Each result cited is universally quantified over the data in its own statement, and is applied to the data named here.
When a level N ≥ N 0 N\ge N_{0} N ≥ N 0 is fixed we abbreviate w ‾ 0 = w ‾ N , τ 0 \overline{w}^{0}=\overline{w}^{0}_{N,\tau} w 0 = w N , τ 0 , w ‾ 0 = w ‾ N , τ 0 \underline{w}^{0}=\underline{w}^{0}_{N,\tau} w 0 = w N , τ 0 , w ‾ = w ‾ N , τ \overline{w}=\overline{w}_{N,\tau} w = w N , τ , w ‾ = w ‾ N , τ \underline{w}=\underline{w}_{N,\tau} w = w N , τ , p 0 = p 0 , N p_{0}=p_{0,N} p 0 = p 0 , N and μ x = μ x N \mu_{x}=\mu^{N}_{x} μ x = μ x N . Two facts are used throughout. First, 0 ≤ ω g ( s ) ≤ 2 b g 0\le\omega_{g}(s)\le2b_{g} 0 ≤ ω g ( s ) ≤ 2 b g for s ≥ 0 s\ge0 s ≥ 0 : the set defining ω g ( s ) \omega_{g}(s) ω g ( s ) contains ∣ g ( μ ) − g ( μ ) ∣ = 0 |g(\mu)-g(\mu)|=0 ∣ g ( μ ) − g ( μ ) ∣ = 0 , and each of its elements is at most ∣ g ( μ ) ∣ + ∣ g ( ν ) ∣ ≤ 2 b g |g(\mu)|+|g(\nu)|\le2b_{g} ∣ g ( μ ) ∣ + ∣ g ( ν ) ∣ ≤ 2 b g by The N-Particle Dyson Game and its Mean-Field Limit: Standing Data and Equations §data . Second, every ν ∈ D \nu\in\mathcal{D} ν ∈ D is atomless: D \mathcal{D} D is contained in D log \mathcal{D}_{\log} D l o g by The Confined Logarithmic-Energy Pair on the Wasserstein Space of the Real Line §pair , and every element of D log \mathcal{D}_{\log} D l o g gives measure 0 0 0 to each one-point set by The Logarithmic Energy of a Probability Measure on the Real Line §energy , which is atomlessness . Since every point of W N W_{N} W N is ordered (as recorded in Quantile Blocks of an Atomless Measure on the Line: Block Maps, Distances to Ordered Empirical Measures, and the Block Test Function ), Quantile Blocks of an Atomless Measure on the Line: Block Maps, Distances to Ordered Empirical Measures, and the Block Test Function §optimal , applied with μ ^ = ν \hat{\mu}=\nu μ ^ = ν , gives for all N ≥ N 0 N\ge N_{0} N ≥ N 0 , x , y ∈ W N x,y\in W_{N} x , y ∈ W N and ν ∈ D \nu\in\mathcal{D} ν ∈ D
∥ x − y ∥ N = W 2 ( μ x , μ y ) ≤ W 2 ( μ x , ν ) + W 2 ( μ y , ν ) . (Q) \frac{\lVert x-y\rVert}{\sqrt{N}}=W_{2}(\mu_{x},\mu_{y})\le W_{2}(\mu_{x},\nu)+W_{2}(\mu_{y},\nu).\qquad\text{(Q)} N ∥ x − y ∥ = W 2 ( μ x , μ y ) ≤ W 2 ( μ x , ν ) + W 2 ( μ y , ν ) . (Q)
