TheoremBase

Proof

Throughout we fix an ordered pair (σ,γ)(\sigma,\gamma) with σ≠γ\sigma\neq\gamma in {1,…,l}\{1,\dots,l\} and abbreviate g=βˉ0(σ,γ,⋅)g=\bar{\beta}_0(\sigma,\gamma,\cdot) and gk=βˉ1k(σ,γ,⋅)g_k=\bar{\beta}_1^k(\sigma,\gamma,\cdot) for k∈{1,…,m}k\in\{1,\dots,m\}; these are real-valued functions on UU. All estimates obtained below hold for every such pair, of which there are finitely many. We write

F(x)=βˉ(σ,γ,Σ,α)=g(Σ)+∑k=1mgk(Σ) αk(x=(Σ,α)∈U×V),F(x)=\bar{\beta}(\sigma,\gamma,\Sigma,\alpha)=g(\Sigma)+\sum_{k=1}^mg_k(\Sigma)\,\alpha^k\qquad(x=(\Sigma,\alpha)\in U\times V),

the second equality being the coordinate formula for the dot product. We use throughout the norm properties: clause 1 (the square of the norm is the sum of the squares of the coordinates), clause 4 (∣xi∣≤∣x∣|x_i|\le|x|), clause 5 (absolute homogeneity) and clause 6 (the triangle inequality). By the definition of the rate data, UU is open, convex and bounded with Δl⊂U\Delta^l\subset U, the control set A\mathcal{A} is nonempty, convex and compact, each of g,g1,…,gmg,g_1,\dots,g_m is a C1C^1 map on UU whose partial derivatives are again C1C^1 on UU, and all of ∣g∣,∣gk∣|g|,|g_k|, their first partial derivatives and their second partial derivatives are bounded by K0K_0 on UU.

Step 0. Elementary bounds.

(0a) If n≥1n\ge1, y∈Rny\in\mathbb{R}^n and C≥0C\ge0 is a real number with ∣yi∣≤C|y_i|\le C for every ii, then ∣y∣≤n C|y|\le\sqrt{n}\,C. Indeed yi2=∣yi∣2≤C2y_i^2=|y_i|^2\le C^2 by monotonicity of squaring (clause 2), so ∣y∣2=∑iyi2≤nC2=(n C)2|y|^2=\sum_iy_i^2\le nC^2=(\sqrt{n}\,C)^2, and since ∣y∣≥0|y|\ge0 and n C≥0\sqrt{n}\,C\ge0 the same clause, read in the other direction, gives ∣y∣≤n C|y|\le\sqrt{n}\,C.

(0b) 1≤l1\le\sqrt{l} and 1≤m1\le\sqrt{m}: since 1≤l1\le l and 12=11^2=1, (l)2=l(\sqrt{l})^2=l, clause 2 of the same lemma applied to the nonnegative reals 11 and l\sqrt{l} gives 1≤l1\le\sqrt{l}; likewise for mm.

(0c) For x=(Σ,α)x=(\Sigma,\alpha) and x′=(Σ′,α′)x'=(\Sigma',\alpha') in Rl+m\mathbb{R}^{l+m} we have ∣Σ−Σ′∣≤∣x−x′∣|\Sigma-\Sigma'|\le|x-x'| and ∣α−α′∣≤∣x−x′∣|\alpha-\alpha'|\le|x-x'|, because ∣Σ−Σ′∣2≤∣Σ−Σ′∣2+∣α−α′∣2=∣x−x′∣2|\Sigma-\Sigma'|^2\le|\Sigma-\Sigma'|^2+|\alpha-\alpha'|^2=|x-x'|^2 and both quantities are nonnegative, so clause 2 of the monotonicity lemma applies; similarly for the second inequality.

(0d) U×VU\times V is an open subset of Rl+m\mathbb{R}^{l+m} once VV is known to be open (Step 2): given x=(Σ,α)∈U×Vx=(\Sigma,\alpha)\in U\times V, choose ρ1,ρ2>0\rho_1,\rho_2>0 such that every point within distance ρ1\rho_1 of Σ\Sigma lies in UU and every point within distance ρ2\rho_2 of α\alpha lies in VV; if ∣x′−x∣<min⁡(ρ1,ρ2)|x'-x|<\min(\rho_1,\rho_2) then by (0c) ∣Σ′−Σ∣<ρ1|\Sigma'-\Sigma|<\rho_1 and ∣α′−α∣<ρ2|\alpha'-\alpha|<\rho_2, so x′∈U×Vx'\in U\times V.

Step 1. The restriction is an affine-controlled family (clause 1).

