## with application to Lamperti representation

Lo¨ıc Chaumont

AbstractWe obtain a bijection between some set of multidimensional sequences
and the set ofd-type plane forests which is based on the breadth first search algo-
rithm. This coding sequence is related to the sequence of population sizes indexed
by the generations, through a Lamperti type transformation. The same transforma-
tion in then obtained in continuous time for multitype branching processes with dis-
crete values. We show that any such process can be obtained from ad^{2}-dimensional
compound Poisson process time changed by some integral functional. Our proof
bears on the discretisation of branching forests with edge lengths.

### 1 Introduction

A famous result from Lamperti [8] asserts that any continuous state branching pro- cess can be represented as a spectrally positive L´evy process, time changed by the inverse of some integral functional. This transformation is invertible and defines a bijection between the set of spectrally positive L´evy processes and this of con- tinuous state branching processes. The same type of transformation holds between continuous time, integer valued branching processes and downward skip free com- pound Poisson processes. Lamperti’s result is the source of an extensive mathemat- ical literature in which it is mainly used as a tool in branching theory. However, recently Lamperti representation itself has been the focus of some research papers.

In [2] several proofs of this result are proposed and in [4] an extension of the trans- formation to the case of branching processes with immigration is proved. The case of affine processes, which includes continuous state multitype branching processes with immigration, was investigated in [10]. In the latter paper a Lamperti type rep- Lo¨ıc Chaumont – LAREMA – UMR CNRS 6093, Universit´e d’Angers, 2 bd Lavoisier, 49045 Angers cedex 01 e-mail: loic.chaumont@univ-angers.fr

1

resentation in law of affine processes was obtained. Then right after our paper was submitted, the two prepublications [6] and [3], appeared where pathwise construc- tion of affine processes is obtained through Lamperti representation.

In the present work we show through a combinatorial method, an extension of
Lamperti representation to continuous time, integer valued, multitype branching
processes. More specifically, letZ= (Z^{(1)}, . . . ,Z^{(d)})be such a process issued from
x∈Z^{d}+, then we shall prove thatZcan be represented as

(Z_{t}^{(1)}, . . . ,Z_{t}^{(d)}) =x+

d i=1

### ∑

X_{R}^{i,1}_{t}

0Z_{s}^{(i)}ds, . . . ,

d i=1

### ∑

X_{R}^{i,d}_{t}

0Z^{(i)}_{s} ds

!

, t≥0,

whereX^{(i)}= (X^{i,1}, . . . ,X^{i,d}),i=1, . . . ,d, ared independentZ^{d}+-valued compound
Poisson processes. Conversely, givenX^{(i)},i=1, . . . ,d, the above equation admits a
unique solutionZ, andZ is a multitype branching process. Since 0 is an absorbing
state forZ, it is plain that the whole path ofX= (X^{(1)}, . . . ,X^{(d)})is not always needed
in the above transformation. For instance, whend=1, we see that the processX
can be stopped at its first passage time T_{x} at level−x. In the multitype case, we
shall prove that the processesX^{(1)}, . . . ,X^{(d)}can be stopped at timesT_{x}^{(1)}, . . . ,T_{x}^{(d)},
respectively, whereT_{x}= (T_{x}^{(1)}, . . . ,Tx^{(d)})is defined as the ‘first passage time’ at level

−xby the multidimensional random field,
X= (t_{1}, . . . ,t_{d})7→

d i=1

### ∑

X_{t}^{i,j}_{i} , j∈[d]

!

=X_{t}^{(1)}_{1} +. . .+X_{t}^{(d)}_{d} .
The law of the multivariate random timeT_{x}will be given in Theorem 1.

The multitype Lamperti representation is not invertible as in the one dimensional
case. However, by considering the whole branching structure behind the multitype
branching process, we actually obtain in Theorems 2 and 3 a one-to-one pathwise
transformation between(X^{(1)}, . . . ,X^{(d)})and a particular family of processes(Z^{i,}^{j}:
i,j=1, . . .d)satisfying the decomposition

Z_{t}^{(i)}=

d i=1

### ∑

Z_{t}^{i,}^{j} and Z_{t}^{i,j}=x_{i}1_{i=j}+X_{R}^{i,}_{t}^{j}

0Z_{s}^{(i)}ds, t≥0,

whereZ_{t}^{i,}^{j}is the total number of individuals of type jwhose parent has typeiand
who were born before timet.

The proofs of our results are achieved by using a special coding of multitype plane forests based on the breadth first search algorithm. This deterministic one- to-one correspondence between some set of multivariate sequences and multitype forests is stated in Theorem 4 and leads to a Lamperti type representation of dis- crete time, multitype branching processes in Theorem 5. Results in discrete time are displayed and proved in Section 3, whereas the next section is devoted to the statements of our results in continuous time. The latter will be proved in Section 4.

### 2 Main results in continuous time

In all this work, we use the notationR+= [0,∞),Z+={0,1,2, . . .}and for any pos-
itive integerd, we set[d] ={1, . . . ,d}. We also define the following partial order on
R^{d}by settingx= (x_{1}, . . . ,x_{d})≥y= (y_{1}, . . . ,y_{d}), ifxi≥yi, for alli∈[d]. Moreover,
we writex>yifx≥yand if there existsi∈[d]such thatx_{i}>y_{i}. We will denote by
e_{i}thei-th unit vector ofZ^{d}+.

Fixd≥2 and letν= (ν_{1}, . . . ,νd), whereνi is any probability measure onZ^{d}+

such thatνi(e_{i})<1. LetZ= (Z^{(1)}, . . . ,Z^{(d)})be ad-type continuous time andZ^{d}+-
valued branching process with progeny distributionν= (ν_{1}, . . . ,ν_{d})and such that
typei∈[d]has reproduction rateλ_{i}>0. Fori,j∈[d], the quantity

m_{i j}=

### ∑

x∈Z^{d}+

x_{j}ν_{i}(x),

corresponds to the mean number of children of type j, given by an individual of
typei. LetM:= (m_{i j})_{i,j∈[d]}be the mean matrix ofZ. We say that the progeny distri-
butionνis irreducible if the matrixM= (m_{i j})satisfiesm^{(n)}_{i j} >0, for somenand for
alli,j∈[d], wherem^{(n)}_{i j} is the(i,j)-th element of the matrixM^{n}. Recall that ifνis
irreducible, then according to Perron-Frobenius Theorem, it admits a unique eigen-
valueρwhich is simple, positive and with maximal modulus. If moreover,νis non
degenerate, that is if individuals have exactly one offspring with probability strictly
less than 1, then extinction holds if and only ifρ≤1, see [7], [12] and Chapter V
of [1]. Ifρ=1, we say thatZis critical and ifρ<1, we say thatZis subcritical.

