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Interacting particle mean field and vortex blob error — Examples

1 · Prerequisites

2 · Summary

The examples make the model and error assumptions concrete. In A globally Lipschitz alignment model with exact mean trajectory, the kernel K(x,y)=a(y−x) has two-variable Lipschitz constant a. The particle mean is constant; for a>0, every particle approaches it by an explicit exponential trajectory, while for a=0 every particle is stationary, illustrating the exact empirical weak equation and the general Dobrushin stability convention.

A dimension-dependent lower bound for empirical W1 error uses a uniform law on the vertices of a high-dimensional cube. Counting unsampled vertices gives a deterministic lower bound on empirical W1 error and rules out the stated uniform dimension-free empirical rate. A mixed-sign vorticity is not a probability for W1 gives a nonzero signed measure of total mass zero, explaining why probability W1 cannot replace the signed discrepancies defined on the main page.

Softened Newtonian particles do not specify the physical collision force compares singular Newtonian relative acceleration with a smooth softened field. Smoothness at a collision changes the force model; it supplies no collision law for the singular system.

Same-sign smooth vortex density and probability blob error budget specializes to a smooth nonnegative unit-mass vorticity and distinct equal-weight initial particles. Under its Countable Choice, common smooth force-residual, and RK4 tube assumptions, including numerical grid states, admitted stages from both exact and numerical starts, and defined one-step maps at every grid step, its probability coupling estimate separates initial empirical error, blob regularization, Simpson force quadrature, and fourth-order time error. The initial coupling need only approach the infimum. The conclusion remains conditional at fixed blob width and makes no uniform singular-limit claim.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

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Softened Newtonian particles do not specify the physical collision force

Example

For two Newtonian point masses in R3 with positive constants absorbed into c>0, the unsoftened relative acceleration is F(r)=−c r/∣r∣3 for r≠0, where ∣⋅∣ is Euclidean. A softened model uses Fε(r)=−cr(∣r∣2+ε2)3/2,ε>0. The softened field is smooth at a collision, but it defines a different dynamical model.

Facts & Assumptions

Given: c>0, ε>0, and the two displayed force laws.

Verification

Given: The unsoftened and softened force formulas in the Example.

1.1givenF1algebra

For r≠0, their scalar denominators are ∣r∣3 and (∣r∣2+ε2)3/2, which differ because ε>0. Thus Fε(r)≠F(r) for every nonzero r.

2.1givenstep 1.1algebra∎

At r=0, the unsoftened formula is undefined, whereas the softened formula gives Fε(0)=0. The denominator ∣r∣2+ε2 is smooth and strictly positive, and u↦u−3/2 is smooth for u>0; hence the softened field is C∞ on all of R3. Its smooth extension therefore supplies a convention for its own regularized model, not a collision law for the singular Newtonian system.

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A dimension-dependent lower bound for empirical W1 error

Example

Let M∈N with M≥1, set VM={0,1}M⊂RM, and let μM be uniform on its 2M vertices. For any empirical measure νN=N−1∑j=1NδYj obtained from N samples Yj∈VM, the 1-Wasserstein error has the deterministic lower bound W1(μM,νN)≥1−N2M. Thus no dimension-free bound W1(μ,μN)≤CN−1/2 can hold uniformly over all dimensions and all empirical samples.

Facts & Assumptions

Given: The uniform probability on VM, an integer N≥1, and any list of sample vertices Y1,…,YN∈VM.

[F1]

W1 is the infimum of mean Euclidean transport costs over probability couplings (The coupling definition of the 1-Wasserstein distance).

Verification

Given: The data in the Example.

1.1givenalgebra

Let S={Y1,…,YN} be the empirical support. It contains at most N vertices, so μM(VM∖S)≥1−N/2M. Distinct vertices of VM have Euclidean distance at least one.

2.1F1step 1.1algebra∎

In any coupling of μM to νN, every point of VM∖S must send its mass to a point of S, at cost at least one per unit mass. Hence every coupling costs at least 1−N/2M, and taking the infimum in [F1] proves the bound. If 2M≥2N, it is at least 1/2; choosing N arbitrarily large and then such an M rules out a uniform dimension-free CN−1/2 bound.

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A mixed-sign vorticity is not a probability for W1

Example

On R2, let ω=δ0−δ(1,0). It is a nonzero finite signed measure of total mass zero and total variation two. The probability W1 in The coupling definition of the 1-Wasserstein distance cannot be applied to ω.

