A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian
We consider compact Grassmann manifolds G/K over the real, complex or quaternionic numbers whose spherical functions are Heckman-Opdam polynomials of type BC. From an explicit integral representation of these polynomials we deduce a sharp Mehler-Heine formula, that is an approximation of the Heckman...
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Rösler, M. Voit, M. 2019-02-12T18:12:01Z 2019-02-12T18:12:01Z 2015 A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian / M. Rösler, M. Voit // Symmetry, Integrability and Geometry: Methods and Applications. — 2015. — Т. 11. — Бібліогр.: 32 назв. — англ. 1815-0659 2010 Mathematics Subject Classification: 33C52; 43A90; 60F05; 60B15; 43A62; 33C80; 33C67 DOI:10.3842/SIGMA.2015.013 https://nasplib.isofts.kiev.ua/handle/123456789/146999 We consider compact Grassmann manifolds G/K over the real, complex or quaternionic numbers whose spherical functions are Heckman-Opdam polynomials of type BC. From an explicit integral representation of these polynomials we deduce a sharp Mehler-Heine formula, that is an approximation of the Heckman-Opdam polynomials in terms of Bessel functions, with a precise estimate on the error term. This result is used to derive a central limit theorem for random walks on the semi-lattice parametrizing the dual of G/K, which are constructed by successive decompositions of tensor powers of spherical representations of G. The limit is the distribution of a Laguerre ensemble in random matrix theory. Most results of this paper are established for a larger continuous set of multiplicity parameters beyond the group cases. en Інститут математики НАН України Symmetry, Integrability and Geometry: Methods and Applications A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian Article published earlier |
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A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian |
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A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian Rösler, M. Voit, M. |
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A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian |
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A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian |
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A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian |
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A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian |
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central limit theorem for random walks on the dual of a compact grassmannian |
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Rösler, M. Voit, M. |
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We consider compact Grassmann manifolds G/K over the real, complex or quaternionic numbers whose spherical functions are Heckman-Opdam polynomials of type BC. From an explicit integral representation of these polynomials we deduce a sharp Mehler-Heine formula, that is an approximation of the Heckman-Opdam polynomials in terms of Bessel functions, with a precise estimate on the error term. This result is used to derive a central limit theorem for random walks on the semi-lattice parametrizing the dual of G/K, which are constructed by successive decompositions of tensor powers of spherical representations of G. The limit is the distribution of a Laguerre ensemble in random matrix theory. Most results of this paper are established for a larger continuous set of multiplicity parameters beyond the group cases.
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A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian / M. Rösler, M. Voit // Symmetry, Integrability and Geometry: Methods and Applications. — 2015. — Т. 11. — Бібліогр.: 32 назв. — англ. |
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AT roslerm acentrallimittheoremforrandomwalksonthedualofacompactgrassmannian AT voitm acentrallimittheoremforrandomwalksonthedualofacompactgrassmannian AT roslerm centrallimittheoremforrandomwalksonthedualofacompactgrassmannian AT voitm centrallimittheoremforrandomwalksonthedualofacompactgrassmannian |
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2025-11-27T04:31:13Z |
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Symmetry, Integrability and Geometry: Methods and Applications SIGMA 11 (2015), 013, 18 pages
A Central Limit Theorem for Random Walks
on the Dual of a Compact Grassmannian
Margit RÖSLER † and Michael VOIT ‡
† Institut für Mathematik, Universität Paderborn,
Warburger Str. 100, D-33098 Paderborn, Germany
E-mail: roesler@math.upb.de
‡ Fakultät für Mathematik, Technische Universität Dortmund,
Vogelpothsweg 87, D-44221 Dortmund, Germany
E-mail: michael.voit@math.uni-dortmund.de
Received October 14, 2014, in final form February 03, 2015; Published online February 10, 2015
http://dx.doi.org/10.3842/SIGMA.2015.013
Abstract. We consider compact Grassmann manifolds G/K over the real, complex
or quaternionic numbers whose spherical functions are Heckman–Opdam polynomials of
type BC. From an explicit integral representation of these polynomials we deduce a sharp
Mehler–Heine formula, that is an approximation of the Heckman–Opdam polynomials in
terms of Bessel functions, with a precise estimate on the error term. This result is used to
derive a central limit theorem for random walks on the semi-lattice parametrizing the dual
of G/K, which are constructed by successive decompositions of tensor powers of spherical
representations of G. The limit is the distribution of a Laguerre ensemble in random matrix
theory. Most results of this paper are established for a larger continuous set of multiplicity
parameters beyond the group cases.
Key words: Mehler–Heine formula; Heckman–Opdam polynomials; Grassmann manifolds;
spherical functions; central limit theorem; asymptotic representation theory
2010 Mathematics Subject Classification: 33C52; 43A90; 60F05; 60B15; 43A62; 33C80;
33C67
1 Introduction
For Riemannian symmetric spaces G/K of the compact or non-compact type, there is a well-
known contraction principle which states that under suitable scaling, the spherical functions ϕλ
of G/K tend to the spherical functions ψλ of the tangent space of G/K in the base point, which
is a symmetric space of the flat type:
lim
n→∞
ϕnλ(exp(x/n)) = ψλ(x).
See [4] and, for a more recent account, [2]. This curvature limit, also known as Mehler–Heine
formula, extends to the more general setting of hypergeometric functions associated with root
systems, which converge under rescaling to generalized Bessel functions. This is proven in [6] by
a limit transition in the Cherednik operators; see also [2] for a different approach. In the compact
rank one case, the contraction principle is a weak version of the classical Hilb formula for Jacobi
polynomials (see [27, Theorem 8.21.12]), which provides in addition a precise estimate on the
rate of convergence. In this paper, we prove a Mehler–Heine formula with a precise estimate
on the error term for a certain class of orthogonal polynomials associated with root systems,
which in particular encompasses the spherical functions of compact Grassmannians. This result
is a “compact” analogue of Theorem 5.4 in [26], which gives a scaling limit with error bounds for
hypergeometric functions in the dual, non-compact setting. In the second part of the paper, we
mailto:roesler@math.upb.de
mailto:michael.voit@math.uni-dortmund.de
http://dx.doi.org/10.3842/SIGMA.2015.013
2 M. Rösler and M. Voit
shall use the Mehler–Heine formula 2.4 in order to establish a central limit theorem for random
walks on the semi-lattice of dominant weights parametrizing the unitary dual of a compact
Grassmannian.
To become more precise, we consider the compact Grassmannians Gp,q(F) = G/K over one
of the (skew-) fields F = R,C,H, with G = SU(p + q,F) and K = S(U(q,F)× U(p,F)), where
p ≥ q ≥ 1. Via polar decomposition of G, the double coset space G//K = {KgK : g ∈ G} may
be topologically identified with the fundamental alcove
A0 :=
{
x = (x1, . . . , xq) ∈ Rq :
π
2
≥ x1 ≥ x2 ≥ · · · ≥ xq ≥ 0
}
,
with x ∈ A0 being identified with the matrix
ax =
cosx − sinx 0
sinx cosx 0
0 0 Ip−q
.