We now define the underlying compound Poisson process in the Lamperti repre-
sentation ofZthat will be presented in Theorems 2 and 3. LetX= (X^{(1)}, . . . ,X^{(d)}),
whereX^{(i)},i∈[d]ared independentZ^{d}-valued compound Poisson processes. We
assume thatX_{0}^{(i)}=0 and thatX^{(i)}has rateλ_{i}and jump distribution

µi(k) = ν˜i(k)

1−ν˜i(0), if k6=0 and µi(0) =0, (1) where

ν˜_{i}(k_{1}, . . . ,k_{d}) =ν_{i}(k_{1}, . . . ,ki−1,k_{i}+1,ki+1, . . . ,k_{d}). (2)
In particular, with the notationX^{(i)}= (X^{i,1}, . . . ,X^{i,d}), for alli=1, . . . ,d, the pro-
cessX^{i,i}is aZ-valued, downward skip free, compound Poisson process, i.e.∆X_{t}^{i,i}=
X_{t}^{i,i}−X_{t−}^{i,i}≥ −1,t≥0, withX0−=0 and for alli6=j, the processX^{i,j}is an increas-
ing compound Poisson process. We emphasize that in this definition, some of the
processesX^{i,j},i,j∈[d]can be identically equal to 0.

We first present a result on passage times of the multidimensional random field

X :(t_{1}, . . . ,t_{d})7→

d

### ∑

i=1

X_{t}^{i,}_{i}^{j},j∈[d]

!

=X_{t}^{(1)}_{1} +. . .+X_{t}^{(d)}

d ,

which is a particular case of additive L´evy process, see [11] and the references therein. Henceforth, a process such as X will be called anadditive(downward skip free)compound Poisson process.

Theorem 1.Let x= (x_{1}, . . . ,x_{d})∈Z^{d}+. Then there exists a(unique)random time
T_{x}= (T_{x}^{(1)}. . . ,T_{x}^{(d)})∈R^{d}+such that almost surely,

x_{j}+

### ∑

i,T_{x}^{(i)}<∞

X^{i,j}(T_{x}^{(i)}) =0, for all j such that T_{x}^{(}^{j)}<∞, (3)

and if T_{x}^{0}is any random time satisfying(3), then T_{x}^{0}≥T_{x}. The time T_{x}will be called
the first passage time of the additive compound Poisson process X at level−x.

The process(T_{x},x∈Z^{d}+)is increasing and additive, that is, for all x,y∈Z^{d}+,

T_{x+y}^{(d)}=T_{x}+T˜_{y}, (4)

whereT˜_{y}is an independent copy of T_{y}. The law of T_{x}onR^{d}+is given by
P(T_{x}∈dt,X_{t}^{i,}^{j}

i =x_{i,}_{j},1≤i,j≤d) =

det(−x_{i,}_{j})
t_{1}t_{2}. . .t_{d}

d

### ∏

i=1

P(X_{t}^{i,}^{j}

i =xi,j,1≤j≤d)dt_{1}dt_{2}. . .dt_{d},
where the support of this measure is included in

x_{i j}∈Z:x_{i j}≥0,x_{ii}≤0,∑^{d}_{i=1}xi,j=−x_{i} .
Note that from the additivity property (4) of(T_{x},x∈Z^{d}+), we derive that the law of
this process is characterised by the law of the variablesT_{e}_{i}fori∈[d].

As the above statement suggests, some coordinates of the timeT_{x} may be infinite.

More specifically, we have:

Proposition 1.Assume thatνis irreducible and non degenerate.

1. Ifνis(sub)critical, then almost surely, for all x∈Z^{d}+and for all i∈[d], T_{x}^{(i)}<∞.

2. Ifνis super critical, then for all x∈Z^{d}+, with some probability p>0, Tx^{(i)}=∞,
for all i∈[d]and with probability1−p, T_{x}^{(i)}<∞, for all i∈[d].

There are instances of reducible distributions ν such that for some x∈Z^{d}+, with
positive probability,T_{x}^{(i)}<∞, for alli∈AandT_{x}^{(i)}=∞, for alli∈B,(A,B)being
a non trivial partition of[d]. It is the case for instance whend=2, forx= (1,1),
X^{1,2}=X^{2,1}≡0, 0<m_{11}<1 andm_{22}>1.

Then we defined-type branching forests with edge lengths as finite sets of inde-
pendent branching trees with edge lengths. We say that such a forest is issued from
x= (x_{1}, . . . ,x_{d})∈Z^{d}+(at timet=0), if it containsx_{i} trees whose root is of typei.

The discrete skeleton of a branching forest with edge lengths is a discrete branching
forest with progeny distributionν. The edges issued from vertices of typeiare ex-
ponential random variables with parameterλi. These random variables are mutually
independent and are independent of the discrete skeleton. A realisation of such a
forest is represented in Figure 1. Then to eachd-type forest with edge lengths,F,
is associated the branching processZ= (Z^{(1)}, . . . ,Z^{(d)}), whereZ^{(i)}is the number of
individuals inF, alive at timet.

Definition 1.Fori6=j, we denote byZ_{t}^{i,j} the total number of individuals of type j
whose parent has typeiand who were born before timet. The definition ofZ_{t}^{i,i}for
i∈[d]is the same, except that we add the number of roots of typeiand we subtract
the number of individuals of typeiwho died before timet.

More formal definitions of branching forests with edge lengths and processesZ^{i,}^{j}
will be given in sections 4.2 and 4.3, see in particular (24).

Then we readily check that the branching processZ= (Z_{1}, . . . ,Z_{d})which is as-
sociated to this forest can be expressed in terms of the processesZ^{i,j}, as follows:

Z_{t}^{(}^{j)}=

d

### ∑

i=1

Z_{t}^{i,}^{j}, j∈[d].

*t*

Fig. 1 A two type forest with edge lengths issued fromx= (2,2). Vertices of type 1 (resp. 2) are
represented in black (resp. white). At timet,Z_{t}^{1,1}=1,Z_{t}^{1,2}=2,Z_{t}^{2,1}=3 andZ_{t}^{2,2}=2.

