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Bounded kernels give a local positive measure-valued solution

Statement

For the bounded Lipschitz kernels and daughter measures of Continuous-size coagulation-fragmentation weak model, every positive initial measure μ0∈Mw(E) has a unique positive solution μ∈C([0,T0];Mw(E)) to the weak model for some T0>0.

Facts & Assumptions

Given: The bounded-kernel weak equation, a positive initial measure, and the weighted total-variation space.

[F1]

Continuous-size coagulation-fragmentation weak model: K,β,Bx define the weak vector field C(μ,μ)+Fμ and preserve positivity of the gain measures.

[F2]

The bounded-kernel continuous coagulation-fragmentation field is locally Lipschitz: that vector field is Lipschitz on every bounded ball of Mw(E).

[F3]

The weighted total-variation measure space is complete: Mw(E) is complete in ∥⋅∥w.

[F4]

Bounded coagulation is bilinear and bounded in weighted total variation: the coagulation bilinear operator is bounded on weighted total variation.

[F5]

Mass-normalized fragmentation is bounded in weighted total variation: the fragmentation operator is bounded on weighted total variation.

Proof

1.1givenF1F2F4F5algebra

For a positive path ν in a ball of radius R, define aν(t,x)=∫EK(x,y)νt(dy)+β(x) and the positive gain GC(νt)=12∬K(x,y)δx+yνt(dx)νt(dy), GF(νt)=∫Eβ(x)Bx νt(dx), and G=GC+GF. Then 0≤aν≤K∗R+β∗. Since w(x+y)≤2w(x)w(y), ∥GC(μ)∥w≤K∗∥μ∥w2; bilinearity gives its local Lipschitz bound. Also ∥GF(μ)∥w≤β∗(D+1)∥μ∥w by the daughter estimate in [F5]. Thus G is bounded and Lipschitz on the ball, and aν−aη is bounded by K∗∥ν−η∥w.

2.1F2F3F4F5step 1.1choose

On C([0,T];Mw(E)) define Φ(ν)t=e−∫0taν(s,⋅) dsμ0+∫0te−∫staν(r,⋅) drG(νs) ds. The loss rate is continuous in time in L∞(E), since ∥aν(t,⋅)−aν(s,⋅)∥∞≤K∗∥νt−νs∥w; the gain path is continuous in Mw(E) by the bounded-operator estimates in [F4]–[F5]. For bounded b, multiplication Mbσ=bσ satisfies ∥Mb∥≤∥b∥∞, so the survival multipliers are continuous in operator norm and Φν is a continuous path. For positive ν it is positive. On the closed positive path ball of radius R>2∥μ0∥w, the gain bound gives ∥Φν∥CMw≤∥μ0∥w+TCR≤R for sufficiently small T. The bounds ∣aν−aη∣≤K∗∥ν−η∥w and ∣e−u−e−v∣≤∣u−v∣ give ∥Φν−Φη∥CMw≤(TLR+TK∗∥μ0∥w+T2K∗CR)∥ν−η∥CMw. Choose T so this coefficient is below 1.

3.1F3step 2.1algebra

The closed positive path ball is complete: a Cauchy sequence converges uniformly by [F3], its uniform limit is continuous, and the positive cone is closed because ν−(E)≤∥ν−νj∥TV when νj≥0. It is nonempty because it contains the constant path νt0=μ0. If q<1 is the contraction coefficient in step 2.1, iteration νj+1=Φ(νj) from ν0 satisfies ∥νj+1−νj∥≤qj∥ν1−ν0∥. For m>n, ∥νm−νn∥≤∥ν1−ν0∥∑j=nm−1qj≤qn∥ν1−ν0∥/(1−q)→0, so completeness gives a limit. The contraction bound makes Φ continuous, hence the limit is fixed; if two fixed points existed, their distance would be at most q times itself, hence zero. For a fixed point, S(t,s):=Me−∫staν(r,⋅)dr has operator-norm derivative ∂tS(t,s)=−Maν(t,⋅)S(t,s), since the scalar exponential difference quotients converge uniformly in x. Splitting the difference quotient of the source integral at s=t gives its endpoint term G(νt) and its integral term −Maν(t,⋅)∫0tS(t,s)G(νs)ds; thus the fixed point solves ν˙=G(ν)−aνν. Conversely, for any positive solution ζ, the inverse multiplier A(t)=Me∫0taζ(s,⋅)ds is operator-norm differentiable with A′=MaζA. The product difference quotient gives (Aζ)′=AG(ζ); integrating this continuous derivative by telescoping partitions and multiplying by A(t)−1 recovers the same mild formula. Continuity at 0 puts any competing solution in this ball on a sufficiently short interval, where fixed-point uniqueness makes it equal to the constructed solution.

4.1givenF1step 3.1algebra∎

The derivative established in step 3.1 is μ˙t=G(μt)−aμ(t,⋅)μt. Symmetry of K combines the two coagulation loss marginals into −∫K(x,y)δx μt(dx)μt(dy); the fragmentation loss is −∫β(x)δx μt(dx). Hence this is precisely the weak equation in [F1], proving the claim.

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