Here we use the diagonal matrix notation x = diag(x1, . . . , xq), and the functions sin, cos
are understood component-wise. For details, see [23, Theorem 4.1]. The spherical functions
of Gp,q(F) can be viewed as Heckman–Opdam polynomials of type BCq, which are also known
as multivariable Jacobi polynomials. They may be described as follows: denote by FBC(λ, k; ·)
the Heckman–Opdam hypergeometric function associated with the root system
R = 2BCq = {±2ei,±4ei : 1 ≤ i ≤ q} ∪ {±2ei ± 2ej : 1 ≤ i < j ≤ q} ⊂ Rq,
with spectral variable λ ∈ Cq and multiplicity parameter k = (k1, k2, k3) ∈ R3 corresponding to
the roots ±2ei, ±4ei and 2(±ei ± ej). Fix the positive subsystem
R+ = {2ei, 4ei, 1 ≤ i ≤ q} ∪ {2ei ± 2ej , 1 ≤ i < j ≤ q}
and the associated semi-lattice of dominant weights,
P+ =
{
λ ∈ (2Z)q : λ1 ≥ λ2 ≥ · · · ≥ λq ≥ 0
}
.
Then the set of spherical functions of Gp,q(F) is parametrized by P+ and consists of the functions
ϕpλ(ax) = FBC(λ+ ρp, k(p), ix) =: Rpλ(x), λ ∈ P+ (1.1)
with multiplicity parameter
k(p) = (d(p− q)/2, (d− 1)/2, d/2), (1.2)
where d = dimR F ∈ {1, 2, 4} and
ρp =
1
2
∑
α∈R+
kαα =
q∑
i=1
(
d
2
(p+ q + 2− 2i)− 1
)
ei.
The functions Rpλ are the Heckman–Opdam polynomials associated with the root system R
(called Jacobi polynomials in the following) and with multiplicity k(p), normalized according
to Rpλ(0) = 1. We refer to [12, 13, 22] for Heckman–Opdam theory in general, and to [23] and
the references cited there for the connection with spherical functions in the compact BC case.
Notice that our notion of FBC coincides with that of Heckman, Opdam and [25, 26], while it
differs from the geometric notion in [23]. Theorem 4.3 of [23] corresponds to (1.1).
In Theorem 4.2 of [23], the product formula for spherical functions of (G,K) was written as
a formula on A0 and analytically extended to a product formula for the Jacobi polynomials Rpλ
A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian 3
with multiplicity k(p) corresponding to arbitrary real parameters p > 2q − 1. This led to
three continuous series of positive product formulas for Jacobi polynomials corresponding to
F = R,C,H and to associated commutative hypergroup structures on A0; see [15] and [3] for the
notion of hypergroups. Using a Harish-Chandra-type integral representation for the Rpλ, we shall
derive a Mehler–Heine formula with a precise asymptotic estimate for the Jacobi polynomials Rpλ
in terms of Bessel functions associated with root system Bq on the Weyl chamber
C = {x = (x1, . . . , xq) ∈ Rq : x1 ≥ · · · ≥ xq ≥ 0}.
This Mehler–Heine formula will be the key ingredient for the main result of the present paper,
a central limit theorem for random walks on the semi-lattice P+, which parametrizes the spherical
unitary dual of G/K. To explain this CLT, let us first recall that via the GNS representation,
the spherical functions ϕλ, λ ∈ P+ of (G,K), which are necessarily positive definite, are in a one-
to-one correspondence with the (equivalence classes of) spherical representations (πλ, Hλ) of G,
that is those irreducible unitary representations of G whose restriction to K contains the trivial
representation with multiplicity one, see [9] or [14, Chapter IV]. The decomposition of tensor
products of spherical representations into their irreducible components leads to a probability
preserving convolution ∗d,p and finally a Hermitian hypergroup structure on the discrete set P+;
see [7] and [18]. Following, e.g., [3, 29, 32], we introduce random walks (Sd,pn )n≥0 on P+ associated
with ∗d,p and derive some limit theorems for n→∞. The main result of this paper will be the
Central Limit Theorem 3.12. This CLT implies the following result for Gp,q(F) = G/K:
Theorem 1.1. Let (πλ, Hλ) be a non-trivial spherical representation of G associated with λ ∈
P+ \ {0}. Let uλ ∈ Hλ be K-invariant with ‖uλ‖ = 1. For each n ∈ N, decompose the n-fold
tensor power (π⊗,nλ , H⊗,nλ ) into its finitely many irreducible unitary components
(
π⊗,nλ , H⊗,nλ
)
=
(⊕
τn
πτn ,
⊕
τn
Hτn
)
,
where the components are counted with multiplicities. Consider the orthogonal projections pτn :
H⊗,nλ → Hτn and a P+-valued random variable Xn,λ with the finitely supported distribution∑
τn
∥∥pτn(u⊗,nλ )
∥∥2δτn ∈M1(P+)
with the point measures δτn at τn. Then, for n→∞,
Xn,λ
m(λ)
√
n
tends in distribution to
dρd,p(x) = c−1d,p
q∏
j=1
x
d(p−q+1)−1
j
∏
1≤i<j≤q
(
x2i − x2j
)d
e−(x
2
1+···+x2q)/2 dx ∈M1(C)
with a suitable normalization cd,p. Notice that the probability measure dρd,p is the distribution
of a Laguerre ensemble on C. The modified variance parameter m(λ) > 0 is a second order
polynomial in λ and given explicitly in Lemma 3.3 below.
For q = 1, the Central Limit Theorem 3.12 has a long history as a CLT for random walks
on Z+ whose transition probabilities are related to product linearizations of Jacobi polynomials.
This includes random walks on the duals of SU(2) and (SO(n),SO(n − 1)) in [8] and [11]. See
also [29] for further one-dimensional cases. For q ≥ 2 our results are very closely related to the
work [5] of Clerc and Roynette on duals of compact symmetric spaces. For a survey on limits
for spherical functions and CLTs in the non-compact case for q = 1 we refer to [31].
4 M. Rösler and M. Voit
2 A Mehler–Heine formula
In this section we derive a Mehler–Heine formula for the Jacobi polynomials Rpλ(λ ∈ P+),
describing the approximation of these polynomials in terms of Bessel functions with a precise
error bound. Our result will be based on Laplace-type integrals for the Jacobi polynomials and
the associated Bessel functions, where we treat the group cases with integers p ≥ q as well as
the case p ∈ R with p ≥ 2q− 1 beyond the group case. The integral representation for Rpλ below
is a special case of a more general Harish-Chandra integral representation for hypergeometric
functions FBC in [26]. To start with, let us introduce some notation:
Let Hq(F) = {x ∈ Mq(F) : x∗ := xt = x} denote the space of Hermitian matrices over F,
and denote by ∆(x) the determinant of x ∈ Hq(F), which may be defined as the product of
(right) eigenvalues of x. We mention that for F = H, this is just the Moore determinant, which
coincides with the Dieudonné determinant if x is positive semi-definite, see, e.g., [1]. On Hq(F),
we consider the power functions
∆λ(a) := ∆1(a)λ1−λ2 · · ·∆q−1(a)λq−1−λq∆q(a)λq , λ ∈ Cq,
with the principal minors ∆r(a) = det((aij)1≤i,j≤r) of the matrix a = (aij)1≤i,j≤q ∈ Hq(F),
see [10]. We introduce the matrix ball Bq := {w ∈ Mq(F) : w∗w < I}, where A < B means
for matrices A,B ∈ Mq(F) that B − A is (strictly) positive definite. On Bq, we define the
probability measures
dmp(w) =
1
κpd/2
∆(I − w∗w)pd/2−γdw ∈M1(Bq),
with p ∈ R, p > 2q − 1. Here dw is the Lebesgue measure on the ball Bq,
γ := d
(
q − 1
2
)
+ 1
and
κpd/2 =
∫
Bq
∆(I − w∗w)pd/2−γ dw.
