This paper investigates a family of parameterized sequences related to the Catalan sequence, establishing conditions for their positive definiteness and exploring their connections with free and monotonic convolutions.
Contribution
It introduces a new family of sequences, provides criteria for their positive definiteness, and links them to free and monotonic convolution theories.
Findings
01
Derived sufficient conditions for positive definiteness.
02
Identified connections with free convolution.
03
Analyzed examples from OEIS.
Abstract
We study a family of sequences cn(a2,…,ar), where r≥2 and a2,…,ar are real parameters. We find a sufficient condition for positive definiteness of the sequence cn(a2,…,ar) and check several examples from OEIS. We also study relations of these sequences with the free and monotonic convolution.
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Full text
Some relatives of the Catalan sequence
Elżbieta Liszewska
and
Wojciech Młotkowski
Telecommunications and Teleinformatics Department (KTT), Wrocław University of Science and Technology,
Wybrzeże Wyspiańskiego 27,
50-370 Wrocław, Poland
Instytut Matematyczny,
Uniwersytet Wrocławski,
Plac Grunwaldzki 2/4,
50-384 Wrocław, Poland
We study a family of sequences cn(a2,…,ar), where r≥2 and a2,…,ar are real parameters.
We find a sufficient condition for positive definiteness of the sequence cn(a2,…,ar)
and check several examples from OEIS. We also study relations
of these sequences with the free and monotonic convolution.
W. M. is supported by the Polish
National Science Center grant No. 2016/21/B/ST1/00628.
Introduction
The Catalan sequence (n2n+1)2n+11:
[TABLE]
(entry A000108 in OEIS [14]) plays an important role in mathematics.
It counts several combinatorial objects, such as binary trees, noncrossing partitions, Dyck paths,
dissections of a polygon into triangles and many others, as can be seen in the Stanley’s book [15].
It also shows up as the moment sequence of the Marchenko-Pastur law
and (in its aerated version) of the Wigner law, which in the free probability theory
are the analogs of the Poisson and the normal law.
One of the generalizations are Fuss numbers (npn+1)pn+11,
which count for example p-ary trees with np−n+1 leaves,
see [2].
The generating function
[TABLE]
The coefficients (nnp+r)np+rr have also combinatorial interpretations, see [2],
and are called generalized Fuss numbers or Raney numbers. Formulas (2), (3)
remain true if the parameters p,r are real.
It turns out that for p,r∈R the sequence (nnp+r)np+rr
is positive definite if and only if either p≥1,0<r≤p or p≤0,p−1≤r<0 or r=0,
see [6, 7, 8, 1, 3].
Moreover, the corresponding probability distributions μ(p,r) are interesting from the point of view
of noncommutative probability, for example the free R-transform of μ(p,r) is Bp−r(z)r−1,
μ(1+p,1)=μ(1,1)⊠p, p>0, where “⊠” is the multiplicative free convolution,
and μ(p,q)⊳μ(p+r,r)=μ(p+r,q+r), where “⊳” is the monotonic convolution, see [9].
In this paper we are going to study sequences cn(a) which are defined
by real parameters a=(a2,…,ar) and recurrence relation (4),
with c0(a)=1. If r=2, a2=1 then cn(a) is the Catalan sequence.
First we provide combinatorial motivations for such sequences, for example in terms of action of a finite family
of operators on a product.
Formula (4) implies equations (6)
and (7) for the generating and
the upshifted generating function Ca(z), Da(z):=zCa(z).
In Section 2 we study these functions, in particular we give a sufficient condition when the domain of Da(z)
and Ca(z) is contained in C∖R.
Consequently, Da is a Pick function and the sequence cn(a) is positive definite.
If this is the case then the corresponding probability distribution will be denoted μ(a).
We find the free R-transform for μ(a),
which is a rational function, and study the convolution semigroup
μ(a)⊞t. We also prove that μ(a′)⊳μ(a′′)=μ(a),
where the sequence a is given by (17).
In Section 6 we study in details the case r=3. We give formulas for cn(a,b),
free cumulants κn(a,b), the generating functions Ca,b(z),Da,b(z),
and prove that the sequence cn(a,b) is positive definite if and only if a2+3b≥0.
Moreover, for a,b>0 the distribution μ(a,b) is infinitely divisible with respect to the additive free
convolution “⊞”.
For the case r=4 we provide sufficient conditions for positive definiteness
(Theorem 7.2, Proposition 7.3).
Then we consider the symmetric case, i.e. when aj=0 whenever j is even, and
in the final section we provide a record
of these integer sequences from OEIS which
are of the form cn(a) and verify their positive definiteness.
