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Regularized continuity equations are represented by characteristic flows

Statement

Assume AC. Let (μtε,vtε) be the Gaussian-regularized solution from the preceding lemma on [0,T]×Rd, and write μtε=ptε(x)dx. There is a unique maximal local flow Xtε(x) solving X˙tε(x)=vtε(Xtε(x)), X0ε(x)=x. For μ0ε-almost every x the path exists on all of [0,T], the map from x to its path is Borel on this full-measure domain, and for every t∈[0,T], μtε=(Xtε)#μ0ε.

Statement references

Facts & Assumptions

Given: AC, the positive smooth densities ptε, the locally time-integrably Lipschitz vector field vtε, its distributional continuity equation, and finite action.

[F1]

The Gaussian-regularized pair has positive spatially smooth density, solves the continuity equation, and has finite action. Gaussian regularization preserves finite-action continuity equations

[F2]

A Borel field with integrable local magnitude and Lipschitz bounds has a unique maximal local flow; its time maps are diffeomorphisms between their open domains and images, and an interior maximal endpoint requires escape from every compact set. Local flows for time-measurable fields with integrable local bounds

[F3]

A finite Borel probability on a Polish space is inner regular; on a Euclidean open set, compactly supported continuous functions are uniformly approximated by smooth compactly supported functions by convolving their zero extensions with a unit-mass bump of sufficiently small support. Assuming countable choice, Borel probability measures on Polish spaces are inner regular Euclidean spaces admit a smooth compactly supported unit-mass bump The mollifier family generated by a unit-mass smooth bump Convolution with a mollifier is smooth, and derivatives pass under the integral sign

[F4]

Tonelli and Fubini apply to the nonnegative action and integrable first-derivative terms; Holder bounds first moments by the square root of finite second action. Tonelli's theorem for nonnegative measurable functions on a sigma-finite product Fubini's theorem for L^1 functions on a sigma-finite product Holder's inequality for integrals, including the endpoint cases

[F5]

AC supplies Countable Choice, so every Borel probability on a Polish space is inner regular; a nonzero finite Borel measure inherits this by normalization. An open E⊊Rd is Polish: dE(x,y)=∣x−y∣+∣dist⁡(x,Ec)−1−dist⁡(y,Ec)−1∣ is a complete compatible metric, since a dE-Cauchy sequence has a Euclidean limit and bounded reciprocal distance prevents that limit from lying on Ec; the case E=Rd uses its Euclidean metric. The Axiom of Choice AC implies DC implies countable choice The Axiom of Countable Choice (ACω) Assuming countable choice, Borel probability measures on Polish spaces are inner regular Polish spaces are separable completely metrizable spaces

[F6]

Dominated convergence applies to sequences bounded by an integrable function on either finite measure. Dominated convergence

[F7]

Monotone convergence passes increasing nonnegative truncations through the measures and time integral. Monotone convergence for the integral

Proof

1.1F1F2given

Apply [F2] to vε and denote by Dt the open set of initial points whose trajectories exist from time 0 through t, and by Et=Xtε(Dt) its open image. Fix t∈(0,T] and f∈Cc∞(Et). For 0≤r≤t and x∈Dr,t, the set of states whose trajectories exist from r to t, define ψ(r,x)=f(Xε(t;r,x)); extend it by zero outside Dr,t. Since supp⁡f is compactly contained in Et, its backward images form a compact subset of the flow domain. Thus ψ has compact spatial support uniformly in r, is continuously differentiable in x, and is absolutely continuous in r locally. The start-time derivative from [F2] and the flow identity give ∂rψ=∇f(X(t;r,x))⋅[−DxX(t;r,x)vrε(x)]=−vrε(x)⋅∇xψ almost everywhere.

2.1F1F3F5F6step 1.1

For this fixed t define the restricted finite pushforward νt on Et by νt(B)=μ0ε({x∈Dt:Xtε(x)∈B}) for Borel B⊆Et. The set is Borel because Xtε is continuous on the open domain Dt; preimages preserve disjoint unions, so νt is a finite Borel measure of mass μ0ε(Dt). The weak continuity-equation identity extends from smooth compact tests to compactly supported tests that are C1 in x and absolutely continuous in r with locally integrable time derivative: multiply by a time cutoff, convolve in time and space on a fixed compact neighborhood, and pass to the limit. The terms converge because pε is locally bounded, pεvε is locally integrable in time and space by finite action, and the test and its spatial gradient converge uniformly while its time derivative converges in L1. Apply this extension to η(r)ψ(r,x) from step 1.1 for every smooth compactly supported time cutoff η. The transport equation leaves ∫η′(r)F(r)dr=0, so F(r)=∫ψ(r,x)dμrε(x) is constant on (0,t). Continuity of the flow and of μrε extends the identity to r=0,t, giving ∫f(y)dμtε(y)=∫f(Xtε(x))dμ0ε(x) for every f∈Cc∞(Et). Uniform mollification extends equality to every f∈Cc(Et); both measures are finite, so uniform limits pass through their integrals. For a compact K⊂Et, choose n sufficiently large that the closed 1/n-neighborhood of K is compactly contained in Et and set fn(x)=max⁡{0,1−ndist⁡(x,K)}. Then fn∈Cc(Et) and fn↓1K, so [F6] gives νt(K)=μtε(K). By [F5], both finite Borel measures on the Polish space Et are inner regular; their agreement on compact sets therefore proves νt=μtε∣Et.

3.1F1F2F4F7step 2.1

For every r∈(0,T], step 2.1 gives equality of the restricted finite measures on Er. Applying it to y↦min⁡{N,∣vrε(y)∣2} and letting N↑∞ by [F7] yields ∫Dr∣vrε(Xrε(x))∣2dμ0ε(x)=∫Er∣vrε(y)∣2dμrε(y)≤∫∣vrε(y)∣2dμrε(y). Let D={(r,x):x∈Dr}. This domain is relatively open in [0,T]×Rd and (r,x)↦Xrε(x) is continuous on it: cover any compact trajectory segment through (r,x) by finitely many local flow neighborhoods from [F2] and patch their continuous dependence on the initial point; time continuity follows from the integral equation. Thus the integrand is Borel; extend it by zero off D. Tonelli [F4] then gives ∫ ⁣∫0min⁡{T,τ(x)}∣vrε(Xrε(x))∣2dr dμ0ε(x)≤∫0T ⁣∫∣vrε(y)∣2dμrε(y)dr<∞. Thus for μ0ε-almost every x the path has finite squared speed integral up to its maximal endpoint. Holder then makes its total path length finite. Such a path is Cauchy at any finite endpoint; it cannot escape every compact set, contradicting [F2] if an endpoint lies in (0,T). At T it has a finite limit and extends continuously to T. Thus μ0ε(DT)=1.

4.1F2F3step 2.1step 3.1∎

For each t, step 2.1 identifies μtε∣Et with νt=(Xtε)#(μ0ε∣Dt), where this restricted pushforward is the finite measure defined in step 2.1. Since DT⊆Dt and μ0ε(DT)=1 by step 3.1, νt(Et)=μ0ε(Dt)=1. Hence μtε(Et)=1, and the equality of restricted measures extends to all Borel subsets of Rd. Because Dt is open and Xtε is continuous there, extend Xtε to all of Rd by setting it to zero off Dt; this is Borel and its pushforward is νt since μ0ε(Dt)=1. Thus μtε=(Xtε)#μ0ε. This proves the claim for every t, with the unique flow given by [F2].

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