Requirement 1 of an affine-controlled transition-rate family is exactly clause 1 of the rate-data definition, restricted to Δl×A\Delta^l\times\mathcal{A}.

For requirement 2, let ff be any one of g,g1,…,gmg,g_1,\dots,g_m and let Σ,Σ′∈Δl\Sigma,\Sigma'\in\Delta^l. Since Δl⊂U\Delta^l\subset U and UU is convex, the segment joining Σ\Sigma to Σ′\Sigma' lies in UU. The map ff is C1C^1 on the open set UU with ∣∂if∣≤K0|\partial_if|\le K_0 there, so clause (i) of the multivariate Taylor lemma, applied with n=ln=l and M1=K0M_1=K_0, gives

∣f(Σ)−f(Σ′)∣≤l K0 ∣Σ−Σ′∣.|f(\Sigma)-f(\Sigma')|\le\sqrt{l}\,K_0\,|\Sigma-\Sigma'| .

In particular ∣β0(Σ)−β0(Σ′)∣≤l K0∣Σ−Σ′∣≤Λ∣Σ−Σ′∣|\beta_0(\Sigma)-\beta_0(\Sigma')|\le\sqrt{l}\,K_0|\Sigma-\Sigma'|\le\Lambda|\Sigma-\Sigma'|, using 1≤m1\le\sqrt{m} from (0b). Applying the displayed bound to each component gkg_k and then (0a) in Rm\mathbb{R}^m gives

∣β1(Σ)−β1(Σ′)∣≤m l K0 ∣Σ−Σ′∣=Λ∣Σ−Σ′∣.|\beta_1(\Sigma)-\beta_1(\Sigma')|\le\sqrt{m}\,\sqrt{l}\,K_0\,|\Sigma-\Sigma'|=\Lambda|\Sigma-\Sigma'| .

Thus both maps are Lipschitz with constant Λ\Lambda on Δl\Delta^l, and since A\mathcal{A} is nonempty, convex and compact, (β0,β1)(\beta_0,\beta_1) is an affine-controlled transition-rate family on ll states with control set A\mathcal{A} and Lipschitz constant Λ\Lambda. By clause 1 of the lemma on affine-controlled data, RR and BB are finite nonnegative real numbers, and by its clause 2 the associated β\beta is a transition-rate family on ll states with control set A\mathcal{A} and rate bound BB. This proves clause 1.

Step 2. The set VV (clause 2).

A⊆V\mathcal{A}\subseteq V. For α∈A\alpha\in\mathcal{A} the set whose infimum defines ρ(α)\rho(\alpha) contains the value ∣α−α∣=0|\alpha-\alpha|=0 and consists of nonnegative numbers, so ρ(α)=0<1\rho(\alpha)=0<1.

Openness. Let α∈V\alpha\in V and put s=ρ(α)<1s=\rho(\alpha)<1 and ϱ=1−s>0\varrho=1-s>0. If ∣α′−α∣<ϱ|\alpha'-\alpha|<\varrho then clause 3 of the nonexpansiveness lemma gives ρ(α′)≤∣α′−α∣+ρ(α)<ϱ+s=1\rho(\alpha')\le|\alpha'-\alpha|+\rho(\alpha)<\varrho+s=1, so α′∈V\alpha'\in V. Hence VV is open.

The bound ∣α∣≤R+1|\alpha|\le R+1, and boundedness. Let α∈V\alpha\in V, put s=ρ(α)<1s=\rho(\alpha)<1 and ε=(1−s)/2>0\varepsilon=(1-s)/2>0. By clause 4 of the approximation property of the infimum there is a∈Aa\in\mathcal{A} with ∣α−a∣<s+ε<1|\alpha-a|<s+\varepsilon<1. Since ∣a∣≤R|a|\le R by the definition of RR as a supremum, the triangle inequality gives ∣α∣≤∣a∣+∣α−a∣≤R+1|\alpha|\le|a|+|\alpha-a|\le R+1. In particular every point of VV lies within distance R+1R+1 of the origin, so VV is a bounded set.

