The ergodic Mean Field Game system for a type of state constraint condition
1 Introduction
The object of this paper is to establish well-posedness (existence and uniqueness) results for a type of state constraint ergodic Mean Field Game (MFG) system
(1.1) |
supplemented with the state constraint-type infinite Dirichlet boundary condition
(1.2) |
where is the distance to the boundary. Here is an open bounded subset of , is the Hamiltonian associated with the cost function of an individual agent, is the ergodic constant, is the distribution of the agents, and is the interaction term. The Hamilton-Jacobi-Bellman (HJB) equation is understood in the viscosity sense and the Kolmogorov-Fokker-Planck (KFP) equation, in the distributional sense.
The MFG with the boundary condition can be interpreted as a state constraint-type problem. Indeed, the infinite boundary condition prevents the underlying stochastic trajectories from reaching the boundary, forcing them to stay in the domain.
The theory of MFGs was introduced by Lasry and Lions [8] and, in a particular setting, by Caines, Huang, and Malhamé [4], to describe the interactions of a large number of small and indistinguishable rational agents. In the absence of common noise, the behavior of the agents leads to a forward-backward coupled system of PDEs, consisting of a backward HJB equation describing the individual agent’s value function, and a forward KFP equation for the distribution of the law (density) of the population.
The forward-backward system with periodic boundary conditions and either local or non-local coupling, as well its ergodic stationary counterpart, was first studied in [8]. Summaries of results may also be found in Cardaliguet [2], Lions [9], and Gomes, Pimentel, and Voskanyan [3]. Fewer results exist, however, in the case of either Dirichlet, state constraint or Neumann boundary conditions.
We next state the main result of this paper for superlinear power-like Hamiltonians, that is,
(1.3) |
and suitable assumptions on the coupling (see , and in Section 2.2). We emphasize that the particular form of the Hamiltonian is by no means essential to the analysis that follows. It simply provides a sufficiently general model problem that results in the necessary asymptotics of and near . In particular, for , Hamiltonians for which
(1.4) |
locally uniformly in as are permissible. We state the result below, deferring the precise meaning of a solution to the system until Section 3.
Theorem.
Let and assume either or .
Then, for all , there exists a solution to the system
(1.5) |
Moreover, if satisfies , then the solution is unique.
As will be explained below, the conditions and describe non-local and local couplings respectively, while is the usual monotonicity condition.
1.1 Background
Heuristically, HJB equations with convex (in the momentum) Hamiltonian are associated with the stochastic control problem governed by the dynamics
where is a non-anticipating process. In feedback form, the optimal policy is .
In settings in which the trajectories of the agents reach the boundary but do not leave the domain or, as is the case we consider here, do not reach the boundary at all, the solutions of the HJB equation are referred to as state constraint solutions.
If the drift is bounded, then for all , . It follows that for trajectories to remain inside , the drift must become unbounded near the boundary, pushing the agents back into the domain. For Hamiltonians of the form (1.3), or more generally , state constraint solutions exist when the equation is paired with an infinite Neumann condition (reflection cost) or infinite Dirichlet condition (exit cost), the “correct” choice of boundary condition depending on whether the Hamiltonian is sub- or super-quadratic. Indeed, when , solutions are bounded but the normal component of the drift blows up at the boundary. In the sub-quadratic case, the solution itself also blows up.
In the sub-quadratic case, the trajectories never reach the boundary. Hence, the population density is “almost zero” near . As the behavior of at the boundary is coupled with the blowup of on , no boundary condition is required on in (1.5).
A type of MFG state-constraint problem has been studied by Porretta and Ricciardi in [10]. The authors impose structural assumptions on their Hamiltonian so that, for all choices of the control, an agent governed by these dynamics does not exit the domain . In this instance, no explicit boundary conditions on the value function are necessary to achieve well posedness. However, the assumptions of [10] do not permit coercive Hamiltonians, and, in particular, do not apply to the ones considered in this paper.
1.2 Infinite Dirichlet boundary conditions
In the context of HJB equations, infinite boundary conditions with power-like Hamiltonians were studied by Lasry and Lions in [7], who considered the HJB equation
(1.6) |
with and , as well as the ergodic problem
both coupled with the infinite Dirichlet boundary condition .
