Last October, Romain Dujardin gave a nice talk at Bourbaki seminar about the equidistribution of Fekete points, pluripotential theory and the works of Robert Berman, Sébastien Boucksoum and David Witt Nyström(including this article here). The video of Dujardin’s talk (in French) is available here and the corresponding lecture notes (also in French) are available here.
In the sequel, I will transcript my notes for Dujardin’s talk (while referring to his text for all omitted details). In particular, we will follow his path, that is, we will describe how a question related to polynomial interpolation was solved by complex geometry methods, but we will not discuss the relationship of the material below with point processes.
Remark 1 As usual, any errors/mistakes in this post are my sole responsibility.
1. Polynomial interpolation and logarithmic potential theory in one complex variable
1.1. Polynomial interpolation
Let be the vector space of polynomials of degree
in one complex variable. By definition,
.
The classical polynomial interpolation problem can be stated as follows: given points
on
, can we find a polynomial with prescribed values at
‘s? In other terms, can we invert the evaluation map
,
?
The solution to this old question is well-known: in particular, the problem can be explicitly solved (whenever the points are distinct).
What about the effectiveness and/or numerical stability of these solutions? It is also well-known that they might be “unstable” in many aspects: for instance, the inverse of starts to behave badly when some of the points
get close together, a small error on the values
might lead to huge errors in the polynomial
, Runge’s phenomenon shows that certain interpolations about equidistant point in
are highly oscillating, etc.
This motivates the following question: are there “optimal” choices for the points (leading to “minimal instabilities” in the solution of the interpolation problem)?
This vague question can be formalized in several ways. For instance, the interpolation problem turns out to be a linear algebra question asking to invert an appropriate Vandermonde matrix and, a fortiori, the calculations will eventually oblige us to divide by an adequate determinant
. Hence, if we denote by
,
, the base of monomials of
, then we can say that an optimal configuration maximizes the modulus of Vandermonde’s determinant
Of course, this optimization problem has a trivial solution if we do not impose constraints on . For this reason, we shall fix some compact subset
and we will assume that
.
Definition 1 A Fekete configuration
is a maximum of
Definition 2 The
-diameter of
is
where
is a Fekete configuration.
It is not hard to see that , i.e.,
is a decreasing sequence.
Definition 3
is the transfinite diameter.
The transfinite diameter is related to the logarithmic potential of .
1.2. Logarithmic potential
In the one-dimensional setting, the equidistribution of Fekete configurations towards an equilibrium measure was established by Fekete and Szegö.
Theorem 4 (Fekete, Szegö) If
and
is a sequence of Fekete configurations, then the sequence of probability measures
converges in the weak-* topology to the so-called equilibrium measure
of
.
Proof: Let us introduce the following “continuous” version of Fekete configurations. Given a measure on
, its “energy” is
so that if we forget about the “diagonal terms” , then
. Recall that the capacity of
is
where
(and
stands for the space of probability measures on
).
Theorem 5 (Frostman) Either
is polar, i.e.,
for all
or there is an unique
with
.
We are not going to prove this result here. Nevertheless, let us mention that an important ingredient in the proof of Frostman’s theorem is the logarithmic potential associated to
: it is a subharmonic function whose (distributional) Laplacian is
. A key feature of the logarithmic potential is the fact that if
, then
for
-almost every
: observe that this allows to conclude the uniqueness of
because it would follow from
that
is harmonic, “basically” zero on
, and
near infinity.
Anyhow, it is not hard to deduce the equidistribution of Fekete configurations towards from Frostman’s theorem. Indeed, let
be
and consider the modified energy
. A straighforward calculation (cf. the proof of Théorème 1.1 in Dujardin’s text) reveals that if
is a converging subsequence, say
, then
.
1.3. Two remarks
The capacity of admits several equivalent definitions: for instance, the quantities
form a submultiplicative sequence (i.e., ) and the so-called Chebyshev constant
coincides with . In other terms, the capacity of
is the limit of certain geometrical quantities
associated to a natural norm
on the spaces of polynomials
.