The next theorem asserts that from a givend-type forest with edge lengthsF, issued

fromx= (x_{1}, . . . ,x_{d}), we can construct ad-dimensional additive compound Poisson

process X= (∑^{d}_{i=1}X_{t}^{i,}_{i}^{j}, j∈[d],(t_{1}, . . . ,t_{d})∈R^{d}+)stopped at its first passage time
of −x, such that the branching processZ associated toF can be represented as a
time change of X. This extends the Lamperti representation to multitype branching
processes.

Theorem 2.Let x= (x_{1}, . . . ,x_{d})∈Z^{d}+and let F be a d-type branching forest with
edge lengths, issued from x, with progeny distributionνand reproduction ratesλ_{i}.
Then the processes Z^{i,}^{j}, i,j∈[d] introduced in Definition 1 admit the following
representation:

Z_{t}^{i,}^{j}=xi1_{i=j}+X^{i,}^{j}

R_{t}

0Z^{(i)}s ds, t≥0, (5)

where

X^{(i)}= (X^{i,1},X^{i,2}, . . . ,X^{i,d}), i=1, . . . ,d,

are independentZ^{d}+-valued compound Poisson processes with respective rates λi

and jump distributionsµidefined in(1), stopped at the first hitting time T_{x}of−x by
the additive compound Poisson process,X=

∑^{d}_{i=1}X_{t}^{i,}_{i}^{j}, j∈[d],(t_{1}, . . . ,t_{d})∈R^{d}+

, that is,

X_{t}^{(i)}1

{t<T_{x}^{(i)}}+ (X^{i,1}

T_{x}^{(i)}, . . . ,X^{i,d}

T_{x}^{(i)})1

{t≥T_{x}^{(i)}}, t≥0.

In particular the multitype branching process Z, issued from x= (x_{1}, . . . ,x_{d})∈
R^{d}+admits the following representation,

(Z_{t}^{(1)}, . . . ,Z_{t}^{(d)}) =x+

d i=1

### ∑

X_{R}^{i,1}_{t}

0Z_{s}^{(i)}ds, . . . ,

d i=1

### ∑

X_{R}^{i,d}_{t}

0Z^{(i)}_{s} ds

!

, t≥0. (6)

Moreover, the transformation(5)is invertible, so that the processes Z^{i,}^{j}, i,j∈[d]

can be recovered from the processes X^{(i)}, i∈[d].

Note that in Theorem 2,Tx^{(i)}actually represents the total length of the branches is-
sued from vertices of typeiin the forestF.

Conversely, the following theorem asserts that an additive compound Poisson pro- cessXbeing given, we can construct a multitype branching forest whose branching processZis the unique solution to equation (6).

Theorem 3.Let x= (x_{1}, . . . ,x_{d})∈Z^{d}+and

X^{(i)}= (X^{i,1},X^{i,2}, . . . ,X^{i,d}), i=1, . . . ,d,

be independentZ^{d}+valued compound Poisson processes with respective ratesλi>0
and jump distributions µi, stopped at the first hitting time T_{x} of−x by the addi-
tive compound Poisson process(t_{1}, . . . ,t_{d})7→

∑^{d}_{i=1}X_{t}^{i,j}

i ,j∈[d]

. Then there is a
branching forest with edge lengths, with progeny distributionν and reproduction
ratesλ_{i}>0such that the processes Z^{i,j} of Definition1satisfy relation(5). More-
over, the branching process Z= (Z^{(1)}, . . . ,Z^{(d)})associated to this forest is the unique
solution of the equation,

(Z_{t}^{(1)}, . . . ,Z_{t}^{(d)}) =x+

d i=1

### ∑

X^{i,1}

R_{t}

0Zs^{(i)}ds, . . . ,

d

### ∑

i=1X^{i,d}

R_{t}
0Z^{(i)}s ds

!

, t≥0.

We emphasize that Theorems 2 and 3 do not define a bijection between the set of
branching forests with edge lengths and this of additive compound Poisson pro-
cesses, as in the discrete time case, see Section 3. Indeed, in the continuous time
case, when constructing the processesZ^{i,}^{j} as in Definition 1, at each birth time,
we lose the information of the specific individual who gives birth. In particular, the
forest which is constructed in Theorem 3 is not unique. This lost information is
preserved in discrete time and the breadth first search coding that is defined in Sub-
section 3.2 allows us to define a bijection between the set of discrete forests and this
of coding sequences.

### 3 Discrete multitype forests 3.1 The space of multitype forests

We will denote byF the set of plane forests. More specifically, an elementf∈F is a directed planar graph with no loops on a possibly infinite and non empty set of verticesv=v(f), with afinitenumber of connected components, such that each vertex has a finite inner degree and an outer degree equals to 0 or 1. The elements ofF will simply be called forests.The connected components of a forest are called thetrees. A forest consisting of a single connected component is also called a tree.

In a treet, the only vertex with outer degree equal to 0 is called therootoft. It will
be denoted byr(t). The roots of the connected components of a forestfare called
the roots off. For two verticesuandvof a forestf, if(u,v)is a directed edge off,
then we say thatuis achildofv, or thatvis theparentofu. The setv(f)of vertices
of each forestfwill be enumerated according to the usual breadth first search order,
see Figure 2. We emphasize that we begin by enumerating the roots of the forest
from the left to the right. In particular, our enumeration is not performed tree by
tree. If a forestfcontains at leastnvertices, then then-th vertex offis denoted by
u_{n}(f). When no confusion is possible, we will simply denote then-th vertex byu_{n}.

Ad-type forest is a couple(f,cf), wheref∈Fandcfis an applicationcf:v(f)→
[d]. Forv∈v(f), the integercf(v)is called thetype(or thecolor) ofv. The set of fi-
nited-type forests will be denoted byFd. An element(f,c_{f})∈Fdwill often simply
be denoted byf. We assume that for anyf∈Fd, ifu_{i},u_{i+1}, . . . ,u_{i+j}∈v(f)have the
same parent, thenc_{f}(u_{i})≤c_{f}(u_{i+1})≤. . .≤c_{f}(u_{i+}_{j}). Moreover, ifu_{1}, . . . ,u_{k}are the
roots off, thencf(u_{1})≤. . .≤cf(u_{k}). For eachi∈[d]we will denote byu^{(i)}n =u^{(i)}n (f)
then-th vertex of typeiof the forestf∈Fd, see Figure 2.

