Adopt the setting and notation of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record, with the probability space of that lemma renamed (Ω♭,F♭,P♭): natural numbers N≥1, l≥2, m≥1, l~≥1; a nonempty control set A⊆Rm in Euclidean space; real numbers B≥0, B~≥0 and T>0; a transition-rate family β with control set A and rate bound B; an observation-rate family β~ with rate bound B~, its aggregate observation drift b~=(b~υ) and the total observation rate b~tot=∑υ=1l~b~υ on the probability simplex Δl; the aggregate lattice GN⊆Δl and the point x0∈GN; the observation record space (R,R,ρ) with horizon T and l~ channels, records written r=(k,t,v) with t=(t1,…,tk) and v=(v1,…,vk); an A-valued observation-driven control policy h with record-frozen control paths ar; the real number R, for which we assume the strict inequality R>NBT; the cells, the index set L, the dimension d, the smoothing parameter η (a real number occurring only as the subscript of the Gaussian smoothing weight φη; the occupation indicators ηr,i,γ below always carry superscripts), the Borel σ-algebra B(Rd) and Lebesgue measure λd on Rd; the driving variables and the cell-count vector K on (Ω♭,F♭,P♭); the copy clocks P♯; the regularised recursion paths Σˉt♯,r(ω♭), the likelihoods ℓ♯,ω♭(r) and the conflict-free set G♯ of claim 3 of that lemma; and the synthetic copy (Ω♯,F♯,μ♯) with Ω♯=Ω♭×Rd×R, F♯=(F♭⊗B(Rd))⊗R, and the record D(ω♭,θ,r)=r. Integrals of [0,∞]-valued measurable maps are those of Lebesgue Integral of a Nonnegative Measurable Function, products being formed with the convention 0⋅∞=0 of Image Measures, Measures with Densities, and Change of Variables, and 1S denotes the indicator of a set S.
Let moreover (Ω,F,P) be an N-agent driving system with l states and l~ observation channels, with expectation E (extended to [0,∞]-valued measurable maps as their integrals with respect to P); let a solution of the controlled N-agent dynamics on [0,T] for the policy h and for the same data m, A, β, B, β~, B~ and T be given, with regular event Ω0, empirical state measure Σt and observation record W; and fix reconstruction data (ηr,i,γ,σr,i,A~r,i,υ,G) for this driving system and policy, with reconstructed empirical state measures Σr and, for each r∈R, the event Ωr of clause (d) of that lemma. Put D0={Σ0=x0}.
Let Path=Path(GN,T) be the space of piecewise constant paths in GN with horizon T, with its σ-algebra C=CT generated by the sets {p:p(u)=y} (u∈[0,T], y∈GN), and write C⊗R for the product σ-algebra on Path×R. Define Π on Ω, with values in the set of maps [0,T]→GN (the empirical state measure Σu(ω) lies in GN for every ω and u, its coordinates being agent counts divided by N), by Π(ω)(u)=Σu(ω) for ω∈Ω0 and Π(ω)(u)=x0 for ω∈/Ω0; and define Π♯ on Ω♯ by Π♯(ω♭,θ,r)(u)=Σˉu♯,r(ω♭) (u∈[0,T]). Then:
1. (Measurability.) D0∈F; Π and Π♯ take their values in Path and are measurable with respect to F, respectively F♯, and C; W is measurable with respect to F and R, and D with respect to F♯ and R.
2. (Law identity for path and record.) For every F:Path×R→[0,∞] measurable with respect to C⊗R,
E[1D0F(Π,W)]=P(D0)∫Ω♯F(Π♯,D)dμ♯in [0,∞].
3. (Law identity for the aggregate at a fixed time and the record.) For every s∈[0,T] and every F′:GN×R→[0,∞] measurable with respect to the product of the σ-algebra of all subsets of GN and R,
E[1D0F′(Σs,W)]=P(D0)∫Ω♯F′(Σˉs♯,D,D)dμ♯in [0,∞],
where Σˉs♯,D(ω♭,θ,r)=Σˉs♯,r(ω♭). In particular, if P(D0)=1, the pair (Σs,W) under P and the pair (Σˉs♯,D,D) under μ♯ have the same image measure on the product of the σ-algebra of all subsets of GN and R.