It was shown in [7] that the boundary value problem
(1.7) |
has a unique viscosity solution , where uniqueness for is understood to be modulo an additive constant. Such a solution has unbounded drift in the direction of the boundary and the agents remain in the domain.
Due to the coupled nature of the MFG system, the existence and well posedness of the corresponding KFP equation depends in an essential way on the asymptotics of and near the boundary.
In general, if , the distributional solution of
(1.8) |
need not be unique unless a boundary condition is specified.
On the other hand, if
(1.9) |
where and is the outward unit normal to the boundary at the point closest to , Huang, Ji, Liu and Yi showed in [5] that solutions are unique, despite the absence of boundary conditions.
To show for and apply this result, we need to make precise the asymptotics of and near the boundary.
In [7], the authors proved that if is a solution of , the asymptotics are precisely of this type. Namely, there exists a constant such that
In this paper, we refine the result and show that the rate of convergence of the above limit is controlled by the norm of . This becomes important when proving stability results related to .
1.3 The methodology
As usual, the existence of a solution to the MFG system is proven via a fixed point argument. To apply such an argument, it is crucial to obtain bounds on up to . Toward that end, for , we define the subdomain by
As a first step, we show that if satisfies with constant , then there exists , , and such that any solution of satisfies
(1.10) |
This estimate is needed in both the local and non-local cases.
The space in which the fixed point argument is carried out differs in the non-local and local coupling settings. In the former, the fixed point is obtained in the space
(1.11) |
where is as in and, here, depends only on . The map formed by composing the solution maps of and ) satisfies the conditions of Schaefer’s fixed point theorem. In particular, the continuity of is straightforward due to the regularizing effect of the coupling.
By contrast, the continuity of the solution map is far from obvious in the local case, where for a continuous and bounded function . Convergence of a sequence in does not yield local uniform convergence of as it does in the non-local case. Thus the fixed point argument must be performed in a different space.
To deal with this issue, we introduce, for , the approximating coupled ergodic system
(1.12) |
where and is a suitable extension of to all of satisfying
We note that (1.12) is not the standard MFG system with Neumann boundary conditions, in which the HJB and KFP equations are set in the same domain and both have Neumann boundary conditions. Instead, the HJB equation is set in the entire domain , allowing us to to take advantage of the known asymptotics of and near the boundary. On the other hand, the Neumann conditions on the KFP equation allow us to exploit in regularity of up to .
As we discuss below, for , the KFP equation
has a a unique (modulo a multiplicative constant) distributional solution, which is positive and Hölder continuous up to the boundary with Hölder constant depending on the norm of the drift. If is the solution of a HJB equation like , is bounded on and this result applies to the KFP equation in . Moreover, as shown in [7], the local bounds on the solutions of the HJB equation are uniform in the norm of , which is independent of . Therefore, as we show below, it is possible to carry out a fixed point argument in .
We are then able to pass from the solution of the approximating system to a solution of the original system on by the stability of the HJB equation and the local uniform bounds on , which in turn follow from local uniform bounds on .
Lastly, under the usual monotonicity assumption we establish uniqueness in both the local and non-local case. The key observation in the argument is that, for solutions of (1.5), decays near the boundary as in (1.10).
1.4 Organization of the paper
The paper is organized as follows. The assumptions on the domain and the coupling are stated in Section 2. Section 3 introduces the notions of weak solutions of the KFP and HJB equations and proves (local) regularity and stability results. Section 4 treats the non-local coupling case. In Section 5, we show the approximating problem (1.12) has a solution and pass to the limit to obtain a solution to on the entire domain. Section 6 establishes the uniqueness of the system and quantifies the sense in which vanishes at the boundary. The Appendix contains two technical lemmata used in Sections 3 and 5.
2 Assumptions and definitions
2.1 The domain
Throughout this paper it is assumed that
In particular, the domain satisfies the uniform interior ball condition. Namely, there exists a such that for every , the ball is contained in .
Recall the definition of the subdomains
Due to the -regularity of , there exists such that and for all there exists a unique point such that . Moreover, on ,
Lastly, we define to be a extension of which is equal to on . We additionally require that in and in for some positive constant .