Also, it is interesting to consider the maximization problem for weighted versions
of the energy of measures.
As it turns out, these ideas play a role in higher dimensional context discussed below.
2. Pluripotential theory on
Denote by the space of polynomials of degree
on
complex variables: it is a vector space of dimension
as
.
Let be a compact subset of
and consider
. Similarly to the case
, the interpolation problem of inverting the evaluation map
involves the computation of the determinant
where
is the base of monomials. Once again, we say that a collection
of
points in
maximizing the quantity
is a Fekete configuration and the transfinite diameter of
is
where
is the –diameter of
.
Given the discussion of the previous section, it is natural to ask the following questions: do Fekete configurations equidistribute? what about the relation of the transfinite diameter and pluripotential theory?
A first difficulty in solving these questions comes from the fact that it is not easy to produce a “continuous” version of Fekete configurations via a natural concept of energy of measures having all properties of the quantity in the case
.
A second difficulty towards the questions above is the following: besides the issues coming from pairs of points which are too close together, our new interpolation problem has new sources of instability such as the case of a configuration of points lying in an algebraic curve. In particular, this hints that some techniques coming from complex geometry will help us here.
The next result provides an answer (comparable to Frostman’s theorem above) to the second question:
Theorem 6 (Zaharjuta (1975)) The limit of
exists. Moreover, if
is not pluripolar, then
.
Here, we recall that a pluripolar set is defined in the context of pluripotential theory as follows. First, a function on a open subset
is called plurisubharmonic (psh) whenever
is upper semicontinuous (usc) and
is subharmonic for any
holomorphic curve. Equivalently, if
, then
is psh when
is usc and the matrix of distributions
is positive-definite Hermitian, i.e.,
. Next,
is pluripolar whenever
where
is a psh function.
An important fact in pluripotential theory is that the positive currents can be multiplied: if
are bounded psh functions, then the exterior product
can be defined as a current. In particular, we can define the Monge-Ampère operator
on the space of bounded psh functions.
Note that is a positive current of maximal degree, i.e., a positive measure. This allows us to define a candidate for the equilibrium measure in higher dimensions in the following way.
Let
be the so-called Lelong class of psh functions. Given a compact subset , let
Observe that is a natural object: for instance, it differs only by an additive constant from the logarithmic potential of the equilibrium measure of
when
. Indeed, this follows from the key property of the logarithmic potential (“
implies
for
-almost every
”) mentioned earlier and the fact that
is a subharmonic function which essentially vanishes on
.
In general, is not psh. So, let us consider the psh function given by its usc regularization
. Note that
, so that we can define the equilibrium measure of
as
It is worth to point out that can be recovered from the study of polynomials (in a similar way to our discussion of the Chebyshev constant in the previous section). More concretely, we have
for all
and a result of Siciak ensures that
Finally, note that this discussion admits a weighted version where the usual Euclidean norm on
is replaced by
, the determinant
is replaced by
, etc.
3. Bernstein–Markov property
Let be a probability measure on
giving zero mass to all pluripolar subsets. Since algebraic subvarieties are pluripolar (because they are included in the locus
of some polynomial
), we have that
gives no weight to algebraic subvarieties. Hence, a polynomial
with
must vanish, i.e.,
.
It follows that is equivalent to the uniform norm
on the finite-dimensional vector spaces
, i.e., there is a (best) constant
such that
for all .
Definition 7 We say that
has the Bernstein–Markov property if
.
The following result ensures that one can “always” work with measures enjoying the Bernstein–Markov property:
Theorem 8 (Bloom–Levenberg) Every non-pluripolar compact subset
supports a probability measure with the Bernstein–Markov property.
Moreover, if where
is an open subset of
with smooth boundary, then the equilibrium measure
has the Bernstein–Markov property (see this paper here):
Theorem 9 (Siciak) If
is regular (i.e.,
is continuous), then
has the Bernstein–Markov property.
The Bernstein–Markov property is useful because it allows to interpret the transfinite diameter as the growth rate of certain volumes in the spaces of polynomials.