Convexity. Let α,α′∈V\alpha,\alpha'\in V and let tt be real with 0≤t≤10\le t\le1. Put s=max⁡{ρ(α),ρ(α′)}<1s=\max\{\rho(\alpha),\rho(\alpha')\}<1 and ε=(1−s)/2>0\varepsilon=(1-s)/2>0, and apply the approximation property of the infimum separately to ρ(α)\rho(\alpha) and to ρ(α′)\rho(\alpha') to obtain a,a′∈Aa,a'\in\mathcal{A} with ∣α−a∣<ρ(α)+ε≤s+ε|\alpha-a|<\rho(\alpha)+\varepsilon\le s+\varepsilon and ∣α′−a′∣<ρ(α′)+ε≤s+ε|\alpha'-a'|<\rho(\alpha')+\varepsilon\le s+\varepsilon. Since A\mathcal{A} is convex, ta+(1−t)a′∈Ata+(1-t)a'\in\mathcal{A}, and by absolute homogeneity and the triangle inequality

∣tα+(1−t)α′−(ta+(1−t)a′)∣≤t∣α−a∣+(1−t)∣α′−a′∣<s+ε<1.\big|t\alpha+(1-t)\alpha'-\big(ta+(1-t)a'\big)\big|\le t|\alpha-a|+(1-t)|\alpha'-a'|<s+\varepsilon<1 .

As ρ(tα+(1−t)α′)\rho(t\alpha+(1-t)\alpha') is a lower bound for the distances to points of A\mathcal{A}, it follows that ρ(tα+(1−t)α′)<1\rho(t\alpha+(1-t)\alpha')<1, that is, tα+(1−t)α′∈Vt\alpha+(1-t)\alpha'\in V. This proves clause 2, and with it (0d).

Step 3. The partial derivatives of βˉ\bar{\beta} (clause 4).

Let x=(Σ,α)∈U×Vx=(\Sigma,\alpha)\in U\times V.

(a) State coordinates. Fix i∈{1,…,l}i\in\{1,\dots,l\} and hold all coordinates of xx except xix_i fixed. By the slice-function lemma, the slice of gg in the coordinate xix_i is differentiable at Σ\Sigma with derivative ∂ig(Σ)\partial_ig(\Sigma), and likewise for each gkg_k. The slice of FF in the coordinate xix_i is the finite linear combination of these slices with the constant coefficients 1,α1,…,αm1,\alpha^1,\dots,\alpha^m, so by the linear-combination rule it is differentiable with derivative ∂ig(Σ)+∑kαk∂igk(Σ)\partial_ig(\Sigma)+\sum_k\alpha^k\partial_ig_k(\Sigma). By the slice-function lemma again,

∂iF(x)=∂ig(Σ)+∑k=1mαk ∂igk(Σ).\partial_iF(x)=\partial_ig(\Sigma)+\sum_{k=1}^m\alpha^k\,\partial_ig_k(\Sigma).

(b) Control coordinates. Fix k∈{1,…,m}k\in\{1,\dots,m\} and hold all coordinates except xl+kx_{l+k} fixed. The slice of FF in that coordinate is the map t↦c0+gk(Σ) tt\mapsto c_0+g_k(\Sigma)\,t, where c0=g(Σ)+∑k′≠kgk′(Σ)αk′c_0=g(\Sigma)+\sum_{k'\neq k}g_{k'}(\Sigma)\alpha^{k'} does not depend on tt. For every real h≠0h\neq0 the corresponding difference quotient is

(c0+gk(Σ)(t+h))−(c0+gk(Σ)t)h=gk(Σ),\frac{\big(c_0+g_k(\Sigma)(t+h)\big)-\big(c_0+g_k(\Sigma)t\big)}{h}=g_k(\Sigma),

a quantity independent of hh; hence the slice is differentiable with derivative gk(Σ)g_k(\Sigma), and by the slice-function lemma ∂l+kF(x)=gk(Σ)\partial_{l+k}F(x)=g_k(\Sigma). This is the first identity of clause 4.

(c) Second derivatives. The function ∂iF\partial_iF computed in (a) has exactly the form treated in (a) and (b), with g,gkg,g_k replaced by ∂ig,∂igk\partial_ig,\partial_ig_k, which are again C1C^1 on UU. Hence, for i,i′∈{1,…,l}i,i'\in\{1,\dots,l\} and k∈{1,…,m}k\in\{1,\dots,m\},

∂i′∂iF(x)=∂i′∂ig(Σ)+∑k=1mαk ∂i′∂igk(Σ),∂l+k∂iF(x)=∂igk(Σ),\partial_{i'}\partial_iF(x)=\partial_{i'}\partial_ig(\Sigma)+\sum_{k=1}^m\alpha^k\,\partial_{i'}\partial_ig_k(\Sigma),\qquad \partial_{l+k}\partial_iF(x)=\partial_ig_k(\Sigma),

the second identity being the third identity of clause 4. Finally ∂l+kF(x)=gk(Σ)\partial_{l+k}F(x)=g_k(\Sigma) depends only on Σ\Sigma, so its slice in any control coordinate xl+k′x_{l+k'} is constant and every difference quotient vanishes, giving ∂l+k′∂l+kF=0\partial_{l+k'}\partial_{l+k}F=0, the second identity of clause 4; and its slice in a state coordinate xi′x_{i'} gives ∂i′∂l+kF(x)=∂i′gk(Σ)\partial_{i'}\partial_{l+k}F(x)=\partial_{i'}g_k(\Sigma). This proves clause 4.

