TheoremBase

The Even-Split Equilibrium of the Ising Population Model is a Stationary Mean-Field Triple and is Optimal

The constant triple with an even population split, unit transition rates and vanishing co-state is a stationary mean-field triple whose control is the unique Hamiltonian minimiser and is globally optimal for the mean-field problem, and the first-order to-go regularity hypothesis holds with vanishing constant.

Statement

Fix parameters as in The Ising Population Data (i) and adopt the Ising population data with those parameters, together with The Ising Population Model Instantiates the Data of the Fluctuation Theory, whose claims identify β\beta, its aggregate state drift bb, the extensions (U,V,βˉ)(U,V,\bar{\beta}) and (Uc,Lˉ,Gˉ)(U_{c},\bar{L},\bar{G}), the extended aggregate state drift bˉ\bar{b}, and the partial derivatives of Lˉ\bar{L}. Adopt the coordinate and partial-derivative notation ∂i\partial_{i} of the extension definitions, as in that lemma. Write UA\mathcal{U}_{\mathcal{A}} for the set of A\mathcal{A}-valued controls on [0,θ][0,\theta] for a horizon θ>0\theta>0, F[θ]F^{[\theta]} for the mean-field cost and Jx∗[θ]J^{*[\theta]}_{x}, Mx∗[θ]\mathcal{M}^{*[\theta]}_{x} for the optimal mean-field value and the set of optimal mean-field controls from x∈Δ2x\in\Delta^{2}, all formed with the data (β0,β1)(\beta_{0},\beta_{1}), (L,G)(L,G) and the horizon θ\theta; the superscript [θ][\theta] is dropped when θ=T\theta=T.

Define the equilibrium triple of these data to be the three constant maps S,A,P:[0,T]→R2S,A,P:[0,T]\to\mathbb{R}^{2} given by

St=(12,12),At=(1,1),Pt=(0,0)(t∈[0,T]):S_{t}=\Bigl(\tfrac{1}{2},\tfrac{1}{2}\Bigr),\qquad A_{t}=(1,1),\qquad P_{t}=(0,0)\qquad(t\in[0,T]) :

an evenly split population, held there by unit transition rates, with vanishing co-state. Then the following hold.

1. (A trajectory pair.) b(St,At)=0b(S_{t},A_{t})=0 for every t∈[0,T]t\in[0,T], and (S,A)(S,A) is a mean-field trajectory pair for β\beta with horizon TT. Moreover SS takes values in Δ2\Delta^{2}, S0=(12,12)S_{0}=\bigl(\tfrac{1}{2},\tfrac{1}{2}\bigr), and Stγ=S0γ+∫[0,t]bγ(Ss,As) dsS^{\gamma}_{t}=S^{\gamma}_{0}+\int_{[0,t]}b^{\gamma}(S_{s},A_{s})\,ds for every t∈[0,T]t\in[0,T] and γ∈{1,2}\gamma\in\{1,2\}, so that SS satisfies, with x0=S0x_{0}=S_{0}, the standing hypothesis on the map written S∗S^{*} in The Block Cascade of Anchored Good-Set Clocks: Adapted Good Sets, Matched Escape Bounds, and the Energy Ledger.

2. (A stationary mean-field triple.) All four first-order partial derivatives of Lˉ\bar{L} vanish at (St,At)(S_{t},A_{t}) for every t∈[0,T]t\in[0,T]. The map PP is a stationary co-state for β\beta, (L,G)(L,G) and the chosen extensions, so that (S,A,P)(S,A,P) is a stationary mean-field triple for them; and the constant CP=0C_{P}=0 satisfies ∑δ=12∣Ptδ∣≤CP\sum_{\delta=1}^{2}|P^{\delta}_{t}|\le C_{P} for every t∈[0,T]t\in[0,T].

3. (Hypothesis (U).) The mean-field Hamiltonian along the triple, in the sense of Quadratic Growth of the Mean-Field Hamiltonian in the Control along a Stationary Mean-Field Triple, is

Ht(a)=12χ(ϕ(a1)+ϕ(a2))(t∈[0,T], a∈V),\mathcal{H}_{t}(a)=\frac{1}{2\chi}\bigl(\phi(a^{1})+\phi(a^{2})\bigr)\qquad(t\in[0,T],\ a\in V),

and for every t∈[0,T]t\in[0,T] the point At=(1,1)A_{t}=(1,1) is the unique minimiser of Ht\mathcal{H}_{t} on A\mathcal{A}, with Ht(At)=0\mathcal{H}_{t}(A_{t})=0; that is, hypothesis (U) of that lemma holds.

4. (Optimality of the equilibrium control.) Let θ>0\theta>0 be a real number. Then Jx∗[θ]≥0J^{*[\theta]}_{x}\ge0 for every x∈Δ2x\in\Delta^{2}, and J(1/2,1/2)∗[θ]=0J^{*[\theta]}_{(1/2,1/2)}=0, this value being attained by the class in UA\mathcal{U}_{\mathcal{A}} of the constant map with value (1,1)(1,1) on [0,θ][0,\theta]. In particular, with θ=T\theta=T, the class [A][A] lies in MS0∗\mathcal{M}^{*}_{S_{0}}.

5. (Hypothesis (TG).) Hypothesis (TG) of Quadratic Expansion Bounds for the Mean-Field To-Go Value along a Stationary Mean-Field Triple holds for these data and the triple (S,A,P)(S,A,P), with the constants εtg=1\varepsilon_{tg}=1 and Ctg=0C_{tg}=0.

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