m. Clearly, for all and .
Since
lie in a ball of radius R
Combining these two inequalities together yields □
We will also need the following lemma.
Lemma 1. Let and be two sequences in such thatfor all . Then, as . Proof. By induction on m, if , then and immediately implies that .
Assume that the statement is true for a fixed
m. Now, we need to show that the statement is true for
. Take any
and
such that
for
and
The goal is to show that
. Since
, from the above, we obtain
for
. Hence
for all
. Setting
the above gives
By the inductive assumption applied to
and
, we conclude that
Hence
Setting
in (
10), we obtain
Combining these two gives
Since , we conclude that as required. □
We are now ready for the proof of the main theorem.
Theorem 6. Let P be a Hermite projector onto an N-dimensional space . Suppose thatwhere are ideal projectors such that the ideals form the primary decomposition of the ideal Then, each is Hermite.
Proof. We will start with
. Assume that
and
. Since
P is Hermite, by Corollary 2, for every functional
for every
. In particular, if
, then due to (
12),
and hence (
13) holds. By Corollary 1, the sets
lie in some ball in
of radius
R and
are the only accumulation points of
Partition the points
so that for every sequence
, we have
and, for sufficiently large
n, the points
are arbitrarily close to the set
. In particular,
We rewrite (
13) as
where the points in
and
satisfy (
15) and (
14), respectively. Now, let
p be a polynomial in
such that
. Such a polynomial exists since, otherwise, every polynomial in
would vanish at
and hence
. Next, consider polynomials
for
where
is defined as in Proposition 1, and
f is arbitrary. Since
p is in the ideal
so are
, hence
. By the same proposition and by (
14), these polynomials are uniformly bounded and belong to a finite-dimensional space of polynomials of degree
. Thus, the convergence (
16) on this space is uniform, and (
16) gives
Furthermore, since
vanishes on
, it follows that
for
. Finally, since
is the limit point of
Setting
for
and applying Lemma 1, we conclude that
Thus, we eliminate the points that accumulate at
from the sum in (
16). Since this implies (
6) holds for
, we can repeat this procedure, eliminating all points from
in the sum (
13) that accumulates at
. We arrive at the sequences of sets
that have an accumulation point at
such that every
F in
Thus, for sufficiently large
n, the dimension of this space must be greater or equal to the dimension of the space
. Hence
. Repeating this procedure for the rest of the points
, we will obtain a disjoint partition of
:
such that for every
and
Hence, for sufficiently large n, we have . By Corollary 2, we obtain that each is Hermite. □
4. Some Applications
The first application of the main theorem is to show the existence of a symmetric ideal projector (in three or more variables) that is not Hermite.
Definition 3. An ideal J in is called symmetric if for any polynomial in J and for any permutation σ on the set , the polynomial is also in J. An ideal projector P is called symmetric if is a symmetric ideal.
Theorem 7. In three or more variables, there exists a finite-dimensional symmetric ideal projector that is not Hermite.
Proof. The result follows from the existence of a finite-dimensional non-Hermite ideal projector
Q such that
is primary, i.e.,
consists of one point. We chose such
Q so that
. Now, for every permutation
σ, consider the ideal
with
. Then, clearly, the ideal
is a symmetric ideal and (
20) is a primary decomposition of this ideal. Let
P be an ideal projector with
. Then,
P is a symmetric ideal projector. If
P was a Hermite projector, then, by the Theorem 6,
Q would also be Hermite, which gives us a contradiction. □
Problem 1. Does there exist a non-Hermite ideal projector P such that P is symmetric and , i.e., is primary?
Our second application concerns linear algebra. A sequence of commuting matrices is called simultaneously diagonalizable if there exists an matrix S such that the matrices are diagonal matrices. We have the following.
Theorem 8 ([
12])
. Let P be an ideal projector. Then, P is a Lagrange projector if and only if the sequence of matrices associated with P by (4) is simultaneously diagonalizable. The ideal projector P is Hermite if and only if the sequence of matrices associated with P by (4) is a limit of a sequence of simultaneously diagonalizable matrices. Commuting matrices that are limits of simultaneously diagonalizable matrices have received a fair amount of attention (cf. [
13,
19,
20]). The following result was proved in [
5]:
Theorem 9. Let P be an ideal projector onto the N-dimensional subspace V and letbe the primary decomposition of P. Then, - (i)
has a unique (up to order of blocks) block diagonalization consisting of m blocks and m is the maximal number of blocks in any block-diagonalization of .
- (ii)
Each block defines a distinct primary ideal.
Under the assumptions of the above, we can set
(where all
have the same size) and
where
Observe that defines a sequence of commuting matrices.
It is clear that if each sequence is a limit of simultaneously diagonalizable matrices , then is a limit of simultaneously diagonalizable matrices. Our main Theorem 6 asserts that the converse is also true. That is, if is a limit of simultaneously diagonalizable matrices, then the sequences of maximal blocks are also limits of simultaneously diagonalizable sequences. This leads to an interesting question about the extension of this result to an arbitrary commuting block-diagonal sequence of matrices.
Problem 2. Let be a sequence of commuting matrices such that each is block diagonal, i.e., of the form of (21). Let be of the same size and commute. Suppose that is a limit of simultaneously diagonalizable matrices. Does it imply that each sequence is a limit of simultaneously diagonalizable matrices? Remark 1. In the language of algebraic geometry, the ideals that serve as kernels of Hermite projectors are called "smoothable" (cf. [14]). Hence, the main result of this paper formulated in this language says that an ideal J is smoothable if and only if every ideal in the primary decomposition of J is smoothable.