According to Theorem 2.4 of [26], the Heckman–Opdam hypergeometric function FBC(λ, k(p), x)
with λ ∈ Cq, x ∈ Rq and k(p) as in (1.2) has the following integral representation for p ∈ R with
p > 2q − 1:
FBC(λ, k(p), x) =
∫
Bq×U0(q,F)
∆(λ−ρp)/2(gx(u,w)) dmp(w)du,
where U0(q,F) denotes the identity component of U(q,F) and
gx(u,w) = u−1(coshx+ w∗ sinhx)(coshx+ sinhxw)u.
It is easily checked that U0(q,F) may be replaced by U(q,F) in the domain of integration.
Notice further that x 7→ gx(u,w) extends to a holomorphic function on Cq. As the principal
minors ∆r(a) are polynomial in the entries of a ∈ Hq(F), it follows that x 7→ ∆λ/2(gx(u,w))
extends to a holomorphic function on Cq for each λ ∈ P+. In view of relation (1.1), this leads
to the following integral representation for the Jacobi polynomials Rpλ:
Proposition 2.1. Let p ∈ R with p > 2q − 1 and k(p) = (d(p − q)/2, (d − 1)/2, d/2) with
d ∈ {1, 2, 4}. Then the Jacobi polynomials Rpλ, λ ∈ P+, have the integral representation
Rpλ(x) =
∫
Bq×U(q,F)
∆λ/2(gix(u,w)) dmp(w)du for x ∈ A0 (2.1)
A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian 5
with
gix(u,w) = u−1(cosx+ w∗i sinx)(cosx+ i sinxw)u.
We next turn to the Bessel functions which will show up in the Mehler–Heine formula. They
are given in terms of Bessel functions of Dunkl type which generalize the spherical functions
of Cartan motion groups; see [6] and [21] for a general background. We denote by JBk the
Bessel function which is associated with the rational Dunkl operators for the root system Bq =
{±ei,±ei ± ej : 1 ≤ i < j ≤ q} and multiplicity k = (k1, k2) corresponding to the roots ±ei and
±ei ± ej . We shall be concerned with multiplicities which are connected as follows to the BCq
multiplicities k(p) from (1.2):
k = (k1, k2) with k1 = k(p)1 + k(p)2 = d(p− q + 1)/2− 1/2, k2 = k(p)3 = d/2.
For such k on Bq, we use the notion
ϕ̃pλ(x) := JBk (x, iλ), x ∈ C, λ ∈ Cq.
It is well-known that for integers p ≥ q, the ϕ̃pλ are the spherical functions of the Euclidean
symmetric spaces G0/K, where K = S(U(p,F)× U(q,F)) and G0 = K nMp,q(F) is the Cartan
motion group associated with the Grassmannian Gp,q(F). Hereby the double coset space G0//K
is identified with the Weyl chamber C such that x ∈ C corresponds to the double coset of
(Ip × Iq, (Ip−q, x)) ∈ G0, and in this way, K-biinvariant functions on G0 may be considered as
functions on C. Two functions ϕ̃pλ and ϕ̃pµ coincide if and only if λ and µ are in the same Weyl
group orbit. Finally, the bounded spherical functions are exactly those ϕ̃pλ with λ ∈ C. The
Bessel functions ϕ̃pλ with d = dimFR and not necessarily integral parameter p are closely related
to Bessel functions on the symmetric cone of positive definite q×q-matrices over F, see Section 4
of [24]. It has been shown there that for p > 2q− 1, they have a positive product formula which
generalizes the product formula in the Cartan motion group cases and leads to a commutative
hypergroup structure on the Weyl chamber C.
Lemma 2.2. For p ∈ R with p > 2q−1, the Bessel functions ϕ̃pλ with λ ∈ Rq have the following
integral representation:
ϕ̃pλ(x) =
∫
Bq
∫
U(q,F)
eiRe tr(wxuλ)dmp(w)du. (2.2)
Proof. This follows readily from equations (3.12) and (4.4) in [24]; see also Proposition 5.3
of [26]. �
Remark 2.3. There are finitely many geometric cases which are not covered by the range
p ∈ ]2q − 1,∞[, namely the indices p ∈ {q, q + 1, . . . , 2q − 1}. In these cases, the Jacobi polyno-
mials Rpλ and the Bessel functions ϕ̃pλ both admit interpretations as spherical functions and
have an integral representation similar to that above, by the following reasoning: According
to Lemma 2.1 of [25], the measure mp ∈ M1(Bq) with p ∈ N, p ≥ 2q is just the pushforward
measure of the normalized Haar measure on U(p,F) under the mapping
v 7→ σ∗0vσ0, with σ0 =
(
Iq
0(p−q)×q
)
∈Mp,q(F).
For p ∈ {q, q + 1, . . . , 2q − 1}, we now define the measure mp ∈ M1(Bq) in the same way as
a pushforward measure of the Haar measure on U(p,F). (But in contrast to the case p ≥ 2q,
it will not have a Lebesgue density in these cases). From the integral representations (3.3)
and (4.4) of [24] for the Bessel functions, as well as Theorem 2.1 of [26] and relation (1.1) between
Jacobi polynomials and hypergeometric functions, one obtains that the integral representations
of Proposition 2.1 and Lemma 2.2 extend to the case p ∈ {q, q + 1, . . . , 2p− 1}.
6 M. Rösler and M. Voit
We shall now compare the integral representations of Proposition 2.1 and Lemma 2.2, which
will lead to the following quantitative Mehler–Heine (or Hilb-type) formula.
Theorem 2.4. There exist constants C1, C2 > 0 such that for all p ∈ {q, q + 1, . . . , 2q − 1}∪
]2q − 1,∞[, all λ ∈ P+, and x ∈ A0,∣∣Rpλ(x)− ϕ̃pλ(x)
∣∣ ≤ C1x
2
1λ1e
C2x21λ1 .
Thus in particular,∣∣∣Rpnλ (xn)− ϕ̃pλ(x)
∣∣∣ ≤ C1
n
x21λ1e
C2x21λ1/n → 0 for n→∞.
Notice that the estimate of Theorem 2.4 is uniform in p, a fact which was to our knowledge so
far not even noticed in the rank-one case. We conjecture that the statement of this theorem
remains correct for p ∈ [q,∞[.
Proof. We only consider the case p > 2q − 1 where the proof is based on Proposition 2.1 and
Lemma 2.2. By the previous remark, the cases p = q, q + 1, . . . , 2q − 1 can be treated in the
same way. Notice that it suffices to check uniformity in p for p > 2q − 1.
We substitute w 7→ u∗w∗ in the integral (2.2) and obtain
ϕ̃pλ(x) =
∫
Bq×U(q,F)
eiRe tr(u∗w∗xuλ)dmp(w)du.
Denoting the trace of the upper left (r × r)-block of a (q × q)-matrix by trr, we have
Re tr(u∗w∗xuλ) =
1
2
q∑
r=1
(u∗((xw)∗ + xw)u)rrλr
=
q∑
r=1
[
trr(u
∗((xw)∗ + xw)u)− trr−1(u
∗((xw)∗ + xw)u)
]
λr/2
=
q∑
r=1
trr(u
∗((xw)∗ + xw)u)(λr − λr+1)/2
with λq+1 := 0. Hence
ϕ̃pλ(x) =
∫
Bq×U(q,F)
q∏
r=1
ei trr(u
∗((xw)∗+xw)u)(λr−λr+1)/2dmp(w)du.