1. Operators on a set
Suppose that X is a set and that for j=2,3,…,r we are given some j-ary operators on X,
Fi(j):Xj→X, i=1,2,…,aj, here aj are positive integers.
Put a:=(a2,…,ar) and denote by cn(a) the number of all possible
compositions of these operations applied to the product x0x1…xn.
For example, for n=2 we can apply either
[TABLE]
where
1≤i≤a3, 1≤i1,i2≤a2, so that c2(a)=a3+2a22.
Each such composed operator on x0x1…xn can be written as
[TABLE]
where ws is a result of a composition of operators
Fi(j) on xps−1xps−1+1…xps−1,
with 0=p0<p1<…<pj0=r+1.
Accordingly, we obtain the following recurrence relation
[TABLE]
for n≥1, with the initial condition c0(a)=1.
In a similar way one can prove that cn(a) is the number of:
•
finite rooted labeled trees with n+1 leaves such that the nodes are of order less or equal to r,
and each node v of order 2≤j≤r is given a label ℓ(v)∈{1,2,…,aj},
•
labeled sequences (u1ϵ1,…,usϵs),
such that s≥1,
[TABLE]
for 1≤k≤s, u1+…+us=1 and if uk=1−j then ϵk∈{1,…,aj}, where a0:=1,
and ∣{j:uj=1}∣=n+1,
•
Dyck paths from (0,0) to (s,1), with labeled steps (1,ujϵj),
where s, uj, ϵj satisfy the same conditions as in the previous point.
We will also work with the upshifted generating function Da(z):=zCa(z),
so that (6) is equivalent to
[TABLE]
with Da(0)=0. Hence Da(z) is the inverse function of
Pa(w):=w−a2w2−…−arwr in a neighborhood of w=0.
2. The generating functions and positive definiteness
Motivated by the previous section we are going to study sequences defined by the recurrence
relation (4), with c0(a):=1, where
a=(a2,…,ar)∈Rr−1, r≥2, with ar=0.
Then the generating function Ca(z), given by (5),
and the upshifted generating function Da(z):=zCa(z),
satisfy relations (6) and (7),
with Da(0)=0.
The functions Ca(z), Da(z) can not be extended to entire functions on C.
Proof.
Assume that Da(z) is an entire function.
It can not be a polynomial for otherwise each side of (7)
would be a polynomial of different degree. Hence D(z) is essentially singular at infinity.
By the Casorati-Weierstrass theorem, there exists a sequence zn∈C
such that ∣zn∣→∞ and Da(zn)→0, however this is impossible due to (7).
Therefore Da(z), and consequently Ca(z), can not be extended to entire functions.
∎
Now we will study a possible domain of the functions Ca(z), Da(z).
Denote by Na the set of all such z∈C that the equation
[TABLE]
has a multiple solution. Put
[TABLE]
so that z∈Na if and only if Pa(w)−z has a multiple root.
Proposition 2.3**.**
A complex number z0 belongs to Na if and only if
there exists w0∈C such that Pa(w0)=z0 and Pa′(w0)=0.
Proof.
If z0∈Na then Pa(w)−z0=(w−w0)2Q(w) for some
w0∈C and a polynomial Q(w). Then Pa(w0)=z0 and Pa′(w0)=0.
On the other hand, if Pa(w0)=z0 and Pa′(w0)=0
then Pa(w)−z0=(w−w0)Q1(w) for a certain polynomial Q1,
and the assumption Pa′(w0)=0 implies that Q1(w0)=0, hence z0∈Na.
∎
Corollary 2.4**.**
If all the roots of Pa′(w) are real then Na⊆R.
Note that cardinality of Na is at most r−1
and if z∈Na then z∈Na.
In fact, Na consists of all those z0∈C for which
some of the branches w0(z),…,wr−1(z) of the set of solutions of (8)
meet, while we are interested in just one of these branches, namely that
which satisfies w0(0)=0.
It may happen that 0∈Na, but w=0
is a single root of the equation Pa(w)=0.
Therefore we can uniquely define Da(z) as an analytic function at least on the set
[TABLE]
in such a way that (7) is satisfied, Da(0)=0 and Da(z)=Da(z)
for z∈Da.
Note that (7) implies that Da(z) is injective on its domain.
Recall that a sequence {cn}n=0∞ of real numbers
is called positive definite if
[TABLE]
holds for every sequence of real numbers xi with finite number of nonzero terms.
Equivalently, there exists a positive measure μ on R
such that cn are moments of μ, i.e. cn=∫Rtnμ(dt)
for n=0,1,….