More concretely, let be a non-pluripolar set and
a probability measure with the Bernstein–Markov property.
Lemma 10 One has
with
.
Lemma 11 One has
Since the volumes of the unit balls of a vector space equipped with two Hermitian structures
and
are given by a Gram determinant, i.e.,
where is an orthonormal basis with respect to
, one gets from this fact and the previous two lemmas (whose [elementary] proofs are omitted) that
where is the Haar measure on the torus
and
is the unit ball of
with respect to the Hermitian structure
. (Here, it is natural to introduce
because the base
of monomials of
is orthonormal with respect to
.)
In summary, we saw that the transfinite volume is related to the quotients of volumes of unit balls in the spaces of polynomials. In the last part of this post, we will investigate the problem of understanding quotients of volumes of unit balls in the more general setting of sections of positive vector bundles over complex manifolds.
4. Global pluripotential theory
Let be a compact complex manifold of dimension
. Suppose that
is an ample line bundle, i.e., there is a smooth metric
which is strictly psh (in the sense that any local trivialization
of
has the property that
with
).
By the asymptotic Riemann-Roch theorem, the dimensions of the spaces of sections of the
th tensor power
of
verify
as , where
is the volume of
.
Example 1 For the line bundle
over the complex projective space
, the space
identifies with
(in a given chart of
)
Let us fix a reference metric whose curvature form is denoted by
. Note that all metrics on
have the form
where
is a function. We say
is semi-positive (i.e.,
) whenever
is psh in the sense that
.
Given a smooth positive measure on
and a metric
on
, one has a natural
-structure
on
, namely
where stands for the metric induced on
by
.
Theorem 12 (Berman–Boucksoum) Let
,
be two smooth positive measures and
,
two metrics on
. Then,
where
is the Monge-Ampère energy of
.
(Here, we insist on the quotients of volumes because the volumes are well-defined only up to a multiplicative constant.)
The Monge-Ampère energy is an interesting functional playing the role of a primitive of the Monge-Ampère operator in the sense that
The idea of proof of Berman–Boucksoum theorem above goes along the following lines (cf. this article here for more details). We write where
is a path connecting
and
. The quotient of volumes in the left-hand side is a Gramm determinant (similar to (1)) with respect to an appropriate choice of basis of sections of
and its derivative is the so-called Bergman kernel. In particular, the desired result comes from a comparison between Monge-Ampère operators and Bergman kernels.
For some applications of this result (e.g., to the study of Fekete configurations), it is important to improve this theorem to the case of general measures and
. As it turns out, this is done by considering the quotients of volumes with respect to
norms on
induced by the metrics and the Monge-Ampère energies of certain functions
playing the analog role of the functions
introduced above in the context of compact subset
.
Anyhow, let us close this post by explaining how this technology can be used to get the equidistribution of Fekete points in higher dimensional settings.
5. Equidistribution of Fekete configurations
We saw that the transfinite diameter is related to the quotient of two volumes (cf. (2)). In order to exploit this fact, we need the following result of Berman–Boucksoum.
Theorem 13 (Berman–Boucksoum) The Monge-Ampère energy
is differentiable with respect to
, namely
Remark 2 The Monge-Ampère measure
is the candidate to the equilibrium measure.
Besides the previous theorem, we also need a technical fact about concave functions of the real line:
Lemma 14 Let
be a sequence of (differentiable) concave functions defined in a neighborhood
of
. If
is a (differentiable) concave function on
such that
and
then
.
At this point, the idea is to derive the equidistribution of Fekete configurations
towards an equilibrium measure
in higher dimensional settings from the previous lemma applied to the geometric functionals
and
because a straightforward calculation reveals that
and Theorem 13 and (the generalization to arbitrary measures of) Theorem 12 yield
Remark 3 After the end of the talk, I asked Romain about speed of equidistribution of Fekete points and he pointed out to me that such results were recently obtained by T.-C. Dinh, X. Ma and V.-A. Nguyên.
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