Furthermore, by Proposition 2.1,
Rpλ(x) =
∫
Bq×U(q,F)
q∏
r=1
∆r(gix(u,w))(λr−λr+1)/2dmp(w)du.
Telescope summation yields the well-known estimate∣∣∣∣∣
q∏
r=1
ar −
q∏
r=1
br
∣∣∣∣∣ ≤ (max(|a1|, . . . , |aq|, |b1|, . . . , |bq|)
)q−1 q∑
r=1
|ar − br|
for a1, . . . , aq, b1, . . . , bq ∈ C. We thus obtain
∣∣Rpλ(x)− ϕ̃pλ(t)
∣∣ ≤ q∑
r=1
∫
Bq×U(q,F)
M(x, u, w, λ) (2.3)
A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian 7
×
∣∣∆r(gx(u,w))(λr−λr+1)/2 − ei trr(u∗((tw)∗+tw)u)(λr−λr+1)/2
∣∣dmp(w)du
with
M(x, u, w, λ) := max
(
1, max
r=1,...,q
∣∣∆r(gx(u,w))(λr−λr+1)/2
∣∣q−1).
We now investigate ∆r(gix(u,w))(λr−λr+1)/2 more closely. As x, u, w run through compacta, we
obtain that uniformly in x, u, w,
gix(u,w) = u−1(cosx+ w∗i sinx)(cosx+ i sinxw)u
= u−1
(
Iq + w∗ix+O
(
x2
))(
Iq + ixw +O
(
x2
))
u
= Iq + u−1(ixw + w∗ix)u+O
(
x2
)
,
and thus
∆r(gx(u,w)) = 1 + trr
(
u−1(ixw + w∗ix)u
)
+O
(
x2
)
. (2.4)
Using the power series for ln(1 + z), we further have
∆r(gix(u,w))(λr−λr+1)/2 = exp
[
1
2(λr − λr+1) ln
(
1 + trr
(
u−1(ixw + w∗ix)u
)
+O
(
x2
))]
= exp
[
1
2(λr − λr+1) trr
(
u−1(ixw + w∗ix)u
)
+O
(
x2
)
(λr − λr+1)
]
.
Notice that y := u−1(ixw + w∗ix)u is skew-Hermitian, that is y∗ = −y. Therefore trr(y) =
− trr(y), which implies that Re(trr(y)) = 0. It follows that∣∣∆r(gix(u,w))(λr−λr+1)/2
∣∣ = exp
[
1
2(λr − λr+1) Re
(
trr(y) +O
(
x2
))]
= e(λr−λr+1)O(x2).
Note that these considerations apply for all fields F = R,C,H. It follows that there exists
a constant C3 > 0 (independent of x, u, w, λ) such that
M(x, u, w, λ) ≤ eC3x21λ1 for all x ∈ A0, λ ∈ P+, u ∈ U(q,F), w ∈ Bq.
From this inequality we obtain by the mean value theorem that for all x ∈ A0 and λ ∈ P+,∣∣∆r(gx(u,w))(λr−λr+1)/2 − ei trr(u∗((xw)∗+xw)u)(λr−λr+1)/2
∣∣
≤ eC3x21λ1 − 1 ≤ C3x
2
1λ1e
C3x21λ1 .
These estimates together with (2.3) imply the assertion. �
Example 2.5 (the rank one case). For q = 1 the Jacobi polynomials Rpλ associated with
root system BC1 = {±e1,±2e1} are classical one-variable Jacobi polynomials in trigonometric
parametrization. For integers p, the associated Grassmannians are the projective spaces Pp(F).
For the details, recall that the classical Jacobi polynomials R
(α,β)
n with the normalization
R
(α,β)
n (1) = 1 are given by
R(α,β)
n (x) = 2F1(α+ β + n+ 1,−n;α+ 1; (1− x)/2), (2.5)
where n ∈ Z+, α, β > −1. It is easily derived from the example on p. 17 of [22] that
Rpλ(x) = R
(α,β)
λ/2 (cos 2x) (2.6)
for λ ∈ 2Z+, with
α = (dp− 2)/2, β = (d− 2)/2;
8 M. Rösler and M. Voit
see also [23, Section 5]. In the rank one case, the U(1,F) integral in representation (2.1) cancels
by invariance of ∆ under unitary conjugation. Thus (2.1) reduces to
Rpλ(x) =
1
κpd/2
∫
B1
((cosx+ wi sinx)(cosx+ i sinxw))λ/2
(
1− |w|2
)d(p−1)/2−1
dw
for λ ∈ Z+, p > 1. In particular, if F = R, then d = 1 and B1 = [−1, 1]. Thus
R(p/2−1,−1/2)
n (cos 2x) =
1
κp/2
∫ 1
−1
(cosx+ it sinx)2n
(
1− t2
)(p−3)/2
dt.
If F = C, then d = 2 and B1 = {z ∈ C : |z| ≤ 1}. Using polar coordinates z = teiθ, one obtains
R(p−1,0)
n (cos 2x) =
1
κp
∫ 1
−1
∫ π
0
(
(cosx+ iteiθ sinx)(cosx+ ite−iθ sinx)
)2n(
1− t2
)p−2
t dtdθ.
The quaternionic case can be treated in a similar way. These formulas are just special cases of
a well-known Laplace-type integral representation for Jacobi polynomials with general indices
α ≥ β ≥ −1/2; see, e.g., [20, Section 18.10].
Let us finally mention that the Mehler–Heine formula 2.4 corresponds to [27, Theo-
rem 8.21.12] and that in the case of rank two (q = 2), the Jacobi polynomials of type BC
were first studied by Koornwinder [16, 17].
3 Random walks on the dual of a compact Grassmannian
and on P+
Recall that for integers p ≥ q the functions ϕλ := ϕpλ, λ ∈ P+ form the spherical functions of
the compact Grassmannians G/K = Gp,q(F). As functions on G, they are positive-definite. In
other words, the Jacobi polynomials (Rpλ)λ∈P+ are just the hypergroup characters of the compact
double coset hypergroups G//K ∼= A0. We now recapitulate the associated dual hypergroup
structures on P+.
3.1 Dual hypergroup structures on P+
As mentioned in the introduction, there is a one-to-one correspondence between the set of
(positive definite) spherical functions of G/K, which is parametrized by P+, and the spherical
unitary dual of G/K, i.e., the set ĜK of all equivalence classes of irreducible unitary representa-
tions (π,H) of G whose restriction to K contains the trivial representation with multiplicity
one. Here a representation (π,H) ∈ ĜK and its spherical function ϕπ are related by
ϕπ(x) = 〈u, π(x)u〉 for x ∈ G
with some K-invariant vector u ∈ H with ‖u‖ = 1, which is determined uniquely up to a complex
constant of absolute value 1.
Now consider λ, µ ∈ P+ with associated spherical functions ϕλ, ϕµ and the corresponding
representations (πλ, Hλ), (πµ, Hµ) ∈ ĜK with K-invariant vectors uλ, uµ. The tensor product
(πλ ⊗ πµ, Hλ ⊗Hµ) is a finite-dimensional unitary representation of G which decomposes into
a finite orthogonal sum
(⊕kτk = πλ ⊗ πµ, ⊕kH̃k = Hλ ⊗Hµ)
A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian 9
of irreducible unitary representations (τk, H̃k) where some of them may appear several times.