The moment generating function, the upshifted moment generating function and the Cauchy
transform of μ are given by
[TABLE]
so that Dμ(z)=zCμ(z) and Dμ(z)=Gμ(1/z).
We are now interested for which real parameters a2,…,ar the sequence cn(a),
defined by (4), with c0(a)=1,
is positive definite.
Theorem 2.5**.**
If Na⊆R then the sequence cn(a) is positive definite.
Proof.
By the assumptions, Da(z) can be defined as an analytic function
on Da⊆C∖R
in such a way that Da(z)=Da(z) and Da(0)=0.
For w=x+yi
[TABLE]
so that for ∣z∣ small, z∈C∖R, the sign of ℑDa(z) coincides with that of ℑz.
Now one can observe from (7) that ℑDa(z) never vanish on C∖R.
Therefore if ℑz>0 (resp. <0) then ℑDa(z)>0 (resp. <0), i.e. Da(z) is a Pick function,
which implies that Da(1/z) is the Cauchy transform of a probability measure on R.
∎
Corollary 2.6**.**
If all the roots of Pa′(w) are real then cn(a) is positive definite.
If the sequence cn(a) is positive definite then we will denote
by μ(a) the probability measure for which the numbers cn(a) are moments.
Since the domain of the generating function Ca(z) contains a neighborhood of [math],
such a measure is unique and has compact support.
Example (A063020). Take a=(1,1,−1).
Then Pa(w)=w−w2−w3+w4 and its derivative Pa′(w)=(w−1)(4w2+w−1)
has only real roots. Therefore the sequence A063020:
[TABLE]
(with the initial [math] term skipped) is positive definite.
The following example shows that the converse of Corollary 2.4 is not true.
Example (A121988).
Take a=(2,−2,1). Then Pa(w)=w−2w2+2w3−w4,
Pa′(w)=1−4w+6w2−4w3. The roots of Pa′(w) are 1/2,1/2±i/2
and Pa(1/2±i/2)=1/4, so N2,−2,1={3/16,1/4} and the sequence A121988:
[TABLE]
is positive definite.
3. R-transform and free additive convolution semigroups
For a sequence 1=c0,c1,c2…, with generating function
C(z):=∑n=0∞cnzn (possibly a formal power series),
the free R-transform of cn, or of C(z), is defined by
[TABLE]
The coefficients κn in the Taylor expansion R(z)=∑n=1∞κnzn
are called free cumulants of the sequence cn.
If cn are moments of a probability distribution on R, i.e. cn=∫Rxnμ(dx),
n=0,1,…, then R (resp κn) is called the free R-transform (resp. the free cumulants) of μ.
If R1(z),R2(z),R(z) are R-transforms of probability distributions μ1,μ2,μ, respectively,
and if t≥1 then R1(z)+R2(z), tR(z) are R-transforms of certain probability
distributions which are denoted μ1⊞μ2, μ⊞t, respectively,
see [16, 10, 5] for details.
Now take a=(a2,…,ar)∈Rr−1, with r≥2, ar=0.
Proposition 3.1**.**
The R transform of the sequence cn(a) is
[TABLE]
Proof.
It is sufficient to note that equation (6) can be written as
[TABLE]
∎
Denote by cn⊞t(a) the sequence for which the R-transform is t⋅Ra(z).
The generating and the upshifted generating functions will be denoted Ca⊞t(z),Da⊞t(z).
If cn⊞t(a) is positive definite then the corresponding probability distribution
on R will be denoted μ(a)⊞t.
If 0<t1≤t2 and cn⊞t1(a) is positive definite then so is cn⊞t2(a)
and μ(a)⊞t2=(μ(a)⊞t1)⊞t2/t1.
Proposition 3.2**.**
The function Da⊞t(z) satisfies
[TABLE]
so that Da⊞t(z) is the composition inverse function to
For compactly supported probability distributions μ1,μ2 on R,
with the moment generating functions
[TABLE]
there exists unique compactly supported probability distribution μ1⊳μ2 on R,
called monotonic convolution of μ1 and μ2, such that its moment generating function satisfies
[TABLE]
For details we refer to [9]. In terms of the upshifted moment generating functions
Dμi(z):=zCμi(z),Dμ1⊳μ2(z):=zCμ1⊳μ2(z) relation (15) becomes
[TABLE]
Proposition 4.1**.**
Suppose that a′=(a2′,…,ar′′), a′′=(a2′′,…,ar′′′′)
and the sequences cn(a′),cn(a′′) are positive definite,
with the corresponding probability distributions μ(a′),μ(a′′). Then
[TABLE]
where the sequence a is given by
[TABLE]
Proof.