Facts & Assumptions

Given: The signed measure ω of the Example.

[F1]

W1 is defined only for probability measures with finite first moment (The coupling definition of the 1-Wasserstein distance).

[F2]

dBL is the dual supremum over functions bounded by one with Lipschitz constant at most one (Bounded-Lipschitz dual discrepancy for finite signed measures).

[F3]

Total variation is the supremum over measurable partition sums (The total variation |nu|(E) from countable measurable partitions).

[F4]

The reverse triangle inequality gives ∣∣x∣−∣y∣∣≤∣x−y∣ for the Euclidean norm (Cauchy-Schwarz ∣⟨x,y⟩∣≤∥x∥2∥y∥2 with its equality case, the triangle inequality for ∥⋅∥2, the parallelogram law and polarisation).

Verification

Given: ω=δ0−δ(1,0).

1.1givenF1F3algebra

Among any countable partition, at most two cells have nonzero signed mass, each of magnitude one; the partition into the two singleton atoms and their complement attains the sum two. Thus ∣ω∣(R2)=2 by [F3], while its signed mass is 1−1=0. Therefore ω is neither a nonnegative probability measure nor normalizable by its net mass, so the domain condition in [F1] fails.

2.1F2F4step 1.1algebra∎

The function ϕ(x)=min⁡(1,∣x∣) is bounded by one and 1-Lipschitz by [F4], with ϕ(0)=0 and ϕ(1,0)=1. Hence ∣∫ϕdω∣=1, so dBL(ω,0)≥1. This finite signed dual quantity remains meaningful by [F2], whereas probability W1(ω,0) is undefined.

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A globally Lipschitz alignment model with exact mean trajectory

Example

For a≥0 on Rd, take K(x,y)=a(y−x). For a>0, each particle is pulled toward the current mean position; for a=0, every particle is stationary. It is globally Lipschitz, and its particle trajectories are explicit.

Facts & Assumptions

Given: a≥0, N≥1, and initial positions xi(0)∈Rd.

[F1]

A globally Lipschitz interaction kernel uses the two-coordinate bound in Globally Lipschitz mean-field interaction kernel.

[F2]

The equal-probability particle system is x˙i=N−1∑jK(xi,xj) (Equal-probability mean-field and weighted signed vortex particle systems).

[F3]

The empirical particle measure satisfies the exact weak equation (Exact weak mean-field identity for empirical particle measures).

[F4]

General characteristic probability solutions obey the e2Lt stability estimate (Dobrushin stability in 1-Wasserstein distance for mean-field flows).

Verification

Given: The data in the Example and K(x,y)=a(y−x).

1.1givenF1algebra

For all x,y,x′,y′, ∣K(x,y)−K(x′,y′)∣=a∣(y−y′)−(x−x′)∣≤a(∣x−x′∣+∣y−y′∣), so the global Lipschitz constant may be taken as L=a in [F1].

2.1F2F3F4step 1.1algebra∎

Substitution into [F2] gives x˙i=a(xˉ−xi), where xˉ=N−1∑jxj. Summing over i yields xˉ˙=0, and hence xi(t)=xˉ(0)+e−at(xi(0)−xˉ(0)). For a>0, the formula tends to the constant mean as t→∞; for a=0, it equals xi(0). Thus the empirical measure is an exact weak solution by [F3]; for probability solutions the stability factor is e2at by [F4].

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Same-sign smooth vortex density and probability blob error budget

Example

Assume Countable Choice. Let ω0∈Cc∞(R2) be nonnegative with mass one, and suppose the smooth Euler flow satisfies ωt=(Xt)#ω0, X˙t=(K∗ωt)(Xt), and sup⁡t≤T∥ωt∥∞≤W, with ∫sup⁡t≤T∣Xt(x)∣dω0(x)<∞. Approximate it by N≥1 distinct initial positions x10,…,xN0 with equal weights 1/N, define μN0=N−1∑iδxi0, and let E0=W1(ω0,μN0).