Consider the orthogonal projections pk : Hλ ⊗Hµ → H̃k. Then the vectors pk(uλ ⊗ uµ) ∈ H̃k
are K-invariant, and for pk(uλ ⊗ uµ) 6= 0, we obtain (τk, H̃k) ∈ ĜK , i.e., (τk, H̃k) is equal to
some (πτ , Hτ ), τ ∈ P+. Moreover, for g ∈ G,
ϕλ(g)ϕµ(g) = 〈uλ ⊗ uµ, (πλ ⊗ πµ)(g)uλ ⊗ uµ〉
=
∑
k
〈pk(uλ ⊗ uµ), τk(g) pk(uλ ⊗ uµ)〉 =
∑
k
‖pk(uλ ⊗ uµ)‖2ϕτk(g)
with
∑
k
‖pk(uλ⊗uµ)‖2 = 1. For λ, µ, τ ∈ P+ we now define cλ,µ,τ ≥ 0 as ‖pk(uλ⊗uµ)‖2, whenever
(τk, H̃k) = (πτ , Hτ ) appears above with a positive part, and 0 otherwise. As ϕλ(g) ∈ R for all λ, g
in our case, these nonnegative linearization coefficients also satisfy
cλ,µ,τ = dimHτ
∫
G
ϕλ(g)ϕµ(g)ϕτ (g) dg.
For λ, µ ∈ P+ we define the probability measure
δλ ∗d,p δµ :=
∑
τ∈P+
cλ,µ,τδτ ∈M1(P+) (3.1)
with finite support. By its very construction, this convolution can be extended uniquely in
a weakly continuous, bilinear way to a probability preserving, commutative, and associative
convolution on the Banach space Mb(P+) of all bounded, signed measures on P+. Moreover, as
all spherical functions are R-valued in our specific examples, the contragredient representation
of any element in ĜK is the same representation, i.e., the canonical involution .∗ on P+
∼= ĜK is
the identity. In summary, (Mb(P+), ∗d,p) is a commutative Banach-∗-algebra with the complex
conjugation µ∗(A) := µ(A) as involution. Moreover, (P+, ∗d,p) becomes a so-called Hermitian
hypergroup in the sense of Dunkl, Jewett and Spector; see [3, 7, 15].
The Haar measure on this hypergroup, which is unique up to a multiplicative constant, is
the positive measure ω =
∑
λ∈P+
h(λ)δλ with
h(λ) = c−1λ,λ,0 =
∫
G
ϕ2
λ(g) dg =
1
dimHλ
,
where the first two equations follow from general hypergroup theory (see [15]) and the last one
from the theory of Gelfand pairs (see, e.g., [9]).
The coefficients cλ,µ,τ of the convolution ∗d,p on P+ are related to the unique product li-
nearization
RpλR
p
µ =
∑
τ∈P+
cλ,µ,τR
p
τ
of the Jacobi polynomials Rpλ. It is clear by our construction that for integers p ≥ q, all cλ,µ,τ
are nonnegative with
∑
τ∈P+
cλ,µ,τ = 1.
Clearly, as Rpλ(0) = 1 for all λ, the normalization also holds for all real p ∈ [q,∞[. We
conjecture that actually all cλ,µ,τ are nonnegative for all p ∈ [q,∞[ or at least for all p ∈
[2q − 1,∞[.
Suppose that for fixed p ∈ [q,∞[ the linearization coefficients cλ,µ,τ are all nonnegative.
Then equation (3.1) defines a commutative discrete hypergroup structure (P+, ∗d,p) with the
convolution
δλ ∗d,p δµ :=
∑
τ∈P+
cλ,µ,τδτ ∈M1(P+)
10 M. Rösler and M. Voit
of point measures. For instance, in the rank one case of Example 2.5 the linearization coeffi-
cients cλ,µ,τ are explicitly known and nonnegative for all p ≥ 1 as the product linearization
coefficients of the associated one-dimensional Jacobi polynomials.
3.2 Random walks on P+
We next introduce certain random walks on P+, i.e., time-homogeneous Markov chains on P+
whose transition probabilities are given in terms of the product linearizations coefficients cλ,µ,τ
for some fixed p ∈ [q,∞[. This concept even works, under a suitable restriction, in the case
where some of the cλ,µ,τ are negative. To describe the restriction, we fix p ∈ [q,∞[ and define
the set
P p+ := {λ ∈ P+ : cλ,µ,τ ≥ 0 for all µ, τ ∈ P+}
as well as
M1
p (P+) :=
{
ν ∈M1(P+) : supp ν ⊂ P p+
}
.
We shall call the probability measures ν ∈M1
p (P+) admissible.
Clearly, for integers p ≥ q, as well as for q = 1 we have M1
p (P+) = M1(P+). Unfortunately,
it seems difficult to find further examples. To illustrate the problem, consider the measure
δ(1,0,...,0) ∈ M1(P+) for q ≥ 2 and p ∈ [q,∞[. The explicit Pieri-type formula (6.4) of [28]
then leads to a concrete product linearization formula for RpλR
p
(1,0,...,0). It can be easily derived
from [28] that for all q ≥ 2, p ∈ [q,∞[, and all λ 6= µ, we have cλ,(1,0,...,0),µ ≥ 0 as desired.
However, we are so far not able to check from [28] that cλ,(1,0,...,0),λ ≥ 0 holds, which would be
necessary for δ(1,0,...,0) ∈M1
p (P+).
As before, we fix d = 1, 2, 4 and p ∈ [q,∞[. We also fix an admissible probability measure
ν =
∑
µ
pµδµ ∈ M1
p (P+) and consider a time-homogeneous Markov chain (Sd,pn )n≥0 in discrete
time on P+ starting at time 0 in the origin 0 ∈ P+ and with transition probability
P
(
Sd,pn+1 = τ | Sd,pn = λ
)
= (ν ∗d,p δλ)({τ}), λ, τ ∈ P+, n ∈ N,
where
ν ∗d,p δλ :=
∑
τ
(∑
µ
pµcλ,µ,τ
)
δτ ∈M1(P+).
Such Markov-chains are called random walks on (P+, ∗d,p) associated with ν. It is well-known
and can be easily checked by induction that for all n the n-fold convolution power ν(n) :=
ν ∗d,p · · · ∗d,p ν ∈M1(P+) exists, and that ν(n) is just the distribution P
Sd,p
n
of Sd,pn .
In view of the Central Limit Theorem 1.1, we give an interpretation of these convolution
powers δ
(n)
λ for integers p ≥ q and λ ∈ P+ with λ 6= 0 in terms of representation theory. We
expect that this result is well-known, but we do not know an explicit proof in the literature.
Lemma 3.1. Let (πλ, Hλ) be the non-trivial irreducible unitary representation of G associated
with λ ∈ P+, λ 6= 0 and with a K-invariant vector uλ ∈ Hλ with ‖uλ‖ = 1. For each n ∈ N,
decompose the n-th tensor power (π⊗,nλ , H⊗,nλ ) into its irreducible components(
π⊗,nλ , H⊗,nλ
)
=
(⊕
τn
πτn ,
⊕
τn
Hτn
)
(3.2)
and consider the orthogonal projections pτn : H⊗,nλ → Hτn. Then for all n ∈ N,
δ
(n)
λ =
∑
τn
∥∥pτn(u⊗,nλ
)∥∥2δτn .
A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian 11
Proof. We proceed by induction. In fact, the case n = 1 is trivial. For n → n + 1, we start
with (3.2) and the associated orthogonal projections pτn : H⊗,nλ → Hτn . We now decompose the
products πτn ⊗ πλ and obtain(
π⊗,n+1
λ , H⊗,n+1
λ
)
=
(⊕
τn
(πτn ⊗ πλ),
⊕
τn
(Hτn ⊗Hλ)
)
=
(⊕
τn
(⊕
µk,n
πµk,n
)
,
⊕
τn
(⊕
µk,n
Hµk,n
))
.