It is a consequence of (16) and the fact that Da(z)
is the composition inverse of Pa(w).
∎
It is natural to define a′⊳a′′:=a by formula (17).
Corollary 4.2**.**
If the sequences cn(a′),cn(a′′) are positive definite
then so is cn(a′⊳a′′).
Example: Take a′=(1), a′′=(1,2).
Then P1(w)=w−w2, P1,2(w)=w−w2−2w3 and
[TABLE]
so that
[TABLE]
This leads to the positive definite sequence cn(2,0,−5,6,−2):
[TABLE]
which is absent in OEIS.
The roots of
[TABLE]
are
[TABLE]
and
[TABLE]
This example illustrates that the operation “⊳” does not preserve real rootedness
of Pa′, but, as we will prove, it does preserve the property “Na⊆R”.
Proposition 4.3**.**
For a′=(a2′,…,ar′′), a′′=(a2′′,…,ar′′′′) we have
It is well know that the Catalan sequence is positive definite, namely
[TABLE]
n=0,1,….
Taking P(w):=w−w2 we can now prove this applying Theorem 2.5.
It is also known that μ(1) (and hence μ(a), with a=0) is infinitely divisible with respect to the additive free
convolution ⊞
and the moments of μ(1)⊞t are the Narayana polynomials (see A001263 in OEIS):
[TABLE]
for n≥1, see [10].
The generating function satisfies
[TABLE]
and μ(1)⊞t are known as the Marchenko-Pastur distributions:
[TABLE]
6. The case r=3
In this section we will confine ourselves to the case r=3.
Put a:=a2, b:=a3=0. The corresponding sequence, polynomial and the generating
functions will be denoted cn(a,b), Pa,b(w), Ca,b(z), Da,b(z).
6.1. Formula for cn(a,b)
Proposition 6.1**.**
For a,b∈R, n≥0, we have
[TABLE]
Proof.
By the Lagrange inversion theorem:
[TABLE]
Since (k−n)(−1)k=(kn+k−1), we have
[TABLE]
The coefficient of Da,b(z) at wn is cn−1(a,b), therefore
Moreover, equations (20), (21) admit a multiple solution C,D if and only if z=z±(a,b).
Consequently, Na,b={z−(a,b),z+(a,b)}.
Note that
[TABLE]
If a2+4b=0 then z−(a,b)=0 and z+(a,b)=8/(27a).
Proof.
One can check that the roots of Pa,b′(w)=1−2aw−3bw2 are d±(a,b)
and Pa,b(d±(a,b))=z±(a,b).
∎
It turns out that the solutions of (21) admit nice parametrization.
Theorem 6.3**.**
For
[TABLE]
The square root a2+3b must be the same
for z(a,b,t), D0(a,b,t) and D±(a,b,t)
and the square root 4−t2 must be the same for D±(a,b,t).
Note that for t0:=a/a2+3b we have
[TABLE]
Proof.
Putting D±:=D±(a,b,t), D0:=D0(a,b,t),
it is elementary to check that
[TABLE]
Consequently,
[TABLE]
which completes the proof.
∎
One can check that D+(a,b,t)=D−(a,b,t) iff t=±2,
D+(a,b,t)=D0(a,b,t) iff t=1 and
D−(a,b,t)=D0(a,b,t) iff t=−1.
6.3. The generating functions
Now we will study the generating functions Ca,b(z), Da,b(z).
Recall that they satisfy
[TABLE]
with D(0)=0. These functions
can be defined on Da,b:=C∖{tz±(a,b):t≥1}.
If a2+4b=0, a>0 (resp. a<0) then we can put Da,b:=C∖[8/(27a),+∞)
(resp. Da,b:=C∖(−∞,8/(27a]).
Lemma 6.4**.**
For the real function Pa,b(d)=d−ad2−bd3 we have:
•
If a2+3b≤0 then Pa,b(d) is an increasing function on R.
•
If b<0<a2+3b, a>0 then 0<d+(a,b)<d−(a,b), Pa,b is increasing
on (−∞,d+(a,b)], decreasing on [d+(a,b),d−(a,b)] and
increasing on [d−,+∞).
•
If b>0, a>0 then d−(a,b)<0<d+(a,b),
Pa,b is decreasing on (−∞,d−(a,b)], increasing on [d−(a,b),d+(a,b)]
and decreasing on [d+(a,b),+∞).
Denote τ±(a,b):=1/z±(a,b), so that
[TABLE]
with particular cases τ+(a,−a2/3)=3a, τ+(a,−a2/4)=27a/8.