*u*_{1}^{(1)} *u*^{(2)}_{1} *u*^{(2)}_{2} *u*^{(2)}_{3}

*u*_{1 }, *u*_{2 },*u*^{(1)}_{2} *u*_{5 },

*u*_{6 },*u*_{3}^{(1)}

*u*_{4 },
*u*_{3 },

Fig. 2 A two type forest labeled according to the breadth first search order. Vertices of type 1 (resp. 2) are represented in white (resp. black).

### 3.2 Coding multitype forests

The aim of this subsection is to obtain a bijection between the set of multitype forests and some particular set of integer valued sequences which has been intro- duced in [5]. This bijection, which will be called acoding, depends on the breadth first search ordering defined in the previous subsection. We emphasize that this cod- ing is quite different from the one which is defined in [5].

Definition 2.LetS_{d}be the set of
Z^{d}d

-valued sequences,x= (x^{(1)},x^{(2)}, . . . ,x^{(d)}),
such that for alli∈[d],x^{(i)}= (x^{i,1}, . . . ,x^{i,d})is aZ^{d}-valued sequence defined on some
interval of integers,{0,1,2, . . . ,n_{i}}, 0≤n_{i}≤∞, which satisfiesx^{(i)}_{0} =0 and ifn_{i}≥1,
then

(i)fori6=j, the sequence(x^{i,}_{n}^{j})0≤n≤n_{i} is nondecreasing,
(ii)for alli,x^{i,i}_{n+1}−x^{i,i}n ≥ −1, 0≤n≤n_{i}−1.

A sequencex∈S_{d} will sometimes be denoted byx= (x^{i,}_{k}^{j},0≤k≤n_{i},i,j∈[d])
and for more convenience, we will sometimes denote x^{i,}_{k}^{j} by x^{i,}^{j}(k). The vector

n= (n_{1}, . . . ,n_{d})∈Z^{d}+, whereZ+=Z+∪ {+∞}will be called the length ofx.

Recall the definition of the order onR^{d}, from the beginning of Section 2 and let us
setU_{s}={i∈[d]:s_{i}<∞}, for any s∈Z^{d}+. Then the next lemma extends Lemma 2.2
in [5] to the case where the smallest solution of a system such as(r,x)in (7) may
have infinite coordinates.

Lemma 1.Let x∈S_{d}whose lengthn= (n_{1}, . . . ,n_{d})is such that n_{i}=∞for all i(i.e.

Un=/0)and letr= (r_{1}, . . . ,r_{d})∈Z^{d}+. Then there existss= (s_{1}, . . . ,s_{d})∈Z^{d}+such
that

(r,x) r_{j}+

d i=1

### ∑

x^{i,}^{j}(s_{i}) =0, j∈U_{s}, (7)

(we will say thatsis a solution of the system(r,x))and such that any other solution
qof(r,x)satisfiesq≥s. Moreover we have s_{i}=min{q:x^{i,i}q =min_{0≤k≤s}_{i}x^{i,i}_{k}}, for
all i∈U_{s}.

The solutionswill be calledthe smallest solutionof the system(r,x). We empha-
size that in(7), we may have U_{s}=/0, so that according to this definition, the smallest
solution of the system(r,x)may be infinite, that is s_{i}=∞for all i∈[d]. Note also
that in(7)it is implicit that∑i∈[d]\U_{s}x^{i,}^{j}(s_{i})<∞, for all j∈U_{s}.

Proof. This proof is based on the simple observation that for fixed j, when at least
one of the indicesk_{i}’s fori6=j increases, the term∑i6=jx^{i,}^{j}(k_{i})may only increase
and whenk_{j}increases, the termx^{j,j}(k_{j})may decrease only by jumps of amplitude

−1.

First recall the notationU_{s}, for s∈Z^{d}+introduced before Lemma 1 and setv^{(1)}_{j} =
r_{j}and forn≥1,

k^{(n)}_{j} =inf{k:x_{k}^{j,j}=−v^{(n)}_{j} } and v^{(n+1)}_{j} =r_{j}+

### ∑

i6=j

x^{i,j}(k^{(n)}_{i} ),

where inf /0=∞. Set also k^{(0)}=0 andU_{k}(0)= [d]. Then note that since fori6=j, the
x^{i,}^{j}’s are positive and increasing, we have

k^{(n)}≤k^{(n+1)} and U_{k}(n+1) ⊆U_{k}(n), n≥0.
Moreover, for eachn≥0,

r_{j}+

### ∑

i6=j

x^{i,}^{j}(k^{(n)}_{i} ) +x^{j,}^{j}(k^{(n)}_{j} )≥0, j∈U_{k}(n). (8)
Define

n_{0}=inf

n≥1 :r_{j}+

### ∑

i6=j

x^{i,}^{j}(k^{(n)}_{i} ) +x^{j,j}(k^{(n)}_{j} ) =0, j∈U_{k}(n) ,

where in this definition, we consider thatr_{j}+∑i6=jx^{i,}^{j}(k^{(n)}_{i} ) +x^{j,}^{j}(k^{(n)}_{j} ) =0 is sat-
isfied for all j∈U_{k}(n) ifU_{k}(n) =/0. Note that k^{(n)}=k^{(n}^{0}^{)} andU_{k}(n) =U

k^{(n}^{0}^{)}, for all
n≥n_{0}. The indexn_{0} can be infinite and in general, we have k^{(n}^{0}^{)}=limn→∞k^{(n)}.
Then the smallest solution of the system (r,x) in the sense which is defined in
Lemma 1 is k^{(n}^{0}^{)}.

Indeed, (7) is clearly satisfied for s=k^{(n}^{0}^{)}. Then let q∈Z^{d}+satisfying (7), that is
r_{j}+

### ∑

i6=j

x^{i,}^{j}(q_{i}) +x^{j,j}(q_{j}) =0, j∈U_{q}. (9)

We can prove by induction that q≥k^{(n)}, for alln≥1. Firstly for (9) to be satis-
fied, we should haveq_{j} ≥inf{k:x^{j,}^{j}(k) =−r_{j}}, for all j∈U_{q}, hence q≥k^{(1)}.

Now assume that q≥k^{(n)}. ThenU_{q}⊆U_{k}(n) and from (8) and (9) for each j∈U_{q},
qj≥inf{k:x^{j,}^{j}(k) =−(r_{j}+∑i6=jx^{i,}^{j}(k^{(n)}_{i} ))}, hence q≥k^{(n+1)}.