Notice that here the sum
⊕
τn
⊕
µk,n
corresponds to the sum
⊕
τn+1
of the lemma with n + 1
instead of n. We now consider the orthogonal projections pµk,n : H⊗,n+1
λ → Hµk,n . Then
pτn
(
u⊗,nλ
)
= c
∥∥pτn(u⊗,nλ
)∥∥uτn ,
where |c| = 1, and thus∥∥pµk,n(u⊗,n+1
λ
)∥∥2 =
∥∥pµk,n(pτn(u⊗,nλ
)
⊗ uλ
)∥∥2 =
∥∥pτn(u⊗,nλ
)∥∥2∥∥pµk,n(uτn ⊗ uλ)∥∥2.
This fact, the assumption of our induction and the definition of the convolution now readily
imply the assertion of the lemma for n+ 1. �
We shall prove below that under a natural moment condition on a probability measure ν ∈
M1(P+), the C-valued random variables 1√
n
Sd,pn converge in distribution for n → ∞. In order
to identify the limit distribution µ = µ(d, p, ν) ∈ M1(C) in this central limit theorem, we need
some further preparations.
3.3 Bessel convolutions on C and Laguerre ensembles
As described in Section 2, the Bessel functions ϕ̃pλ with λ ∈ C make up the set of bounded
spherical functions of the Euclidean symmetric space G0/K with K = U(p,F) × U(q,F) and
G0 = K nMp,q(F). Thus by the notation of [3] and [15], the chamber C ∼= G0//K with the
associated double coset convolution •d,p is a commutative double coset hypergroup with the
functions ϕ̃pλ as (bounded) hypergroup characters. We now introduce the probability measures
dρd,p(x) := c−1d,p
q∏
j=1
x
d(p−q+1)−1
j
∏
1≤i<j≤q
(
x2i − x2j
)d
e−(x
2
1+···+x2q)/2 dx
on the Weyl chamber C, with the normalization constant
cd,p =
∫
C
q∏
j=1
x
d(p−q+1)−1
j
∏
1≤i<j≤q
(
x2i − x2j
)d
e−(x
2
1+···+x2q)/2 dx.
The measure ρd,p ∈ M1(C) is well-known in the random matrix theory of so-called Laguerre-
or β-ensembles as it is the distribution of the singular values of a Mp,q(F)-valued random variable
for which the real and imaginary parts of all entries are i.i.d. and standard normally distributed.
This fact is well-known; it can also be derived from the Haar measure of the double coset
hypergroups (C, •d,p) in [24, Section 4.1]. Moreover, having this group theoretic interpretation
in mind, one easily obtains the following well-known relation from the Fourier transform of
a multivariate standard normal distribution:∫
C
ϕ̃pλ(x) dρd,p(x) = e−(λ
2
1+···+λ21)/2 for λ ∈ C, (3.3)
see [10, Proposition XV.2.1] or [30]. This identification of the spherical Fourier-transform of ρd,p
will be essential in the following for the central limit theorem.
12 M. Rösler and M. Voit
3.4 A central limit theorem for random walks on P+
The probability measure ρd,p appears in the CLT below as limit up to some scaling parameter
σ2 = σ2(ν, p, d), which admits an interpretation as a variance parameter. For the description
of σ2, we need the so-called moment functions on (P+, ∗d,p) up to order two. For the general
theory of such moment functions and their applications to limit theorems for random walks
on hypergroups we refer to [3, Chapter 7] and [32], and the references there. The moment
functions are characterized by additive functional equations similar to the multiplicative ones
for hypergroup characters. They are usually defined in terms of (partial) derivatives with respect
to the spectral variables at the identity character. In our examples, the identity corresponds to
x = 0 ∈ C. This motivates the following definition.
Definition 3.2. Let p ∈ [q,∞[ be fixed. For k, l = 1, . . . , q we define the moment functions
mk,mk,l : P+ → R of the first and second order by
mk(λ) := i
∂
∂xk
Rλ(x)
∣∣∣∣
x=0
and mk,l(λ) := − ∂2
∂xk∂xl
Rλ(x)
∣∣∣∣
x=0
.
Let us collect some properties of these moment functions.
Lemma 3.3.
(1) For all k, l = 1, . . . , q with k 6= l and all λ ∈ P+, mk(λ) = mk,l(λ) = 0.
(2) The functions mk,k are independent of k = 1, . . . , q, and the function m := m1,1 : P+ → R
is a second order polynomial of the form
m(λ) =
1
4
q∑
r,s=1
ar,s(λr − λr+1)(λs − λs+1) +
1
2
q∑
r=1
br(λr − λr+1)
with suitable coefficients ar,s, br. In particular, m(0) = 0.
(3) For all λ, τ ∈ P+,
∫
P+
m d(δλ ∗d,p δτ ) = m(λ) +m(τ).
Proof. The Jacobi polynomials Rλ(x) are invariant under the Weyl group of type B acting in
the variable x. In particular, Rλ(x1, . . . , xq) is even in each xi, and this gives part (1). Moreover,
as Rλ(x1, . . . , xq) is invariant under permutations of the xi, the function mk,k is independent
of k. We now study m := m1,1 more closely. We start with the case p > 2q − 1. In this case we
obtain from the integral representation (2.1) that
m(λ) = −
∫
Bq×U(q,F)
∂2
∂x21
(
∆λ/2(gix(u,w))
) ∣∣∣∣
x=0
dmp(w)du (3.4)
with the power function
∆λ/2(gix(u,w)) =
q∏
r=1
∆r(gix(u,w))(λr−λr+1)/2 with λq+1 = 0.
A short calculation, using that ∆λ/2(g0(u,w)) = 1, gives
∂2
∂x21
∆λ/2(gix(u,w))
∣∣∣∣
x=0
=
1
4
(
q∑
r=1
∂
∂x1
(∆r(gix(u,w)))
∣∣∣∣
x=0
(λr − λr+1)
)2
+
1
2
q∑
r=1
∂2
∂x21
(ln ∆r(gix(u,w)))
∣∣∣∣
x=0
(λr − λr+1). (3.5)
A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian 13
Formulas (3.4) and (3.5) now imply that m is a second order polynomial as claimed, with linear
terms
br =
∫
Bq×U(q,F)
∂2
∂x21
(ln ∆r(gix(u,w)))
∣∣∣∣
x=0
dmp(w)du.
The coefficients ar,s are obtained from the Taylor expansion (2.4) of ∆r(gix(u,w)). They are
given by
ar,s :=
∫
Bq×U(q,F)
trr(u
∗(w∗P1 + P1w)u) trs(u
∗(w∗P1 + P1w)u) dmp(w)du (3.6)
with the diagonal matrix P1 := diag(1, 0, . . . , 0) ∈Mq(F). This proves that m is a second order
polynomial for p > 2q − 1. The case p ≥ q follows by analytic continuation.
Finally, for the proof of part (3) we observe that for λ, τ ∈ P+,∫
P+
m d(δλ ∗d,p δτ ) = −
∫
P+
∂2
∂x21
Rκ(x)
∣∣∣∣
x=0
d(δλ ∗d,p δτ )(κ)
= − ∂2
∂x21
(∫
P+
Rκ(x) d(δλ ∗d,p δτ )
) ∣∣∣∣
x=0
= − ∂2
∂x21
(Rλ(x)Rτ (x))
∣∣∣∣
x=0
= m(λ) +m(τ).