2.2 The coupling
Our analysis permits a coupling which is either non-local, on the one hand, or local, continuous, and bounded on the other. Namely, we consider couplings satisfying one of the following:
-
(F1)
The map sends bounded sets in to bounded sets in , and is continuous from into .
-
(F2)
for a continuous, bounded function.
A coupling satisfying assumption has an -bound depending only on . A coupling satisfying inherits regularity from the regularity of and is bounded by .
When proving uniqueness we will require the additional monotonicity assumption
-
(F3)
, with equality only if a.e.
2.3 The space of measures for the non-local setting
In the introduction, we defined a space which quantifies the boundary behavior of solutions to KFP equations with an unbounded drift term. We repeat the definition here for completeness.
Definition 2.1.
For , define a norm by
and recall that is the Banach space induced by this norm, as in .
2.4 The extension of measures defined on subdomains
In the local coupling setting discussed in Section 5 we will consider measures defined on the subdomain . Since is defined on , it will be necessary to define a suitable extension of measures on to that preserves their Hölder regularity.
For and we define by
(2.1) |
It is straightforward to check that on and that with the same Hölder modulus as .
In the sections that follow, we abuse notation slightly and define the coupling by
3 Preliminaries
In this section, we recall some existence and regularity results for the HJB equation and the KFP equation. At the end we prove stability results that will be used in Section 5.
3.1 The Kolmogorov Fokker-Planck equation
Throughout this paper we will need to consider the KFP equation in subdomains of . To that end, we study the following KFP boundary value problem for a general open bounded domain and .
(3.1) |
Later we will apply these results when and .
Definition 3.1.
Given , we say that is a Neumann weak solution of if is a positive probability measure such that, for all ,
The next lemma gathers existence and uniqueness results for Neumann weak solutions of as well as estimates.
Lemma 3.1.
For , admits a unique Neumann weak solution . In addition, for all and, for compact sets , is bounded uniformly by a constant that depends only on and .
Proof.
If the drift in the KFP equation blows-up at the boundary, it is necessary to modify the notion of weak solution as follows.
Definition 3.2.
Given and , we say is a weak solution of
(3.4) |
if is a non-negative function such that, for all ,
Moreover, is a proper weak solution if .
Remark.
The class of test functions in Definition 3.2 can be extended to functions that are constant in a neighborhood of .
The following lemma shows that weak solutions of may arise as the limit of Neumann weak solutions. The rest of the section provides conditions under which the limit is a proper weak solution.
Lemma 3.2.
Let be a Neumann weak solution of for velocity fields . Assume that, as , locally uniformly. Then, along subsequences, and is a weak solution of
Proof.
Recalling that is uniformly bounded for each compact , it is possible to extract a subsequence such that converges locally uniformly to a non-negative function . To see that satisfies the desired equation, consider a test function . Since converges uniformly to in the support of , converges uniformly to . As uniformly in the support of , letting in the weak formulation leads to the desired result. ∎
It follows from Fatou’s lemma that the limit in the above lemma is integrable on and . To ensure that is a proper weak solution it is necessary to impose additional structural conditions on the vector fields . In [1], Bogachev and Rökner give conditions on the drifts under which the sequence of weak solutions is uniformly tight, which in turn yields convergence of to . The version of the theorem relevant to our setting appears below.
Lemma 3.3 (Lemma 1.1 in [1]).
Let by a sequence of nested domains and the corresponding sequence of Neumann weak solutions to on . Suppose that and that, for every , there exists such that
If, in addition, there exists such that, for some , , has Lebesgue measure zero,
(3.5) |
and
(3.6) |
then the sequence is uniformly tight.
A function satisfying the above conditions is referred to as a Lyapanov function. The connection between Lyapanov functions and existence and uniqueness of weak solutions of has been extensively studied in [1], as well as in [5].
It follows from the Lemma 3.3 that, if there exists a satisfying , and
(3.7) |
then, setting , we obtain a sequence of measures that converge to a proper weak solution of
(3.8) |
It is proven in [5] that such a solution is unique.
In the present setting, these results will be applied by considering satisfying, for some and ,
(3.9) |
and , which satisfies and . This is stated precisely in the next result, the proof of which appears in the Appendix.