Finally the fact thats_{i}=min{q:x^{i,i}_{q} =min_{0≤k≤s}_{i}x^{i,i}_{k}}, for alli∈U_{s}readily follows
from the above construction ofs_{i}. ut

Let(f,c_{f})∈Fd,u∈v(f)and denote byp_{i}(u)the number of children of typeiof
u. For eachi∈[d], letn_{i}≥0 be the number of vertices of typeiinv(f). Then we
define the applicationΨ fromFdtoS_{d}by

Ψ(f,cf) =x, (10)

wherex= (x^{(1)}, . . . ,x^{(d)})and for alli∈[d],x^{(i)} is thed-dimensional chainx^{(i)}=
(x^{i,1}, . . . ,x^{i,d}), with lengthn_{i}, whose values belong to the setZ^{d}, such thatx^{(i)}_{0} =0
and ifn_{i}≥1, then

x^{i,j}_{n+1}−x^{i,}_{n}^{j}=p_{j}(u^{(i)}_{n+1}), ifi6=j and x^{i,i}_{n+1}−x^{i,i}_{n} =p_{i}(u^{(i)}_{n+1})−1, 0≤n≤n_{i}−1.
(11)
We recall thatu^{(i)}_{n} is then-th vertex of typeiin the breadth first search order off.

We will see in Theorem 4 that(n_{1}, . . . ,n_{d})is actually the smallest solution of the
system(r,x), wherer_{i}is the number of roots of typeiof the forestf. This leads us
to the following definition.

Definition 3.Fix r= (r_{1}, . . . ,r_{d})∈Z^{d}+, such that r>0.

(i)We denote byΣ_{d}^{r}the subset ofS_{d} of sequencesxwith length n= (n_{1}, . . . ,n_{d})∈
Z^{d}+such that n is the smallest solution of the system(r,x), where for all¯ i∈[d],

¯

x^{(i)}_{k} =x_{k}^{(i)}, ifk≤n_{i}and ¯x^{(i)}_{k} =x^{(i)}_{k}

i , ifk≥n_{i}. We will also say that n is the smallest
solution of the system(r,x).

(ii)We denote byF_{d}^{r}, the subset ofFdofd-type forests containing exactlyr_{i}roots
of typei, for alli∈[d].

The following theorem gives a one to one correspondence between the setsF_{d}^{r}and
Σ_{d}^{r}.

Theorem 4.Letr= (r_{1}, . . . ,r_{d})∈Z^{d}+, be such thatr>0. Then for all(f,cf)∈F_{d}^{r},
the chain x=Ψ(f,c_{f})belongs to the setΣ_{d}^{r}. Moreover, the mapping

Ψ:F_{d}^{r}→Σ_{d}^{r}
(f,c_{f})7→Ψ(f,c_{f})
is a bijection.

Proof. In this proof, in order to simplify the notation, we will identify the sequence xwith its extension ¯xintroduced in Definition 3.

Let(f,c_{f})be a forest ofF_{d}^{r}and let s= (s_{1}, . . . ,s_{d})∈Z^{d}+, wheres_{i}is the number
of vertices of typeiinf. We define a subtree of typei∈[d]of(f,c_{f})as a maximal

connected subgraph of(f,c_{f})whose all vertices are of typei. Formally,tis a subtree
of type iof (f,c_{f}), if it is a connected subgraph whose all vertices are of typei
and such that eitherr(t)has no parent or the type of its parent is different fromi.

Moreover, if the parent of a vertexv∈v(t)^{c}belongs tov(t), thencf(v)6=i.

Leti∈[d]and assume first thatsi<∞(i.e.i∈Us) and letki≤sibe the number
of subtrees of typeiinf. Then we can check that the lengths_{i}of the sequencex^{i,i}
corresponds to its first hitting time of level−k_{i}, i.e.

s_{i}=inf{n:x^{i,i}_{n} =−k_{i}}. (12)
Indeed, let us rank the subtrees of typeiinfaccording to the breadth first search
order of their roots, so that we obtain the subforest of typei:t_{1}, . . . ,t_{k}_{i} and letx^{0}be
its Lukasiewicz-Harris coding path, that isx^{0}_{0}=0 and

x^{0}_{n+1}−x^{0}_{n}=p(un+1)−1, 0≤n≤s_{i}−1,

whereu_{n} is then-th vertex in the breadth first search of this subforest and p(u_{n})
is its number of children. We refer to [9] for the coding of forests through their
Lukasiewicz-Harris coding path. Then we readily check that both sequences have
the same length and end up at the same level, i.e.

inf{n:x^{0}_{n}=−k_{i}}=inf{n:x^{i,i}_{n} =−k_{i}}. (13)
Ifs_{i}=∞then eitherk_{i}=∞and (12) holds, ork_{i}<∞and at least one of the sub-
trees of typeiin the forest is infinite. In this case, we can still comparex^{i,i} to the
Lukasiewicz-Harris coding pathx^{0}in order to obtain (13), so that (12) also holds.

Now let us check that s is a solution of the system(r,x), that is
r_{j}+

d i=1

### ∑

x^{i,}^{j}(s_{i}) =0, j∈U_{s}. (14)
Let j∈U_{s}, thenr_{j}+∑i6=jx^{i,}^{j}(s_{i})clearly represents the total number of vertices of
type jinv(f)which are either a root of type jor whose parent is of a type different
from j, i.e. it represents the total number of subtrees of type j inf. On the other
hand, from (12),−x^{j,j}(s_{j})≥0 is the number of these subtrees. We conclude that
equation (14) is satisfied.