Step 4. Derivative bounds.

By the bounds in the rate-data definition and (0a) in Rm\mathbb{R}^m, the vector ∂iβˉ1(σ,γ,Σ)\partial_i\bar{\beta}_1(\sigma,\gamma,\Sigma) with components ∂igk(Σ)\partial_ig_k(\Sigma) satisfies ∣∂iβˉ1(σ,γ,Σ)∣≤m K0|\partial_i\bar{\beta}_1(\sigma,\gamma,\Sigma)|\le\sqrt{m}\,K_0, and similarly for the vectors formed by ∂i′∂igk(Σ)\partial_{i'}\partial_ig_k(\Sigma) and by gk(Σ)g_k(\Sigma). Using clause 2 of the present lemma (∣α∣≤R+1|\alpha|\le R+1 on VV) and the Cauchy-Schwarz inequality, the identities of Step 3 give, at every point of U×VU\times V,

∣∂iF∣≤K0+m K0(R+1)=K,∣∂l+kF∣=∣gk∣≤K0≤K,|\partial_iF|\le K_0+\sqrt{m}\,K_0(R+1)=K,\qquad |\partial_{l+k}F|=|g_k|\le K_0\le K,

and, for the second derivatives,

∣∂i′∂iF∣≤K0+m K0(R+1)=K,∣∂l+k∂iF∣=∣∂igk∣≤K0≤K,∣∂i′∂l+kF∣=∣∂i′gk∣≤K0≤K,|\partial_{i'}\partial_iF|\le K_0+\sqrt{m}\,K_0(R+1)=K,\qquad |\partial_{l+k}\partial_iF|=|\partial_ig_k|\le K_0\le K,\qquad |\partial_{i'}\partial_{l+k}F|=|\partial_{i'}g_k|\le K_0\le K,

and ∣∂l+k′∂l+kF∣=0≤K|\partial_{l+k'}\partial_{l+k}F|=0\le K, where K0≤KK_0\le K because m(R+1)≥0\sqrt{m}(R+1)\ge0. This is requirement 3 of a twice continuously differentiable extension.

Step 5. Uniform continuity of the second derivatives, and regularity.

Let ε>0\varepsilon>0 be real and put

η=ε2(1+m(R+1)),δ2=ε2(mK0+lK0+1).\eta=\frac{\varepsilon}{2\big(1+\sqrt{m}(R+1)\big)},\qquad \delta_2=\frac{\varepsilon}{2\big(\sqrt{m}K_0+\sqrt{l}K_0+1\big)} .

Requirement 4 of the rate-data definition, applied to each of the finitely many functions g,g1,…,gmg,g_1,\dots,g_m attached to each of the finitely many ordered pairs (σ,γ)(\sigma,\gamma), yields a real δ1>0\delta_1>0 such that all second partial derivatives of all these functions change by at most η\eta between any two points of UU at distance at most δ1\delta_1. Put δ=min⁡{δ1,δ2}>0\delta=\min\{\delta_1,\delta_2\}>0 and let x=(Σ,α)x=(\Sigma,\alpha) and x′=(Σ′,α′)x'=(\Sigma',\alpha') be points of U×VU\times V with ∣x−x′∣≤δ|x-x'|\le\delta; by (0c), ∣Σ−Σ′∣≤δ|\Sigma-\Sigma'|\le\delta and ∣α−α′∣≤δ|\alpha-\alpha'|\le\delta.

For i,i′∈{1,…,l}i,i'\in\{1,\dots,l\} let cc and c′c' be the vectors of Rm\mathbb{R}^m with components ∂i′∂igk(Σ)\partial_{i'}\partial_ig_k(\Sigma) and ∂i′∂igk(Σ′)\partial_{i'}\partial_ig_k(\Sigma') respectively. By (0a), ∣c−c′∣≤m η|c-c'|\le\sqrt{m}\,\eta and ∣c′∣≤m K0|c'|\le\sqrt{m}\,K_0. Hence, by Step 3(c), the triangle inequality and Cauchy-Schwarz,