Note that for fixed a>0 the function τ+(a,b) increases with b∈[−a2/3,+∞)
and τ−(a,b) decreases with b∈[0,+∞).
Theorem 6.5**.**
The sequence {cn(a,b)}n=0∞ is positive definite
if and only if a2+3b≥0.
If a>0 then for the corresponding probability distribution μ(a,b) we have:
•
If b<0≤a2+3b then the support of μ(a,b) is contained in [0,τ+(a,b)].
•
If b>0 then the support of μ(a,b) is contained in [τ−(a,b),τ+(a,b)].
Proof.
If a2+3b≥0 then the sequence {cn(a,b)}n=0∞ is positive definite
by Theorem 2.5 and Lemma 6.2
and Da,b(z) is a Pick function on C∖R,
which can be extended to (−∞,z+(a,b)) if b<0≤a2+3b
and to \big{(}z_{-}(a,b),z_{+}(a,b)\big{)} if b>0.
If a2+3b<0 then Da,b(z) is not analytic at z±(a,b)∈/R,
so can not be extended to a Pick function.
∎
6.4. The generating functions in a neighborhood of [math]
Applying Theorem 6.3 we can write down explicit formulas.
Theorem 6.6**.**
Assume that a>0, 0=b∈R. Then in a neighborhood of z=0 we have
[TABLE]
where
[TABLE]
and
[TABLE]
Proof.
If a2+3b<0 then
the maps
[TABLE]
are real and increasing with t∈R.
For u=t(3+t2) we have t=2sinh(31arcsinh(u/2)), t,u∈R,
which leads to (25) in this case.
If b<0<a2+3b then t0=a/a2+3b>1, the functions t↦t(3−t2), t↦z(a,b,t), t↦D0(a,b,t)
are decreasing for t≥1 and the inverse function for the map t↦u=t(3−t2), t≥1, is
t=2cosh(31arcosh(−u/2)), u≤2.
Finally, if b>0 then 0<t0=a/a2+3b<1 and for t∈[−1,1] the inverse of u=t(3−t2) is
t=2sin(31arcsin(u/2)), u∈[−2,2], which concludes the proof.
∎
6.5. Free cumulants
We will use the following elementary
Proposition 6.7**.**
For a,b∈R we have
[TABLE]
where the coefficients κn(a,b)
are given by
[TABLE]
and satisfy the following recurrence: κ0(a,b)=1,
κ1(a,b)=a and
[TABLE]
for n≥2.
Corollary 6.8**.**
The free cumulants κn(a,b), n≥1, of the sequence cn(a,b) are given by (27).
If a2+4b>0 then we have the following version of Binet’s formula:
[TABLE]
where
[TABLE]
If b>0 then the corresponding probability measure μ(a,b) is infinitely divisible
with respect to the free additive convolution ⊞.
Proof.
For the free R-transform of the sequence cn(a,b) we have
[TABLE]
which proves that the free cumulants are given by (27).
Moreover, it is elementary to check that if a2+4b>0 then
[TABLE]
If b>0 then t−,t+>0, and from (28)
the sequence κn+2(a,b), n≥0, is positive definite.
This implies that μ(a,b) is infinitely divisible
with respect to the free additive convolution ⊞, see [10].
∎
Formula (29) implies that for b>0 the distribution
μ(a,b) can be decomposed as
[TABLE]
where μ(u)⊞t is dilation of the Marchenko-Pastur distribution
μ(1)⊞t with parameter u.
Examples.
One encounters interesting sequences as free cumulants κn(a,b), notably
the Fibonacci sequence A000045 as κn(1,1),
the Pell sequence A000129 as κn(2,1),
the Jacobsthal sequence A001045 as κn(1,2),
also κn(3,−1)=A001906 (bisection of Fibonacci sequence),
κn(4,−1)=A001353, κn(5,−1)=A004254,
κn(5,−2)=A107839, κn(3,−2)=A000225,
κn(1,3)=A006130, κn(1,4)=A006131,
κn(1,5)=A015440.
6.6. Special cases.
Now we will focus on some special cases: a=0, a2+3b=0 and a2+4b=0.
Comparing (2) and (23) one can see
that C0,1(z)=B3(z2).
In fact cn(0,1) is the aerated sequence (n3n+1)3n+11,
i.e. c2n(0,1)=(n3n+1)3n+11 and c2n+1(0,1)=0,
while cn(0,−1) is the aerated sequence (n3n+1)3n+1(−1)n.
By Theorem 6.5 the sequence cn(0,1) is positive definite, cn(0,−1) is not.