Notice that the last equality follows from part (1) and Rλ(0) = 1. �
Example 3.4 (the rank one case). For q = 1, the moment function m is given by
m(λ) =
λ(λ+ dp+ d− 2)
dp
, λ ∈ 2Z+.
In fact, this can be easily derived from the definition of m and the explicit formulas for the
classical Jacobi polynomials in (2.5) and (2.6). Moreover, it can be also derived from the proof
of part (2) of the preceding lemma and a direct elementary computation of a1,1 and b1 for q = 1
there.
We shall need the following variant of Lemma 3.3(2) on the growth of m for p ∈ [q,∞[:
Lemma 3.5. For all x ∈ Rq, λ ∈ P+ and k, l = 1, . . . , q,∣∣∣∣ ∂∂xkRpλ(x)
∣∣∣∣ ≤ λ1 and
∣∣∣∣ ∂2
∂xk∂xl
Rpλ(x)
∣∣∣∣ ≤ λ21.
In particular, m(λ) ≤ λ21 for λ ∈ P+.
Proof. Let again W denote the Weyl group of type BCq. We introduce the normalized W -
invariant orbit sums
M̃λ(x) :=
1
|Wλ|
∑
µ∈W.λ
ei〈λ,x〉, λ ∈ P+.
Then the Jacobi polynomials Rpλ can be written as linear combinations of such orbit sums. It
follows from the considerations in [19, Section 11] that for non-negative multiplicity values, the
expansion coefficients are all non-negative. That is,
Rpλ =
∑
µ∈P+:µ≤λ
cλµM̃µ
14 M. Rösler and M. Voit
with
cλµ = cpλµ ≥ 0,
∑
µ≤λ
cλµ = 1.
Here ≤ denotes the dominance order on P+ given by µ ≤ λ⇐⇒
r∑
i=1
µi ≤
r∑
i=1
λi for r = 1, . . . , q.
We have
∂xkM̃λ(x) =
1
|Wλ|
∑
µ∈W.λ
iµke
i〈µ,x〉, ∂xkxlM̃λ(x) =
−1
|Wλ|
∑
µ∈W.λ
µkµle
i〈µ,x〉.
Notice that |µk| ≤ λk ≤ λ1 for each µ ∈Wλ. We thus obtain, independently of x ∈ A0,∣∣∂xkM̃λ(x)
∣∣ ≤ λ1, ∣∣∂xk∂xlM̃λ(x)
∣∣ ≤ λ21.
Further, if µ ∈ P+ with µ ≤ λ, then µ1 ≤ λ1 and therefore∣∣∂xkRpλ(x)
∣∣ ≤∑
µ≤λ
cλµ
∣∣∂xkM̃µ(x)
∣∣ ≤∑
µ≤λ
cλµµ1 ≤ λ1.
In the same way,∣∣∂xk∂xlRpλ(x)
∣∣ ≤∑
µ≤λ
cλµ
∣∣∂xk∂xlM̃µ(x)
∣∣ ≤∑
µ≤λ
cλµµ
2
1 ≤ λ21. �
We also need some further properties of the moment function m. We here have to restrict
our attention to the case p ∈ {q, q+ 1, . . . , 2q− 1}∪]2q− 1,∞[. We shall assume this restriction
from now on. We expect that the results below are also valid for all p ∈ [q,∞[.
Lemma 3.6.
(1) The matrix A = (ar,s)r,s=1,...,q ∈Mq(R) is positive definite.
(2) For all λ ∈ P+ \ {0}, m(λ) > 0.
(3) There exists a constant C1 > 0 such that for all λ ∈ P+, C1λ
2
1 ≤ m(λ).
Proof. For the proof of (1), we first consider the case p ∈ ]2q − 1,∞[ and conclude from the
definition of the ar,s in the proof in Lemma 3.3 that A is symmetric, and that for all τ ∈ Rq,
τTAτ =
∫
Bq×U(q,F)
(
q∑
r=1
τr trr(·u∗(w∗P1 + P1w)u)
)2
dmp(w)du,
where the functions
(w, u) 7→ trr(·u∗(w∗P1 + P1w)u), Bq × U(q,F)→ R,
are linearly independent for r = 1, . . . q. This shows that τTAτ > 0 for all τ ∈ Rq with τ 6= 0 as
claimed. The case of integers p ≥ q can be handled in a similar way by using a modified version
of integral representation (3.6) for ar,s which is based on Remark 2.3 instead of Proposition 2.1.
For the proof of part (2) we proceed as in the proof of Lemma 3.5 and write
Rpλ =
∑
µ∈P+:µ≤λ
cλµM̃µ with cλµ ≥ 0, cλλ > 0,
∑
µ≤λ
cλµ = 1.
A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian 15
Thus for λ ∈ P+ \ {0},
m(λ) = −∂2x1R
p
λ(x)
∣∣
x=0
=
∑
µ∈P+:µ≤λ
cλµ
|Wµ|
∑
τ∈Wµ
τ21 > 0.
For the proof of part (3), we use (1) and write m(λ) as
m(λ) = λT Ãλ− bTλ
with some positive definite matrix à and some b ∈ Rq. We thus find constants c, d > 0 such
that m(λ)− cλ21 > 0 holds for all λ ∈ P+ with λ1 ≥ d. As there are only finitely many λ ∈ P+
with λ1 < d, we conclude from part (2) that there exists some C1 > 0 with m(λ)− cλ21 > 0 for
all λ ∈ P+ with λ 6= 0. �
Remark 3.7. The nonnegativity of m(λ) in Lemma 3.6(2) can be easily established directly.
In fact, assume that m(λ) < 0 for some λ ∈ P+. Then the Taylor formula
Rλ(x) = 1− m(λ)
2
(
x21 + · · ·+ x2q
)
+O
(
‖x‖3
)
implies that Rλ(x) > 1 for some x close to 0, and thus by the Weyl group invariance of Rλ, for
some x ∈ A0. But this contradicts the fact that ‖Rλ‖∞ ≤ 1 on A0, which is a consequence of
Proposition 2.1. However, we have no different proof for the strict positivity of m(λ) for λ 6= 0
than the one given in Lemma 3.6(2).
We next use the moment function m in order to define a modified variance of measures
ν ∈M1(P+) depending on the underlying convolution ∗d,p. This modified variance will appear
in the CLT below.
Definition 3.8. Let ν ∈M1(P+) be a probability measure with finite second moments, meaning
that
∑
λ∈P+
λ21ν({λ}) <∞. Then the modified second moment σ2 := σ2(ν) of ν is defined as
σ2 :=
∑
λ∈P+
m(λ)ν({λ}).
Notice that by Lemmas 3.3 and 3.6, σ2 is finite and non-negative where σ2 = 0 holds precisely
for ν = δ0.
Lemma 3.9. Let ν ∈M1(P+) be a probability measure with finite second moments and with the
modified variance σ2 ≥ 0. Then the spherical Fourier transform
Fν : Rq → R with Fν(x) :=
∑
λ∈P+
Rpλ(x)ν({λ})
is twice continuously differentiable on Rq with
Fν(0) = 1, ∇Fν(0) = 0, and Hesse matrix D2(Fν)(0) = −σ2Iq.