Step 1 (The hypotheses of the convolution lemma). Fix N ≥ N 0 N\ge N_{0} N ≥ N 0 . We check the hypotheses of Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty for the data listed in the statement. The set W N W_{N} W N is nonempty and open by The Logarithmic Energy on the Weyl Chamber: Derivatives, Monotone Gradient, the Calogero Identity and the Euler Identity §open . It is convex : for x , y ∈ W N x,y\in W_{N} x , y ∈ W N , 0 ≤ t ≤ 1 0\le t\le1 0 ≤ t ≤ 1 and i < j i<j i < j , ( t x i + ( 1 − t ) y i ) − ( t x j + ( 1 − t ) y j ) = t ( x i − x j ) + ( 1 − t ) ( y i − y j ) (tx_{i}+(1-t)y_{i})-(tx_{j}+(1-t)y_{j})=t(x_{i}-x_{j})+(1-t)(y_{i}-y_{j}) ( t x i + ( 1 − t ) y i ) − ( t x j + ( 1 − t ) y j ) = t ( x i − x j ) + ( 1 − t ) ( y i − y j ) is positive, because both differences are positive by The Weyl Chamber of Ordered Points in Euclidean Space and t , 1 − t t,1-t t , 1 − t are nonnegative with sum 1 1 1 . By The N-Particle Dyson Potential on the Weyl Chamber: Penalty, Monotone Gradient, Dissipation with Constants Uniform in N, and Gibbs Integrability §penalty , P N P_{N} P N is a penalty on W N W_{N} W N with monotone gradient and κ N \kappa_{N} κ N is positive; λ \lambda λ is positive and θ = 1 \theta=1 θ = 1 is nonnegative. The dissipation inequality with ε = ε 0 \varepsilon=\varepsilon_{0} ε = ε 0 and C = C 0 N C=C_{0}N C = C 0 N is The N-Particle Dyson Potential on the Weyl Chamber: Penalty, Monotone Gradient, Dissipation with Constants Uniform in N, and Gibbs Integrability §dissipation , where 0 < ε 0 < 1 0<\varepsilon_{0}<1 0 < ε 0 < 1 . Write G ( x ) = N g ( μ x ) G(x)=N\,g(\mu_{x}) G ( x ) = N g ( μ x ) . The function ρ ( s ) = N ω g ( s / N ) \rho(s)=N\,\omega_{g}(s/\sqrt{N}) ρ ( s ) = N ω g ( s / N ) maps [ 0 , ∞ ) [0,\infty) [ 0 , ∞ ) into [ 0 , ∞ ) [0,\infty) [ 0 , ∞ ) and is nondecreasing because ω g \omega_{g} ω g is. For x , y ∈ W N x,y\in W_{N} x , y ∈ W N , Basic Properties of Empirical Measures: Values, Integrals, Push-Forwards, Second Moment, and Lipschitz Dependence on the Configuration §lipschitz (in force with dimension 1 1 1 by N-Particle Systems on the Wasserstein Space: Particles, Configurations and the Configuration Level §particles ) gives N W 2 ( μ x , μ y ) 2 ≤ ∥ x − y ∥ 2 N\,W_{2}(\mu_{x},\mu_{y})^{2}\le\lVert x-y\rVert^{2} N W 2 ( μ x , μ y ) 2 ≤ ∥ x − y ∥ 2 , hence W 2 ( μ x , μ y ) ≤ ∥ x − y ∥ / N W_{2}(\mu_{x},\mu_{y})\le\lVert x-y\rVert/\sqrt{N} W 2 ( μ x , μ y ) ≤ ∥ x − y ∥ / N since both sides are nonnegative, and therefore
∣ G ( x ) − G ( y ) ∣ ≤ N ω g ( W 2 ( μ x , μ y ) ) ≤ N ω g ( ∥ x − y ∥ / N ) = ρ ( ∥ x − y ∥ ) . |G(x)-G(y)|\le N\,\omega_{g}\bigl(W_{2}(\mu_{x},\mu_{y})\bigr)\le N\,\omega_{g}\bigl(\lVert x-y\rVert/\sqrt{N}\bigr)=\rho\bigl(\lVert x-y\rVert\bigr). ∣ G ( x ) − G ( y ) ∣ ≤ N ω g ( W 2 ( μ x , μ y ) ) ≤ N ω g ( ∥ x − y ∥ / N ) = ρ ( ∥ x − y ∥ ) .