Lemma 3.4.
Given satisfying with , there exists a unique proper weak solution of
and, for every , there exists a , such that
Remark.
The bound on makes precise the intuition that “approaches 0” near the boundary .
It is proven in [7] that, for solutions of the HJB equation in , satisfies precisely for . This is discussed further in the next section.
3.2 The Hamilton-Jacobi-Bellman equation
In this section, we fix and and consider the stationary HJB equation with infinite Dirichlet conditions
(3.10) |
The estimates detailed here will be used to prove the HJB stability results in Theorem 3.8.
We begin by stating the definition of solutions for concreteness.
Definition 3.3.
For and , is an explosive solution of if is a viscosity solution in and
The existence and uniqueness of solutions to such HJB equations was proven in [7], along with several local estimates. These results are collected in the next two theorems. The second theorem is a straightforward consequence of the bounds established in Theorem IV.I of [7], with a slight modification to fit our ergodic framework.
Theorem 3.5.
(Theorem VI.I in [7])) Let and . The equation admits an explosive solution for all .
Theorem 3.6.
Let , and be an explosive solution of with , for some fixed . There exist positive constants , depending only on and , such that,
-
(i)
,
-
(ii)
, and
-
(iii)
.
In addition, for any compact subsets of , there exists a constant such that
-
(iv)
.
If , the same estimates hold but must be replaced by
-
(iii)’
.
Sketch of Proof of Theorem 3.6.
The first result follows from the construction of in Theorem VI.I of [7] which shows that arises as the local uniform limit of as , where is the unique viscosity solution of
If , for arbitrary , has as sub- and super-solutions , where and is a function of . Similarly, for , has as sub- and super-solutions , where is a function of . Sending yields the desired bound on .
The second result is proven in Theorem IV.I of [7] and is an immediate consequence of as is fixed. The last interior estimate follows from a bootstrap argument.
∎
In order to study the solution of the KFP equation near the boundary, it will be necessary to know the precise asymptotics of . In [7], Lasry and Lions, and later Porretta and Véron in [11], established the following results.
Theorem 3.7.
Remark.
Lemma 7.1 in the Appendix is a slightly stronger version of this theorem, where the convergence is shown to be uniform in . This stronger version will be necessary in Section 5.
Lastly, we provide a stability result particular to the types of couplings we are studying.
Theorem 3.8.
Assume and fix . Let be a sequence of probability measures on which converge in to , and be the unique explosive solution of
subject to the normalization condition . Then there exists , such that and locally uniformly as . Moreover, is the unique explosive solution of
(3.11) |
Proof.
It follows from that and are bounded in . Theorem 3.6 yields that is bounded and hence converges along a subsequence to a constant . The sequence is bounded in so, by Arzelà-Ascoli, we can extract a subsequence converging locally uniformly to such that locally uniformly. By pointwise convergence, .
That as follows from the fact that the sequence of equations have a common explosive subsolution. When , one such subsolution is of the form , where , , and . When the corresponding subsolution is .
Lastly, in view of , converges uniformly to . It follows from classic viscosity theory that is a viscosity solution of . As the explosive solution satisfying is unique, the limit is indepedent of the subsequence.
∎
3.3 Definition and Main Result
We finish this section with the definition of a solution to the system and the main existence and uniqueness result stated in the introduction.
Definition 3.4.
A triplet is a solution of if is an explosive solution of
and is a proper weak solution of
We are now able to state the main result of the paper.
Theorem 3.9.
Assume that and either or holds. Then has a solution for all . Moreover, if also holds, then the solution is unique.
4 Fixed point for the non-local case
In this section we will use Schaefer’s fixed point theorem in to prove the existence of a solution to when holds.
Let . Define to be the map that sends measures to , where is any explosive solution of
(4.1) |
It is immediate from Theorem 3.5 that is well defined as explosive solutions are unique up to a constant.
Define to be the map that sends in the image of to the proper weak solution of the associated continuity equation
(4.2) |
In view of Lemma 3.4 and Theorem 3.7, has a unique proper weak solution for in the image of .
Finally define . In the next result, we apply Schaefer’s fixed point theorem to , thereby obtaining a solution of the MFG system .