It remains to check that s is the smallest solution of the system (r,x). As in
Lemma 1, set k^{(0)}=0 and for all j∈[d],

k^{(n)}_{j} =inf

k:x_{k}^{j,}^{j}=−(r_{j}+

### ∑

i6=j

x^{i,}^{j}(k_{i}^{(n−1)})) , n≥1. (15)

Then from the proof of Lemma 1, we have to prove that s=lim→∞k^{(n)}. Recall the
coding which is defined in (11). For all j∈[d], once we have visited ther_{j} first
vertices of type jwhich are actually roots of the forest, we have to visit the whole
corresponding subtrees, so that, if the total number of vertices of type jin(f,c_{f})is

finite, i.e. j∈U_{s}, then the chainx^{j,}^{j}first hits−r_{j}at timek^{(1)}_{j} <∞. Then at timek^{(1)}_{j} ,
an amount of∑i6=jx^{i,}^{j}(k^{(1)}_{i} )more subtrees of type jhave to be visited. So the chain
x^{j,}^{j}has to hit−(r_{j}+∑i6=jx^{i,}^{j}(k^{(1)}_{i} ))at timek^{(2)}<∞. This procedure is iterated until
the last vertex of type jis visited, that is until times_{j}=limn→∞k^{(n)}_{j} <∞(note that
the sequencek^{(n)}_{j} is constant after some finite index). Besides, from (15), we have

s_{j}=inf{k:x_{k}^{j,}^{j}=−(r_{j}+

### ∑

i6=j

x^{i,}^{j}(s_{i}))}, n≥1, j∈U_{s}.

On the other hand, if the total number of vertices of type jin(f,c_{f})is infinite, then
k^{(n)}_{j} tends to∞(it can be infinite by some rank). So that we also haves_{j}=limn→∞k^{(n)}_{j}
in this case. Therefore, s is the smallest solution of(r,x).

Now letx∈Σ_{d}^{r} with length s, then we construct a forest(f,c_{f})∈F_{d}^{r} such that
Ψ(f,c_{f}) =x, generation by generation, using the definition ofΨ in (10) as follows.

At generationn=1, for eachi∈[d], we taker_{i} vertices of typei. We rank these

r_{1}+. . .+r_{d} vertices as it is defined in Subsection 3.1. Then to thek-th vertex of

typei, we give∆x^{i,}_{k}^{j}:=x^{i,j}_{k} −x^{i,}_{k−1}^{j} children of type j∈[d]if j6=i and∆x^{i,i}_{k} +1
childr en of typei. We rank vertices of generationn=2 and to ther_{i}+k-th vertex
of typei, we give∆x^{i,}_{r}^{j}

i+k children of type j∈[d], if j6=iand∆x^{i,i}_{r}

i+k+1 children
of typei, and this procedure is repeated generation by generation. Proceeding this
way, until the steps∆x^{i,}s_{i}^{j},i,j∈[d], we have constructed a forest ofF_{d}^{r}. Indeed the
total number of children of type jwhose parent is of typei6=jisx^{i,}^{j}(s_{i}), hence, the
total number of children of type jwhich is a root or whose parent is different from
jisr_{j}+∑i6=jx^{i,j}(s_{i}). Moreover, each branch necessarily ends up with a leaf, since

∆x^{i,j}_{s}

i+1=0, for alli6=jand∆x^{i,i}_{s}

i+1=−1. Therefore we have constructed a forest
(f,cf)ofF_{d}^{r}such thatΨ(f,cf) =xand we have proved thatΦ is onto.

Finally, let us denote the forest (f,c_{f}) which is reconstructed from xthrough
the above procedure byΦ(x), then the applicationΦ is actually the inverse ofΨ.
Indeed, we can check from the defintion ofΦ above and that ofΨ in (10) that for
all(f,c_{f})∈F_{d}^{r},Φ(Ψ((f,c_{f}))) = (f,c_{f}). ThereforeΨis one-to-one.

### 3.3 Representing the sequence of generation sizes

To eachf∈F_{d}^{r}we associate the chainz= (z^{(1)}, . . . ,z^{(d)})indexed by the successive
generations inf, where for eachi∈[d], andn≥1,z^{(i)}(n)is the size of the population
of typeiat generationn. More formally, we say that the (index of the) generation
ofu∈v(f)isnifd(r(t_{u}),u) =n, wheret_{u}is the tree offwhich containsu,r(t_{u})is
the root of this tree anddis the usual distance in discrete trees. In order to simplify
the notation, we set|u|=d(r(t_{u}),u). Let us denote byh(f)the index of the highest
generation inf. Thenz^{(i)}is defined by

z^{(i)}(n) =

Card{u∈v(f):c_{f}(u) =i,|u|=n}ifn≤h(f),

0 ifn≥h(f) +1. (16)

We also define the chainsz^{i,}^{j}, fori,j∈[d], as follows:z^{i,}^{j}(0) =0 ifi6=j,z^{i,i}(0) =r_{i},
and forn≥1,

z^{i,}^{j}(n) =ri1_{i=j}+

### ∑

|u|≤n−1

1_{c}

f(u)=i(p_{j}(u)−1_{i=}_{j}). (17)
In words, ifi6= jthenz^{i,}^{j}(n)is the total number of vertices of type jwhose parent
is of typeiin the firstngenerations of the forestf. Ifi= jthen we only count the
number of vertices of typeiwith at least one younger brother of typeiand whose
parent is of typeiin thenfirst generations. To this number, we subtract the number
of vertices of typeiwith no children of typei, whose generation is less or equal than
n−1. Then it is not difficult to check the following relation:

z^{(}^{j)}(n) =

d i=1

### ∑

z^{i,}^{j}(n),n≥0, j∈[d]. (18)
We end this subsection by a lemma which provides a relationship between the chains
x^{i,}^{j} andz^{i,j}, where x=Ψ(f,c_{f}). This result is the deterministic expression of the
Lamperti representation of Theorem 5 below and its continuous time counterpart in
Theorems 2 and 3.

Lemma 2.The chain z^{i,}^{j}may be obtained as the following time change of the chain
x^{i,}^{j}:

z^{i,}^{j}(n) =x^{i,}^{j}(∑^{n−1}_{k=0}z^{(i)}(k)), n≥1, i,j∈[d], i6=j, (19)
z^{i,i}(n) =r_{i}+x^{i,i}(∑^{n−1}_{k=0}z^{(i)}(k)), n≥1, i∈[d]. (20)
In particular, we have

z^{(}^{j)}(n) =r_{j}+

d i=1

### ∑

x^{i,}^{j}(∑^{n−1}_{k=0}z^{(i)}(k)), n≥1, j∈[d]. (21)
Moreover, given x^{i,}^{j}, i,j∈[d], the chains z^{i,}^{j}, i,j∈[d]are uniquely determined by
equations(18),(19)and(20).

Proof. It suffices to check relations (19) and (20). Then (21) will follow from (18).

But (19) and (20) are direct consequences of the definition of the chainsx^{i,}^{j}andz^{i,}^{j}
in (11) and (17) respectively.