It is known that
n=0,1,2,…, so that the distribution μ(0,1) is absolutely continuous,
with the density function W3,1(x2)∣x∣ on (−27/2,27/2).
Moreover, in view of Corollary 5.3 in [6], μ(0,1)
is infinitely divisible with respect to the free convolution “⊞”,
which means that the sequence cn⊞t(0,1) is positive definite for every t>0.
Moreover, since for t>0 the distribution μ(0,1)⊞t is symmetric,
also the sequence c2n⊞t(0,1) is positive definite and the support
of the corresponding probability distribution is contained in [0,+∞).
For b=−a2/3 it is easy to check that
[TABLE]
and
[TABLE]
In particular cn(3,−3)=A097188 (see also A025748):
[TABLE]
while κn(3,−3)=A057083.
In view of Theorem 6.5 the sequence cn(a,−a2/3)
is positive definite. More precisely, if a>0 then
[TABLE]
n=0,1,2,….
Indeed, from the definition of the beta function the integral is equal to
[TABLE]
Using identities: Γ(x+1)=xΓ(x) and Γ(1/3)Γ(2/3)=2π/3
one can check that this coincides with the right hand side of (30).
Put b=−a2/4. Since
[TABLE]
we see that Ca,−a2/4(z) can be represented as B(z)2,
where B(z) satisfies equation
[TABLE]
This means that
[TABLE]
and
[TABLE]
in particular cn(2,−1)=A006013.
The density of μ(2,−1),
can be found in [12], formula (29) and [7], formula(42).
The cumulant sequence κn(2,−1) is particularly simple: 2,3,4,5,… (A000027 in OEIS).
7. The case r=4
Put a:=(a,b,e)∈R3, with e=0, Pa,b,e(w)=w−aw2−bw3−ew4.
We have c0(a)=1, c1(a)=a, c2(a)=2a2+b, c3(a)=5a3+5ab+e,
c4(a)=14a4+21a2b+3b2+6ae, which leads to
Proposition 7.1**.**
If the sequence cn(a,b,e) is positive definite then
The polynomial Pa,b,e′(w) has only real roots if and only if
[TABLE]
If this is the case then cn(a,b,e) is positive definite.
Proof.
It is elementary to see that
[TABLE]
has only real roots if and only if
[TABLE]
has two real roots w−,w+
such that either sgn(Pa,b,e′(w−))=sgn(Pa,b,e′(w+))
or w−=w+ and Pa,b,e′(w−)=0.
Then 3b2≥8ae and
[TABLE]
Since
[TABLE]
we have Pa,b,e′(w−)≤0≤Pa,b,e′(w+) if and only if
[TABLE]
which is equivalent to (33) and implies that 3b2≥8ae.
∎
Remark. If the sequence cn(a,b,e) is positive definite then, by Proposition 3.1,
the free cumulants of the corresponding probability distribution μ(a,b,e)
are the coefficient in the Taylor expansion
[TABLE]
One can check that det(κi+j+2(a,b,e))i,j=02=−e4,
so if e=0 then μ(a,b,e) is never infinitely divisible with respect
to the additive free convolution ⊞.
7.2. A special subclass
Now we will confine ourselves to the case when the coefficients satisfy
[TABLE]
In particular we will describe those parameters a,b,e for which
Pa,b,e′(w) admits complex roots but Na,b,e⊆R.
Proposition 7.3**.**
Assume that b3=4abe+8e2.
Then
[TABLE]
and
[TABLE]
In particular, cn(a,b,e) is positive definite.
On the other hand, if the polynomial Pa,b,e′(w) admits complex roots
w1,w1∈C∖R which
satisfy Pa,b,e(w1)=Pa,b,e(w1)∈R then b3=4abe+8e2 and b4+16be2<0.
Note that if e>0, b=0 then (−b4−32be2)/(256e3)≤e/b2, with equality only if b3=−16e2.
Proof.
It is easy to check that if b3=4abe+8e2 then (36), (37) hold
and for the roots
[TABLE]
of Pa,b,e′(w) we have
[TABLE]
Now assume that w0,w1,w2 are the roots of Pa,b,e′(w), so that
[TABLE]
This implies that w0,w1,w2=0 and
[TABLE]
Then
[TABLE]
Now assume that w0∈R, w1=x+yi, w2=w1=x−yi, x,y∈R, y=0. Then
[TABLE]
so that if Pa,b,e(w1)∈R then w0=x and
[TABLE]
This implies b<0, b3+16e2>0 and b3=4abe+8e2.
∎
On Figure 1 we illustrate the conditions (32), (33) and (35)
for e=1. If (a,b) is below the thin red line then cn(a,b,1) is not positive definite.