Let R=[a,b]×[c,d] with a<b and c<d, let nx,ny be even integers at least two, and put hx=(b−a)/nx and hy=(d−c)/ny. For every time t∈[0,T] and force location z∈R2, let Ft,z∈C4(R,R2) and assume the uniform bounds sup⁡t∈[0,T],z∈R2max⁡(x,y)∈R∣∂x4Ft,z(x,y)∣≤M40,sup⁡t∈[0,T],z∈R2max⁡(x,y)∈R∣∂y4Ft,z(x,y)∣≤M04. Define rq(t,z)=QyQxFt,z−∫RFt,z and ηq=2∣R∣180(hx4M40+hy4M04),∣R∣=(b−a)(d−c), where Qx,Qy are the composite Simpson rules in the two rectangle coordinates. By Tensor composite Simpson error for a two-dimensional force integral, ∣rq(t,z)∣≤ηq uniformly. Assume this common residual is smooth in (t,z), and let the exact particles solve x˙i=1N∑jKε(xi−xj)+rq(t,xi). Assume the resulting nonautonomous field is jointly C4 on an open time-state domain D, with derivatives through order four bounded on a common compact convex tube T⋐D containing the exact paths and RK4 stages. For an integer n≥1 with h=T/n≤h0, let xih(T) be their RK4 approximations from the same initial nodes, with all paths and stages in that tube. Define ωN,hε,q(T)=N−1∑iδxih(T). If CRK is the coefficient from Fourth-order global error for RK4 on a regularized vortex particle tube for this h0, then

W1(ωT,ωN,hε,q(T))≤e2LεT(E0+T(CρεW+ηq))+CRKh4.

The RK4 tube hypothesis includes all numerical grid states and every stage generated at each grid step from both the exact start and the numerical start, and both one-step maps are defined, as required by Fourth-order global error for RK4 on a regularized vortex particle tube.

Facts & Assumptions

Given: The smooth probability vorticity and Euler flow; distinct initial particle nodes; fixed ε>0; a common smooth spatial quadrature field with residual ηq; and the RK4 tube and derivative hypotheses.

[A1]

Assume Countable Choice for the polar-coordinate kernel-consistency estimate (The Axiom of Countable Choice (ACω)).

[F1]

W1 is the coupling infimum for finite-first-moment probability measures (The coupling definition of the 1-Wasserstein distance); the product coupling has finite cost (The coupling infimum is finite for finite-first-moment probabilities).

[F2]

Kernel mollification gives force defect at most CρεW (L1 consistency of the mollified Biot-Savart kernel).

[F3]

Tensor Simpson gives the uniform residual ηq=2∣R∣(hx4M40+hy4M04)/180 (Tensor composite Simpson error for a two-dimensional force integral).

[F4]

Given characteristic flows with force defects η1,η2, every initial coupling transports with cost at most e2Lt(D0+(η1+η2)t) (Probability W1 stability under bounded force defects).

[F5]

RK4 on the controlled smooth particle tube has maximum Euclidean state error at most CRKh4 (Fourth-order global error for RK4 on a regularized vortex particle tube).

[F6]

The mollified kernel has a finite global Lipschitz constant Lε (The mollified Biot-Savart kernel is smooth and globally Lipschitz).

Verification

Given: The data in the Example and the estimate E0=W1(ω0,μN0) for the initial empirical probability.

1.1A1givenF2F3F4F6choose

Write the exact Euler characteristic velocity as the mollified interaction plus residual (K−Kε)∗ωt, whose norm is at most CρεW by [F2]. The quadrature particle field is the mollified interaction plus a common residual of norm at most ηq by [F3]. Fix any initial coupling with cost D0≤E0+δ, where δ>0. Transport it by the Euler flow and the exact quadrature-force particle flow. By [F4], the resulting coupling has cost at time T at most e2LεT(E0+δ+T(CρεW+ηq)).

2.1F1F5F6step 1.1∎

Use the same initial particle label in the exact quadrature-force path and the RK4 path. The RK4 state error in [F5] is Euclidean on the full particle state, so each particle-block displacement is at most CRKh4. Since the initial nodes are distinct, partition the coupling by its second coordinate and label each part by its unique particle index. Push this labelled coupling through the exact Euler flow in the first coordinate and the RK4 particle map in the second. The resulting coupling from the Euler law to the RK4 empirical law has cost at most the step 1.1 bound plus CRKh4. Thus it bounds their W1. Since δ>0 was arbitrary, let δ↓0 to obtain W1(ωT,ωN,hε,q(T))≤e2LεT(E0+T(CρεW+ηq))+CRKh4. This same-sign estimate uses probability transport and has no AC hypothesis; it makes no uniform claim as ε→0.

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