### 3.4 Application to discrete time branching processes

Recall that ν= (ν_{1}, . . . ,ν_{d})is a progeny distribution, such that the νi’s are any
probability measures onZ^{d}+, such thatνi(e_{i})<1. Let(Ω,G,P)be some measurable
space on which, for any r∈Z^{d}+such that r>0, we can define a probability measure
Prand a random variable(F,c_{F}):(Ω,G,Pr)→F_{d}^{r}whose law underPris this of
a branching forest with progeny lawν. Then we construct from(F,c_{F})the random
chains,X = (X^{(1)}, . . . ,X^{(d)}),Z= (Z^{(1)}, . . . ,Z^{(d)})andZ^{i,}^{j},i,j∈[d], exactly as in
(11), (16) and (17), respectively. In particular, X =Ψ(F,c_{F}). We can check that
underPr,Z is a branching process with progeny distributionν. More specifically,
recall from (2) the definition of ˜νi, then the random processesX andZ satisfy the
following result.

Theorem 5.Letr∈Z^{d}+be such thatr>0and let(F,c_{F})be anF_{d}^{r}-valued branching
forest with progeny law ν under Pr. Let N= (N_{1}, . . . ,N_{d})∈Z^{d}+, where N_{i} is the
number of vertices of type i in F.Then,

1. The random variable N is almost surely the smallest solution of the system(r,X)
in the sense of Definition3. Ifνis irreducible, non degenerate and(sub)critical,
then almost surely, N_{i}<∞, for all i∈[d]. Ifνis irreducible, non degenerate and
supercritical, then with some probability p>0, N_{i}=∞, for all i∈[d]and with
probability1−p, N_{i}<∞, for all i∈[d].

2. On the space(Ω,G,P), we can define independent random walksX˜^{(i)}, i∈[d],
with respective step distributions ν˜i, i∈[d], such that X˜_{0}^{(i)} =0 and if N˜ =
(N˜_{1}, . . .N˜_{d})∈Z^{d}+ is the smallest solution of the system(r,X), then the follow-˜
ing identity in law

(X_{k}^{(i)},0≤k≤N_{i},i∈[d])^{(d)}= (X˜_{k}^{(i)},0≤k≤N˜_{i},i∈[d])
holds.

3. The joint law of X_{N}and N is given as follows: for any integers n_{i}and k_{i j}, i,j∈[d],
such that n_{i}>0, k_{i j}∈Z+, for i6=j,−k_{j j}=r_{j}+∑i6=jk_{i j}and n_{i}≥ −k_{ii},

Pr

X_{n}^{i,}^{j}

i =k_{i j},i,j∈[d]and N=n

=

det(−k_{i j})
n_{1}n_{2}. . .n_{d}

d

### ∏

i=1ν_{i}^{∗n}^{i}

k_{i1}, . . . ,k_{i(i−1)},n_{i}+k_{ii},k_{i(i+1)}, . . . ,k_{id}
.

4. The random process Z is a branching process with progeny lawν, which is re- lated to X through the time change:

Z^{(i)}(n) =

d

### ∑

i=1

X^{i,j}(∑^{n−1}_{k=1}Z^{(i)}(k)), n≥1. (22)

Proof. The fact thatNis the smallest solution of the system(r,X)is a direct con-
sequence of Theorem 4 and the definition ofX, that isΨ(F,c_{F}) =X. Assume that
νis irreducible, non degenerate and (sub)critical. Then since the forestF contains
almost surely a finite number of vertices, all coordinates ofN must be finite from
Theorem 4. Ifνis irreducible, non degenerate and supercritical, then with probabil-
ityp>0 the forestFcontains an infinite number of vertices of typei, for alli∈[d]

and with probability 1−pits total population is finite. Then the result also follows from Theorem 4.

In order to prove part 2, let(F_{n},c_{F}_{n})with(F_{1},c_{F}_{1}) = (F,c_{F}), be a sequence of
independent and identically distributed forests. Let us defineX^{n}=Ψ(F_{n},c_{F}_{n})and
then let us concatenate the processesX^{n}= (X^{n,(1)}, . . . ,X^{n,(d)})in a process that we
denote ˜X. More specifically, let us denote byN_{i}^{n}the length ofX^{n,(i)}, then the process
obtained from this concatenation is ˜X= (X˜^{(1)}, . . . ,X˜^{(d)}), where ˜X_{0}^{(i)}=0,N_{i}^{0}=0 and

X˜_{k}^{(i)}=X˜^{(i)}

N_{i}^{0}+...+N_{i}^{n−1}+X^{n,(i)}

k−(N_{i}^{0}+...+N_{i}^{n−1}),

ifN_{i}^{0}+. . .+N_{i}^{n−1}≤k≤N_{i}^{0}+. . .+N_{i}^{n}, n≥1.

Note that ˜X is obtained by coding the forests (F_{n},cFn),n≥1 successively. Then
it readily follows from the construction of ˜X and the branching property that the
coordinates ˜X^{(i)}are independent random walks with step distribution ˜νi. Moreover
N is a solution of the system(r,X˜), so its smallest solution, sayN^{0}, is necessarily
smaller thanN. This means thatN^{0}is a solution of the system(r,X), henceN^{0}=N.

The third part is a direct consequence of the first part and the multivariate ballot Theorem which is proved in [5], see Theorem 3.4 therein.

Then part 4, directly follows from the definition ofZand Lemma 2.

Conversely, from any random walk whose step distribution is given by (2), we can construct a unique branching forest with lawPr. The following result is a direct consequence of Theorems 4 and 5.

Theorem 6.LetX˜^{(i)}, i∈[d]be d independent random walks defined on(Ω,G,P),
whose respective step distributions areν˜i, and setX˜ = (X˜^{(1)}, . . . ,X˜^{(d)}). Letr∈Z^{d}+

such thatr>0and letN be the smallest solution of the system˜ (r,X). We define the˜
Σ_{d}^{r}-valued process X= (X^{(1)}, . . . ,X^{(d)})by(X_{k}^{(i)},0≤k≤N˜_{i}) = (X˜_{k}^{(i)},0≤k≤N˜_{i}).

Then(F,c_{F}):=Ψ^{−1}(X)is aF_{d}^{r}-valued branching forest(F,c_{F})with progeny
distributionν.