If (a,b) is either above the left piece or south-east of the right piece of the thick blue line then
the roots of Pa,b,1′(w) are real and cn(a,b,1) is positive definite.
On the dashed magenta line there are points (a,b) which satisfy b3=4ab+8.
For some of these points, namely when −16<b3<0, the polynomial Pa,b,1′(w) has complex nonreal roots,
but still Na,b,1⊆R and therefore cn(a,b,1) is positive definite.
It turns out that if b3=4abe+8e2 then we are able to write down the generating function.
Proposition 7.4**.**
If b3=4abe+8e2 then
[TABLE]
Consequently,
[TABLE]
[TABLE]
for z in a neighborhood of [math].
Proof.
It is easy to verify (38). This implies that for z
in a neighborhood of [math]
Finally we observe that the case b3=4abe+8e2 comes from the monotonic convolution.
Indeed,
[TABLE]
and every triple (a,b,e)∈R3, satisfying b3=4abe+8e2, b,e=0,
can be represented as (α1+α2,−2α1α2,α12α2) for some α1,α2∈R∖{0}.
8. Symmetric case
In this section we assume that aj=0 whenever j is even, i.e. that the polynomial Pa(w) is odd.
Then Da(z) is odd as well, Ca(z) is even and
cn(a)=0 whenever n is odd. If in addition the sequence cn(a) is positive definite
then the corresponding probability distribution μ(a) is symmetric,
i.e. μ(a)(X)=μ(a)(−X) for every Borel set X⊆R.
The case r=3 was already studied in Subsection 6.6.
8.1. The case r=5.
Assume that a=(0,a,0,b), b=0, Pa(w)=w−aw3−bw5.
Then a necessary condition for positive definiteness of cn(0,a,0,b) is a>0 and 2a2+b≥0.
Proposition 8.1**.**
If a>0, b<0 and 9a2+20b≥0 then the sequence cn(0,a,0,b) is positive definite.
Proof.
We have P0,a,0,b′(w)=1−3aw2−5bw4, so w0 is a root of P0,a,0,b′(w) if and only if
[TABLE]
If a>0, b<0 and 9a2+20b≥0 then all these roots are real.
∎
Example: Take a=(0,2,0,−1).
Then Ca(z) satisfies Ca(z)=1+2z2Ca(z)3−z4Ca(z)5,
equivalently: C_{\mathbf{a}}(z)\big{(}1-z^{2}C_{\mathbf{a}}(z)^{2}\big{)}^{2}=1.
Putting Ca(z):=B(z)2, we get B(z)=1+z2B(z)5, which means that B(z)=B5(z2).
Therefore Ca(z)=B5(z2)2 and, consequently,
c2n(0,2,0,−1)=(n5n+2)2/(5n+2) (A118969).
8.2. The case r=7.
Let us now consider a=(0,a,0,b,0,e), with e=0.
It is easy to check that if cn(0,a,0,b,0,e) is positive definite then a≥0.
Proposition 8.2**.**
If a≥0, b≤0, e>0 and
[TABLE]
then the sequence cn(0,a,0,b,0,e) is positive definite.
Proof.
It is sufficient to prove that (41) implies that the polynomial
hence implies that 25b2−63ae≥0.
Therefore the derivative Q′(t)=−3a−10bt−21et2 has two real roots:
[TABLE]
with 0≤t−≤t+, and we have
[TABLE]
If (42) holds with sharp inequality then we have 1=Q(0)>0, Q(t−)<0, Q(t+)>0 and limt→∞Q(t)=−∞,
so there are t1,t2,t3 such that 0<t1<t−<t2<t+<t3 such that Q(t1)=Q(t2)=Q(t3)=0.
Now we recall that positive definiteness is preserved by pointwise limits.
∎
9. Examples
In this section we provide a record of examples of sequences cn(a)
for which we can verify positive definiteness.
Most of them appear in OEIS, possibly with an additional [math] or 1 term at the beginning.
We refer also to Table 5 in [4].
9.1. Patalan numbers.
Patalan numbers of order p∈R∖{0} (see [13]) are defined
by the generating function
[TABLE]
so that
[TABLE]
Now we observe
Proposition 9.1**.**
The sequence patn(p) is positive definite if and only if ∣p∣≥1.
Moreover, if ∣p∣>1, n≥0 then
[TABLE]
Proof.
One can verify (44) by using the definitions
and basic properties of the beta and gamma functions.
On the other hand
[TABLE]
so the sequence is not positive definite definite if ∣p∣<1.