∣∂i′∂iF(x)−∂i′∂iF(x′)∣≤∣∂i′∂ig(Σ)−∂i′∂ig(Σ′)∣+∣(c−c′)⋅α∣+∣c′⋅(α−α′)∣≤η+m η (R+1)+m K0 δ≤ε2+ε2=ε,|\partial_{i'}\partial_iF(x)-\partial_{i'}\partial_iF(x')|\le\big|\partial_{i'}\partial_ig(\Sigma)-\partial_{i'}\partial_ig(\Sigma')\big|+|(c-c')\cdot\alpha|+|c'\cdot(\alpha-\alpha')|\le\eta+\sqrt{m}\,\eta\,(R+1)+\sqrt{m}\,K_0\,\delta\le\frac{\varepsilon}{2}+\frac{\varepsilon}{2}=\varepsilon ,

using the choices of η\eta and δ2\delta_2. For the mixed second derivatives, Step 3(c) and clause (i) of the Taylor lemma applied to gkg_k (whose first partial derivatives are bounded by K0K_0 on the convex set UU) give

∣∂l+k∂iF(x)−∂l+k∂iF(x′)∣=∣∂igk(Σ)−∂igk(Σ′)∣≤l K0∣Σ−Σ′∣≤l K0 δ≤ε2≤ε,|\partial_{l+k}\partial_iF(x)-\partial_{l+k}\partial_iF(x')|=|\partial_ig_k(\Sigma)-\partial_ig_k(\Sigma')|\le\sqrt{l}\,K_0|\Sigma-\Sigma'|\le\sqrt{l}\,K_0\,\delta\le\frac{\varepsilon}{2}\le\varepsilon ,

and the same bound for ∣∂i′∂l+kF(x)−∂i′∂l+kF(x′)∣|\partial_{i'}\partial_{l+k}F(x)-\partial_{i'}\partial_{l+k}F(x')|; here the Taylor lemma is applied to the function ∂igk\partial_ig_k, which is C1C^1 on UU with second partial derivatives of gkg_k as its partial derivatives, all bounded by K0K_0. Finally ∂l+k′∂l+kF\partial_{l+k'}\partial_{l+k}F vanishes identically, so its increment is 0≤ε0\le\varepsilon. This is requirement 4 of a twice continuously differentiable extension.

The estimates just obtained show in particular that every second partial derivative of FF is continuous on U×VU\times V, so each first partial derivative of FF is a C1C^1 map there. Moreover each first partial derivative of FF is itself continuous: by Step 3(a), the triangle inequality, Cauchy-Schwarz and clause (i) of the Taylor lemma applied to gg and to each gkg_k (all with first partial derivatives bounded by K0K_0 on the convex set UU), together with (0a) and (0c),

∣∂iF(x)−∂iF(x′)∣≤l K0∣Σ−Σ′∣+m l K0∣Σ−Σ′∣(R+1)+m K0∣α−α′∣≤(l K0(1+m(R+1))+m K0)∣x−x′∣,|\partial_iF(x)-\partial_iF(x')|\le\sqrt{l}\,K_0|\Sigma-\Sigma'|+\sqrt{m}\,\sqrt{l}\,K_0|\Sigma-\Sigma'|(R+1)+\sqrt{m}\,K_0|\alpha-\alpha'|\le\Big(\sqrt{l}\,K_0\big(1+\sqrt{m}(R+1)\big)+\sqrt{m}\,K_0\Big)|x-x'| ,

and ∣∂l+kF(x)−∂l+kF(x′)∣=∣gk(Σ)−gk(Σ′)∣≤l K0∣x−x′∣|\partial_{l+k}F(x)-\partial_{l+k}F(x')|=|g_k(\Sigma)-g_k(\Sigma')|\le\sqrt{l}\,K_0|x-x'|. Since all partial derivatives of FF exist on the open set U×VU\times V and are continuous there, FF is a C1C^1 map on U×VU\times V; this is requirement 2.

Step 6. Conclusion (clause 3).

The set UU is open, convex and bounded with Δl⊂U\Delta^l\subset U by the rate-data definition, and VV is open, convex and bounded with A⊆V\mathcal{A}\subseteq V by Step 2. For (Σ,α)∈Δl×A(\Sigma,\alpha)\in\Delta^l\times\mathcal{A} the defining formulas for βˉ\bar{\beta} and for β\beta agree, since β0,β1\beta_0,\beta_1 are the restrictions of βˉ0,βˉ1\bar{\beta}_0,\bar{\beta}_1; this is requirement 1. Requirements 2, 3 and 4 were established in Steps 5, 4 and 5 respectively. Hence (U,V,βˉ)(U,V,\bar{\beta}) is a twice continuously differentiable extension of β\beta with derivative bound KK, which is clause 3.

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