Let l, m, A, β with rate bound B, (U,V,βˉ) with derivative bound K, bˉ, (L,G), (Uc,Lˉ,Gˉ) with second-derivative bound Kc, T>0, and (S,A) be as in the definition of a stationary mean-field triple (the open set of the cost extension, written W in that definition, is written Uc here, so that Lˉ is defined on Uc×Rm and Gˉ on Uc), and let P be a stationary co-state for these data. Adopt the coordinate and partial-derivative notation ∂i, ∂j∂i of the extensiondefinitions: the partial derivatives of orders one and two of each bˉδ exist and are continuous on U×V by part (i) of the regularity of the extended aggregate state drift, and those of Lˉ on Uc×Rm by clause 2 of the cost extension definition together with clauses 1 and 2 of the Ck definition. Let Hij(t), for t∈[0,T] and i,j∈{1,…,l+m}, be the fluctuation Hessian coefficients of these data. Write R for the real numbers, d for the Euclidean distance, ∣⋅∣ for the Euclidean norm (Euclidean distance to the origin), and Δl for the probability simplex. Throughout, a real-valued function on a subinterval I of the real numbers R is called continuous on I when it is continuous relative to I, both I and the codomain R carrying the metric of the real line. Fix a real number CP with ∑δ=1l∣Ptδ∣≤CP for every t∈[0,T]; such a number exists because each component of P is continuous on [0,T] by clause 1 of the co-state definition and therefore attains a maximum and a minimum on [0,T] by the extreme value theorem.
Define the mean-field Hamiltonian along the triple as the function on [0,T]×V given by
which is well defined because St∈Δl⊂U∩Uc and V⊆Rm; the script letter H is distinct from the Hessian coefficients Hij. Define, for t∈[0,T], the real m×m matrix Rt with entries
and write a⋅Rta=∑i,j=1mRtijaiaj for a∈Rm; the displayed formula agrees with the definition of Rt in the completion-of-squares theorem, and only that formula and the wording of its hypothesis (H1) are borrowed from that theorem, not its setting.
Hypotheses.(A) The control set A is convex and compact for the topology determined by the Euclidean distance. (H1) There is a real number r>0 with a⋅Rta≥r∣a∣2 for every t∈[0,T] and every a∈Rm (hypothesis (H1) of the completion-of-squares theorem). (U) For every t∈[0,T], the point At is the unique minimizer of Ht on A: Ht(a)>Ht(At) for every a∈A with a=At.
Then:
(a) (Continuity.) Regarding [0,T]×V as a subset of Euclidean spaceR1+m, the map (t,a)↦Ht(a) is continuous at every point of [0,T]×V, and so is the map (t,a)↦Ht(At); this uses none of the hypotheses (A), (H1), (U).
(b) (Stationarity and the Hessian in the control.) For every t∈[0,T] and j∈{1,…,m},
∂l+jLˉ(St,At)−δ=1∑lPtδ∂l+jbˉδ(St,At)=0,
and for every h∈Rm,
21i=1∑mj=1∑mHl+i,l+j(t)hihj=h⋅Rth.
This uses none of the hypotheses (A), (H1), (U).
(c) (Upper quadratic bound.) Assume that A is convex (only the convexity half of (A) is used). Put M2=Kc+3lKCP and CH=21(l+m)M2. Then for every t∈[0,T] and every a∈A,
Ht(a)−Ht(At)≤CH∣a−At∣2.
(d) (Quadratic growth.) Assume (A), (H1), and (U). Then there is a real number r0>0 such that
Ht(a)−Ht(At)≥r0∣a−At∣2for every t∈[0,T] and every a∈A.
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