Proof. As ν has finite second moments, we conclude form Lemma 3.5 that for all k, l = 1, . . . , q,
the series∑
λ∈P+
ν({λ}) ∂
∂xk
Rpλ(x),
∑
λ∈P+
ν({λ}) ∂2
∂xk∂xl
Rpλ(x)
converge uniformly with respect to x ∈ Rq. This implies that Fν(x) is twice continuously
differentiable on Rq, and the partial derivatives commute with the summation. The derivatives
at x = 0 are now obtained by Lemma 3.3. �
16 M. Rösler and M. Voit
We now turn to random walks (Sd,pn )n≥0 on (P+, ∗d,p) associated with some admissible ν ∈
M1
p (P+). It is well-known (see, e.g., [3, Section 7.3]) that the additive functional equation
for m in Lemma 3.3(3) leads to relations between the modified variance of ν and random walks
associated with ν.
Lemma 3.10.
(1) For all ν1, ν2 ∈M1
p (P+) with finite second moments, the measure ν1 ∗d,p ν2 ∈M1(P+) has
also finite second moments, and σ2(ν1 ∗d,p ν2) = σ2(ν1) + σ2(ν2).
(2) Let (Sd,pn )n≥0 be a random walk on (P+, ∗d,p) associated with the measure ν ∈M1
p (P+) with
finite second moments. Then, for all integers n ≥ 0, the expectation of m(Sd,pn ) satisfies
E(m(Sd,pn )) = nσ2(ν), and the process (m(Sd,pn )− nσ2(ν))n≥0 is a martingale with respect
to the canonical filtration of (Sd,pn )n≥0.
Proof. Part (1) follows easily from Lemma 3.3(3); c.f. [3, Section 7.3.7]. Moreover, the first
assertion of (2) follows from (1) by induction. For the proof of the second statement in (2) we
refer to [3, Proposition 7.3.19]. �
Lemma 3.11. For a ∈ ]0,∞[, define the finite set Ka := {λ ∈ P+ : λ1 ≤ a}. Let (Sd,pn )n≥0
be a random walk on (P+, ∗d,p) as described above associated with some admissible ν ∈M1
p (P+)
with finite second moments. Then, for each ε > 0 there exists some a ≥ 1 such that for all
n ∈ N, P (Sd,pn 6∈ K√na) ≤ ε.
Proof. By Lemma 3.6, we find c > 0 with m(λ) ≥ cλ21 for λ ∈ P+. Therefore, m(λ) ≥ cλ21 ≥
ca2n for all λ ∈ P+ \K√na and all n. Hence,
P
(
Sd,pn 6∈ K√na
)
≤ P
(
m
(
Sd,pn
)
≥ ca2n
)
≤ E(m(Sd,pn ))
ca2n
=
σ2n
ca2n
=
σ2
ca2
with the finite modified variance σ2. This implies the claim. �
We are now ready to prove the main result of this section:
Theorem 3.12. Let p ∈ {q, q + 1, . . . , 2q − 1}∪]2q − 1,∞[. and ν ∈ M1
p (P+) be an admissible
probability measure with ν 6= δ0 and with finite second moments. Let σ2 ∈ ]0,∞[ be the modified
modified variance of ν, and (Sd,pn )n≥0 be a random walk on (P+, ∗d,p) associated with ν. Then
Sd,pn /
√
nσ2 converges in distribution to the distribution ρd,p ∈ M1(C) of a Laguerre ensemble
in C.
Proof. Fix x ∈ C. Let n ∈ N be large enough such that x/
√
n ∈ A0. By Section 3.2, Sd,pn has
the distribution ν(n). We thus obtain from the multiplicativity of the spherical Fourier transform
of probability measures on (P+, ∗d,p), Lemma 3.9, the qualitative Taylor formula, and from the
properties of the moment functions in Lemma 3.3 that for n→∞,
E
(
R
Sd,p
n
(x/
√
n)
)
=
(
Fν(x/
√
n)
)n
=
(
1− σ2
2n
(
x21 + · · ·+ x2q
)
+ o(1/n)
)n
−→ e−(x
2
1+···+x2q)σ2/2. (3.7)
Now fix ε > 0. By Lemma 3.11, there is so a > 0 such that for all n ∈ N, P (Sd,pn 6∈ K√na) ≤ ε.
We now conclude from the Mehler–Heine formula (2.4) that for all λ ∈ K√na, that is, λ ∈ P+
with λ1 ≤ a
√
n,∣∣Rpλ(x/
√
n)− ϕ̃pλ(x/
√
n)
∣∣ ≤ C1x
2
1λ1e
C2x21λ1/
√
n ≤ ε
A Central Limit Theorem for Random Walks on the Dual of a Compact Grassmannian 17
whenever n is sufficiently large. As |Rpλ(x/
√
n)| ≤ 1 and |ϕ̃pλ(x/
√
n)| ≤ 1, we thus have∣∣E(R
Sd,p
n
(x/
√
n)
)
− E
(
ϕ̃
Sd,p
n
(x/
√
n)
)∣∣
≤ E
(∣∣R
Sd,p
n
(x/
√
n)− ϕ̃
Sd,p
n
(x/
√
n)
∣∣1{Sd,p
n ∈K√na}
)
+ 2P
(
Sd,pn 6∈ K√na
)
≤ 3ε
for n sufficiently large. Together with (3.7) and the identity ϕ̃pcy(x) = ϕ̃py(cx) for c > 0 and
x, y ∈ C, this implies that for all x ∈ C,
lim
n→∞
E
(
ϕ̃p
Sd,p
n /
√
σ2n
(x)
)
= lim
n→∞
E
(
ϕ̃p
Sd,p
n
(
x/
√
σ2n
))
= lim
n→∞
E
(
R
Sd,p
n
(
x/
√
σ2n
))
= e−(x
2
1+···+x2q)/2.
From this limit, equation (3.3) and Levy’s continuity theorem for the spherical Fourier transform
on the double coset hypergroup (C, •d,p) (see, e.g., [3, Section 4.2]), we now infer that Sd,pn /
√
σ2n
converges in distribution to ρd,p as claimed. �
Theorem 1.1 in the introduction is an immediate consequence from Theorem 3.12 and Lem-
ma 3.1.
We also remark that the methods of the preceding proof lead with some additional technical
effort to rates of convergence in the CLT; see [11, 29] for the rank one case.
We finish this paper with a strong law of large numbers; it follows easily from the preceding
properties of the moment function m, in combination with strong laws of large numbers for
random walks on commutative hypergroups in [3, Section 7.3] and [32].
Theorem 3.13. Let ν ∈ M1
p (P+) be admissible with with finite second moments, and let
(Sd,pn )n≥0 be an associated random walk on (P+, ∗d,p). Then for all ε > 1/2, Sn/n
ε → 0 al-
most surely.
Proof. Consider first the hypergroup case with an integer p ≥ q. By Lemmas 3.3 and 3.6,
all conditions of Theorem 7.3.26 in [3] are satisfied for the time-homogeneous random walk
(Sd,pn )n≥0, the sequence (rn := n2ε)n≥1, and the moment function m instead of m2 in [3]. This
theorem now yields that m(Sd,pn )/n2ε tends to 0 almost surely, and Lemma 3.6 proves the claim.
An inspection of the details in the proof of Theorem 7.3.26 in [3] shows that this theorem is also
available for all p and admissible ν ∈M1
p (P+) which proves the theorem in general. �
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1 Introduction
2 A Mehler–Heine formula
3 Random walks on the dual of a compact Grassmannian and on P+
3.1 Dual hypergroup structures on P+
3.2 Random walks on P+
3.3 Bessel convolutions on C and Laguerre ensembles
3.4 A central limit theorem for random walks on P+
References
|