Theorem 4.1.
For satisfying and , has a fixed point.
Proof.
Recall that to apply Schaefer’s fixed point theorem, we need to show that is continuous, maps bounded sets to precompact sets, and if is the set defined by
(4.3) |
then is bounded.
We start by showing that is continuous. Consider a sequence that converges to in . To simplify the notation, define , , and . We first show that locally uniformly. We then show that the sequence converges in to a measure and prove that .
Fix and let be the unique explosive solution of that corresponds to and satisfies . Note that by the remark following . Since converges to in , the local uniform convergence of to follows from Theorem 3.8.
In view of the local uniform bounds on , Theorem 3.1 implies the sequence of measures are uniformly bounded in for all and, hence, locally uniformly bounded in for . Along subsequences, the measures converge locally uniformly to a measure . Consequently, we can pass to the limit in the weak formulation of and obtain that is a non-negative measure that satisfies the KFP equation with drift . It remains to show that converges to in .
Lemma 3.4 yields that if , then the sequence is bounded in . This implies that the sequence is uniformly tight. Indeed, for some constant , independent of the choice of and ,
It then follows from the bound
that as .
Since convergence in implies convergence in , this also proves that . The uniqueness of then yields the convergence of the full sequence to .
Next we show that maps bounded sets to precompact ones. Indeed let be a bounded sequence in , and consider , , and defined as before. It suffices to show that there is a convergent subsequence of . The sequence is bounded in and is bounded in . Moreover, Theorem 3.6 yields that is locally uniformly bounded. Finally, Lemma 3.1 implies that is uniformly bounded in . Passing to subsequences, the measures converge locally uniformly to a measure . Proceeding as in the continuity argument, we find that the sequence is uniformly tight and .
It remains to check that the set defined above is bounded. To see this, first observe that if , then . Hence is bounded by assumption . Next we apply Theorem 3.6 to find that is bounded on by a constant . Lemma 3.4 then implies that is bounded.
∎
5 Fixed point argument for the local setting
In this section we will show existence of solutions to under assumption by considering the system , introduced in Section 1, which approximates . First, we will use Schaefer’s fixed point theorem to show the system has a solution. Then, using the uniform tightness results of Lemma 3.3 and the local uniform bounds of Theorem 3.6, we will show that solutions of converge locally uniformly to solutions of .
5.1 The approximate problem
We begin by making precise the notion of solution to the approximating system . We then show the existence of a solution using a fixed point theorem argument similar to that used in the non-local setting.
To utilize the asymptotic behavior of the explosive solutions to HJB equations at the boundary of as well as the bounds of Neumann weak solutions to KFP equations on , the KFP equation of is solved in the subdomain and the HJB equation is solved in .
Definition 5.1.
A triplet is a solution of if is an explosive solution of
and is a Neumann weak solution of
When satisfies , existence of a solution to this system follows from Schaefer’s fixed point theorem.
Indeed, let be the map that sends measures to , where is the explosive solution of
which is well defined for all and . It follows from Theorem 3.5 that the system has a solution for every , and is unique.
Let be the map that sends to the Neumann weak solution of
where is the restriction of to the domain , which is also well defined. In view of Theorem 3.5, there is a unique Neumann weak solution . Moreover, is in for all and, by Sobelov embedding, is in for all . Composing the two, we define .
Theorem 5.1.
For satisfying and , has a fixed point.
Proof.
We apply Schaefer’s fixed point theorem as in Theorem 4.1. As we will be working with an HJB equation set in and a KFP equation set in , we will be exploiting that the method for extending measures from to defined in is -norm preserving.
To show the continuity of , we consider a sequence which converges to in , and we start by showing that converges to locally uniformly. To simplify notation, we let , , and .
Let be the unique explosive solution of that corresponds to and satisfies , where is fixed. As the sequence converges to in , converges uniformly to in , and as a result converges uniformly to in , where and are defined as in .
Due to the stability properties of viscosity solutions, to prove continuity of under assumption , it is sufficient to show that if in , then . However, this follows immediately from the continuity of and the equicontinuity of .