∎
Formula (43) implies that zAp(z) is the inverse function of
[TABLE]
In particular, if p≥2 is an integer then Ap(z) coincides with Ca(z),
where
[TABLE]
Since P′(w)=(1−pw)p−1 the positive definiteness of the corresponding sequence cn(a) is
also a consequence of Corollary 2.6.
For p=2,3,4,5,6,7,8,9,10
we obtain A000108 (Catalan numbers),
A097188 (or A025748), A025749, A025750, A025751, A025752, A025753.
A025754, A025755,
respectively.
The dilated version of p=4, with a=(3,−4,2), leads to A048779.
Let us also note that for p=−2,−3, −4,−5,−6, −7,−8,−9,−10 the sequence patn(p)
appears in OEIS as A001700, A034171, A034255, A034687, A034789, A034904, A034996,
A035097, A035323, respectively.
9.2. Fuss numbers.
Assume that p≥2 is an integer.
From (2) we have Bp(zp−1)=Ca(z)
for a=(0,0,…,0,1), with p−2 zeros. Therefore the Fuss numbers (nnp+1)np+11
of order p appear as the nonzero terms in the sequence cn(a).
More interestingly, put B(z):=Bp(z)p−1, the generating function
of the sequence (nnp+p−1)np+p−1p−1.
As a consequence of (2) it
satisfies equation B(z)\big{(}1-zB(z)\big{)}^{p-1}=1, so that
zB(z) is the composition inverse of P(w)=w(1−w)p−1.
Therefore
[TABLE]
Since P′(w)=(1−pw)(1−w)p−2, Corollary 2.6
implies that this sequence is positive definite, which is already known [6, 7, 8, 1, 3].
Putting p=2,3,4,5,6,7,8,9,10,11 we get A000108 (Catalan numbers),
A006013, A006632, A118971, A130564, A130565, A234466, A234513, A234573, A235340
respectively.
9.3. Various examples for r=3.
Recall that by Theorem 6.5 the sequence cn(a,b) is positive definite if and only if a2+3b≥0.
Positive definite sequences:
cn(1,1)=A001002,
cn(1,2)=A250886,
cn(1,3)=A276314,
cn(2,1)=A192945,
cn(2,2)=A276310,
cn(2,3)=A250887,
cn(2,−1)=A006013, cn(3,2)=A276315,
cn(3,3)=A295541 (up to a sign),
cn(3,4)=A250888,
cn(3,−1)=A249924,
cn(3,−2)=A085614, cn(3,−3)=A097188 (and also A025748), cn(4,−1)=A276316,
cn(4,−3)=A250885.
Also the following free powers are positive definite (see Proposition 3.2):
cn⊞2(2,1)=A228966,
cn⊞3(2,2)=A231554.
In view of remarks in Subsection 6.6.1
the following sequences are positive definite: c2n⊞2(0,1)=A027307,
c2n⊞3(0,1)=A219535,
2n⋅c2n⊞1/2(0,1)=A003168,
2n⋅c2n⊞3/2(0,1)=A219536.
These equalities can be verified by comparing (13)
with equations for the corresponding generating functions provided in OEIS.
Not positive definite sequences:
cn(−1,−1)=A103779,
cn(−1,−2)=A217361.
9.4. Examples for r=4.
By Theorem 7.2 the following sequences are positive definite:
cn(1,1,−1)=A063020, cn(2,0,−1)=A236339,
cn(2,3,1)=A214692,
cn(3,−3,1)=A006632,
cn(5,−8,4)=A024492. The sequence
cn(2,−2,1)=A121988 (see also A129442) is positive definite by Proposition 7.3.
Using Proposition 7.1 or checking Hankel determinants
one can check that the following sequences are not positive definite:
cn(1,0,1)=A049140,
cn(1,0,−1)=A063033,
cn(−2,0,−1)=A217362,
cn(0,1,1)=A217358,
cn(0,−1,−1)=A217359,
cn(1,1,1)=A063018,
cn(1,−1,1)=A063019,
cn(3,3,1)=A192946,
cn(−2,0,−1)=A217362,
cn(2,1,2)=A214372,
cn(0,2,1)=A055392, cn(2,0,−1)=A236339.
9.5. Monotonic powers.
Define a(k):=(1)⊳k, so that
Pa(1)(w)=P1(w)=w−w2 and
[TABLE]
k composition factors, for example
[TABLE]
In view of Corollary 4.2 all the sequences cn(a(k))
are positive definite.
In particular: cn(a(2))=A121988 (and A129442),
cn(a(3))=A158826, cn(a(4))=A158827, cn(a(5))=A158828.
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