### 4 The continuous time setting

### 4.1 Proofs of Theorem 1 and Proposition 1.

LetY = (Y^{(1)}, . . . ,Y^{(d)})be the underlying random walk of the compound Poisson

processX, that is the random walk such that there are independent Poisson processes
N^{(i)}, with parameters λi such thatX_{t}^{(i)}=Y^{(i)}(N_{t}^{(i)}) and(N^{(i)},Y^{(}^{j)},i,j∈[d])are
independent. Then from Lemma 1, there is a random time s∈Z^{d}+, such that almost
surely, for all j∈U_{s},x_{j}+∑^{d}_{i=1}Y^{i,}^{j}(s_{i}) =0. Moreover, if s^{0}is any time satisfying this
property, then s^{0}≥s. Fori∈[d]\Us, the latter equality implies thatY^{i,j}(∞)<∞.

SinceY^{i,}^{j} is a renewal process, it is possible only ifY^{i,}^{j}≡0, a.s., so that we can
write: almost surely,

x_{j}+

### ∑

i,i∈U_{s}

Y^{i,}^{j}(s_{i}) =0, for all j∈U_{s}.

Then the first part of the Theorem follows from the construction of X as a time
change of Y. More formally, the coordinates of T_{x} are given by Tx^{(i)} =inf{t :
N^{(i)}(t) =s_{i}}, so that in particular,s_{i}=N^{(i)}(T_{x}^{(i)}).

Additivity property ofT_{x}is a consequence of Lemma 1 and time change. From
this lemma, we can deduce that for all x,y∈Z^{d}+, if s is the smallest solution of
(x+y,Y), then conditionally to s_{i}<∞, for alli∈[d], the smallest solution s_{1}=
(s_{1,1}, . . . ,s_{1,d})of(x,Y), and satisfies s_{1}≤s ands−s_{1}is the smallest solution of the
system(y,Y˜), where ˜Y_{k}^{(i)}=Y_{s}^{(i)}

1,i+k−Y_{s}^{(i)}_{1,i},k≥0. Moreover, ˜Y= (Y˜^{(i)},i∈[d])has the
same law asY and is independent of(Y_{k}^{(i)},0≤k≤s1,i). Using the time change, we
obtain,

L_{x+y}^{(d)}=L_{x}+L˜_{y},

whereL_{x} has the law ofT_{x} conditionally onT_{x}^{(i)}<∞, for alli∈[d]and ˜L_{y}is an
independent copy ofL_{y}. Then identity (4) follows.

The law ofT_{x}onR^{d}+follows from time change and the same result in the discrete
time case obtained in [5], see Theorem 3.4 therein.

Proposition 1 is a direct consequence of part 1 of Theorem 1 and the time change.

### 4.2 Multitype forests with edge lengths

Ad type forest with edge lengths is an element(f,c_{f}, `_{f}), where(f,c_{f})∈Fd and

`_{f} is some application `_{f}:v(f)→(0,∞). Foru∈v(f), the quantity `_{f}(u)will be
called the life time of u. It corresponds to the length of an edge incident to u in
(f,c_{f}, `_{f}) whose color is this ofu. This edge is a segment which is closed at the
extremity corresponding touand open at the other extremity. Ifu is not a leaf of

(f,c_{f})then`_{f}(u)corresponds to the length of the edge betweenuand its children in
the continuous forest(f,c_{f}, `_{f}). To each tree of(f,c_{f})corresponds a tree of(f,c_{f}, `_{f})
which is considered as a continuous metric space, the distance being given by the
Lebesgue measure along the branches. To each forest(f,cf, `_{f})we associate a time
scale such that a vertexu is born at timet if the distance betweenu and the root
of its tree in(f,c_{f}, `_{f}) ist. Timet is called the birth time ofu in(f,c_{f}, `_{f})and it
is denoted byb_{f}(u). The death time ofu in(f,c_{f}, `_{f})is then b_{f}(u) +`_{f}(u). If s∈
[b_{f}(u),b_{f}(u) +`_{f}(u))then we say thatuis alive at timesin the forest(f,c_{f}, `_{f}). We
denote by h_{f}the smallest time when no individual is alive in(f,c_{f}, `_{f}).

The set ofd type forests with edge lengths will be denoted byF_{d}. The subset of
F_{d}of elements(f,c_{f}, `_{f})such that(f,c_{f})∈F_{d}^{r}will be denoted byF_{d}^{r}. Elements ofF_{d}
will be represented as in Figure 1.

To each forest(f,c_{f}, `_{f})∈F_{d}^{r}, we associate the multidimensional the step func-
tions,(z^{(i)}(t),t≥0)that are defined as follows:

z^{(i)}(t) =Card{u∈v(f):c_{f}(u) =i,uis alive at timetin(f,c_{f}, `_{f}).} (23)
Then the process(z^{i,}^{j}(t),t≥0)introduced in Definition 1 is formally defined by
z^{i,}^{j}(0) =0 ifi6=j,z^{i,i}(0) =r_{i}, and fort>0,

z^{i,}^{j}(t) =r_{i}1_{i=j}+

### ∑

b_{f}(u)+`_{f}(u)<t

1_{c}

f(u)=i(p_{j}(u)−1_{i=}_{j}). (24)
It readily follows from these definitions that

z^{(}^{j)}(t) =

d

### ∑

i=1

z^{i,}_{t}^{j}, t≥0.

We now define the discretisation of forests of F_{d}, with some span δ >0. Let
(f,cf, `_{f})∈F_{d}, then on each tree of(f,cf, `_{f})∈F_{d}, we place new vertices at distance
nδ,n∈Z+of the root along all the branches. A vertex which is placed along an
edge with colorihas also colori. Then we define a forest inFdas follows. A new
vertexvis the child of a new vertexuif and only if both vertices belong to the same
branch of(f,c_{f}, `_{f}), and there isn≥0 such thatuandvare respectively at distance
nδand(n+1)δ from the root. This transformation defines an application which we
will denote by

D_{δ} :F_{d}→Fd

(f,cf, `_{f})7→D_{δ}(f,cf, `_{f}).

Note that with this definition, the roots of the three forests (f,c_{f}), (f,c_{f}, `_{f}) and
D_{δ}(f,c_{f}, `_{f})are the same and more generally, a vertex ofD_{δ}(f,c_{f}, `_{f})corresponds
to a vertexuof(f,c_{f}, `_{f})if and only ifuis at a distance equal tonδ from the root,
for some integern≥0. It is also equivalent to the fact thatuis at generationnin