Next we show that is continuous. Since is bounded in , is uniformly bounded in and, hence, bounded in for . In view of the compact embedding of in , there is a subsequence of that converges in to some . Moreover, converges weakly to . Consequently, we can pass to the limit in the weak formulation of and obtain that is a positive probability measure that satisfies the KFP equation with drift . The uniqueness of yields convergence of to along the full sequence.
Next, to show that is precompact, we will use the bounds in Theorem 3.6, Lemma 3.1, and the Sobelov embedding theorem.
For and , Theorem 3.6 yields , where depends on and . Note that by assumption , is bounded by a constant depending on .
Lemma 3.1 yields that is bounded by a constant depending on .
Since embeds compactly in for , choosing appropriately large , sends bounded sets of to precompact ones.
It remains to check that if is the set defined by
then is bounded. This follows from Theorem 3.1 as is bounded in .
∎
5.2 Limit of the approximate problem
In this section we prove that in the local setting, the solutions of converge locally uniformly to solutions of . We begin by showing that, along subsequences, has a local uniform limit using the Arzelà-Ascoli Theorem. We then construct a Lyapanov function and use Lemma 3.2 and Lemma 3.3 to show that the measures converge locally uniformly to a proper weak solution of a continuity equation. Lastly we show that is the explosive solution corresponding to .
Theorem 5.2.
Given and satisfying , let , and be a solution of satisfying . Along subsequences, converges to a constant and converges in to .
Proof.
It follows from Theorem 3.6, and the uniform in bounds on , that and the bounds of are bounded uniformly in . The desired convergence along subsequences follows by the Arzelà-Ascoli Theorem. ∎
For now we make no claims about the equation solves. We must first make sense of the limit of the measures .
Theorem 5.3.
Given and satisfying , let be a solution of . Along subsequences, converges locally uniformly to which is a proper weak solution of
where and is the limit function from Theorem 5.2.
Proof.
In view of Lemma 3.2 and Lemma 3.3, it suffices to construct a function satisfying and for .
Consider , where and , which satisfies the desired growth condition at the boundary. The -norm of the coupling term is uniformly bounded in by . By Lemma 7.1, uniformly in as . It follows that the limit at the boundary is likewise uniform in , and is satisfied. The uniform tightness of the measures ensures that and converges to in .
∎
We are now ready to state the equation that solves.
Theorem 5.4.
Let satisfy and be a solution of . Let , and be as constructed in Theorems 5.1 and 5.2. Then is the explosive solution of
Proof.
The proof is very similar to the stability argument in Theorem 5.1, and follows from the local uniform Hölder bounds on . Indeed, consider a sequence contained in a compact set , and let . Then,
(5.1) |
By the uniform convergence of to on , goes to as . The continuity of allows us to pass to the limit in the HJB equation, obtaining that is a viscosity solution of
The argument that blows up at the boundary is the same as in Theorem 3.8. ∎
6 Uniqueness
We are now ready to address the uniqueness claim in Theorem 3.9. Throughout the discussion we take and deal with the case at the end of the section.
Proof of Theorem 3.9.
It only remains to show that uniqueness holds when satisfies . Here we follow the classical Lasry-Lions uniqueness argument. Consider two solutions of . Without loss of generality, we may assume that for a fixed .
Letting , , and , it follows that satisfies the system
where and .
Consider a non-negative and compactly supported function ; the particular choice of will be made later.
Multiplying the first equation by and integrating by parts, we obtain
Similarly, using as a test function in the KFP equation, we obtain
Adding the equations and regrouping gives:
(6.1) | ||||
(6.2) | ||||
The left-hand side is positive by the monotonicity assumption , and and are negative by the convexity of the Hamiltonian. We will show that the remaining terms on the right hand side can be made arbitrarily small for the right choice of .
We are now ready to define . Let be a smooth function that is in a neighborhood of , in a neighborhood of , and constant for . For , let . There exists a constant such that, in ,
(6.3) |
and
Together with the local bounds on and from Theorem 3.6, it follows from that there exists a constant , independent of , for which
(6.4) |
Similarly there exists a constant , independent of , for which
(6.5) | ||||
(6.6) |
We recall from Lemma 3.4 that, for small , is finite. It follows that and can be made arbitrarily small for small enough.
To bound the remaining term, we use that and , obtaining
which can also be made arbitrarily small for small enough.
It follows from the monotonicity of , that . That and follows from the uniqueness of solutions to .
∎
Remark.
To prove uniqueness of solutions to when , should be replaced by an estimate of the form
(6.7) |
where is a constant independent of . As has growth slower than , the rest of the proof then proceeds as in the case.
7 Appendix
Lemma 7.1.
Let and consider the unique solution of
(7.1) |
Let . Then, uniformly in ,
It will be enough to show uniform convergence of as .
We prove this by following the proof of Theorem 2.3 in [11] and tracking how the convergence depends on .
In the proof that follows, we argue first when , and discuss the case at the end of the proof. The same arguments also hold for Hamiltonians satisfying locally uniformly in as .
Proof of Lemma 7.1.
Since has a uniform boundary, by Theorem 3.7 there exists a , depending on , such that for every , the ball is contained in , and, for ,
(7.2) |
where .
We begin by fixing and a system of coordinates centered at whose -axis is the inner normal direction. Although we have fixed an , any bounds and rates that follow will not depend on .
Let and consider the domain
Applying the change of variable , the domain converges to the half space , where is the component of the vector in the direction. Under this change of variable we have the bounds
(7.3) |
It is now possible to introduce, for , the blow up function
with domain , which, in view of , is uniformly bounded in and .
Straightforward computations show that describes the blow-up of near the boundary. Indeed, for ,
In , solves, in the viscosity sense,
(7.4) |
Moreover, satisfies the estimate
where comes from the locally uniform bound on from Theorem 3.6.
Consider a family of with and measures such that is uniformly bounded. This is the case, for example, if or are satisfied and the measures are uniformly bounded in . It follows from elliptic regularity that has a convergent subsequence converging in to defined in the half-plane .
Since and uniformly, is a viscosity solution of
(7.5) |
In addition, satisfies the boundary conditions
The boundary conditions follow from
(7.6) |
and the estimates in . As shown in Theorem 4.1 of [11], the equation paired with boundary conditions has a unique positive solution in the half-plane, . From , is indeed positive. Thus converges locally uniformly to , and converges uniformly in , as .
When , rescaling as before does not yield an equation of the type . To circumvent this, we consider a function of the form , which is uniformly bounded in and has a limiting equation of the desired form.
For the case , consider a coordinate system centered at , denoted by , with the -axis as the inner normal direction. By the inner sphere property, there is such that for every , the ball is contained in . Under this new coordinate system define
Note that we changed the definition of here.
Restricting to , the function
is defined on the domain . As before, converges to the half space , where is the component of the vector in the direction. Under this change of variable we have the bounds
In , satisfies, in the viscosity sense,
By Theorem II.3 of [7], is bounded by a constant which is uniform in . From the bounds on it follows that is bounded locally uniformly. From standard elliptic theory, is relatively compact in . Thus, along subsequences converges in to a function , defined in the upper-half plane, which is a viscosity solution of
Moreover, for constant as defined above,
Thus we have the boundary condition
Solutions of the system
are of the form for a constant , which follows from the change of variable . Thus converges locally uniformly to , and converges uniformly in , as .
∎
We now prove Lemma 3.4 from Section 3.1.
Lemma 3.4.
Let satisfy with . Then there exists a unique proper weak solution of
(7.7) |
and, for every , there exists a , such that
(7.8) |
Proof.
The existence of a proper weak solution was proven in Section 3.1. To prove (7.8), we mimick the proof of Lemma 1.1 in [1].
Let for . In the neighborhood of ,
Since the last factor approaches as , in a neighborhood of , we have
(7.9) |
Let be such that, for ,
and define .
Note that since is a probability measure on , is bounded by the norm of on .
We claim that, for all ,
(7.10) |
Since is independent of , it would then follow that
and the growth of in completes the proof of the lemma.
To prove , fix , , and , such that . Consider a nondecreasing cut-off function such that , for , and for . Since is constant in a neighborhood of the boundary , it follows that it is a permissible test function in .
The sign of yields,
The last integrand is zero outside , equals on and, is non-positive on . Consequently,
Letting yields
Since on , and , it follows that
∎
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