Further M = λ − 1 N b g ≥ 0 M=\lambda^{-1}Nb_{g}\ge0 M = λ − 1 N b g ≥ 0 , η = 1 N > 0 \eta=\frac{1}{N}>0 η = N 1 > 0 , τ > 0 \tau>0 τ > 0 , and θ η = 1 N ≤ ε 0 \theta\eta=\frac{1}{N}\le\varepsilon_{0} θ η = N 1 ≤ ε 0 because N ε 0 ≥ N 0 ε 0 ≥ 1 N\varepsilon_{0}\ge N_{0}\varepsilon_{0}\ge1 N ε 0 ≥ N 0 ε 0 ≥ 1 . The operator F F F of that lemma (control cost 1 1 1 , running cost G G G , potential P N P_{N} P N , discount λ \lambda λ , noise intensity κ N \kappa_{N} κ N ) is the operator F N F_{N} F N of The N-Particle Dyson Game and its Mean-Field Limit: Standing Data and Equations §particle-equation : by The N-Particle Dyson Hamilton-Jacobi Equation with a Mean-Field Running Cost §operator and The Dyson Hamilton-Jacobi Equation for N Controlled Particles in the Weyl Chamber §operator , F N F_{N} F N is the penalty-drift operator on W N W_{N} W N with these coefficients and with potential H b N + ∑ k V ( x k ) H_{b_{N}}+\sum_{k}V(x_{k}) H b N + ∑ k V ( x k ) , which is P N P_{N} P N by The N-Particle Dyson Potential on the Weyl Chamber: Penalty, Monotone Gradient, Dissipation with Constants Uniform in N, and Gibbs Integrability §hypotheses . By The N-Particle Dyson Game and its Mean-Field Limit: Standing Data and Equations §particle-equation and Well-Posedness of the Dyson Hamilton-Jacobi Equation in the Weyl Chamber below the Collision Threshold §well-posed , v N v_{N} v N is both a viscosity subsolution and a viscosity supersolution of F F F on W N W_{N} W N , with ∣ v N ( x ) ∣ ≤ M |v_{N}(x)|\le M ∣ v N ( x ) ∣ ≤ M . So Parts A and B apply with u = v = v N u=v=v_{N} u = v = v N .
The derived quantities of that lemma are those of the statement: p 0 p_{0} p 0 is the least value of P N P_{N} P N on W N W_{N} W N ; the lemma's r ( x ) r(x) r ( x ) has square 2 τ ( 2 λ − 1 N b g + 1 N ( P N ( x ) − p 0 ) ) = r N ( x ) 2 2\tau\bigl(2\lambda^{-1}Nb_{g}+\frac{1}{N}(P_{N}(x)-p_{0})\bigr)=r_{N}(x)^{2} 2 τ ( 2 λ − 1 N b g + N 1 ( P N ( x ) − p 0 ) ) = r N ( x ) 2 , so r = r N r=r_{N} r = r N ; θ 1 = 1 − 1 2 N ε 0 = θ 1 , N \theta_{1}=1-\frac{1}{2N\varepsilon_{0}}=\theta_{1,N} θ 1 = 1 − 2 N ε 0 1 = θ 1 , N and θ 2 = 1 + 1 N ε 0 = θ 2 , N \theta_{2}=1+\frac{1}{N\varepsilon_{0}}=\theta_{2,N} θ 2 = 1 + N ε 0 1 = θ 2 , N ; and g 1 ( x ) = G ( x ) + 1 N C 0 N + N ω g ( r N ( x ) / N ) = g N + ( x ) g_{1}(x)=G(x)+\frac{1}{N}C_{0}N+N\,\omega_{g}(r_{N}(x)/\sqrt{N})=g^{+}_{N}(x) g 1 ( x ) = G ( x ) + N 1 C 0 N + N ω g ( r N ( x ) / N ) = g N + ( x ) , likewise g 2 = g N − g_{2}=g^{-}_{N} g 2 = g N − . Thus F 1 F_{1} F 1 and F 2 F_{2} F 2 of the lemma are the two operators of clause (v). Since p 0 = P N ( x ∗ ) p_{0}=P_{N}(x_{*}) p 0 = P N ( x ∗ ) for some x ∗ ∈ W N x_{*}\in W_{N} x ∗ ∈ W N , The Discrete Dyson Energy per Particle: Bounds, Compactness with a Lower Limit, and Recovery Configurations with Separated Particles §bounds gives p 0 ≥ e ∗ N p_{0}\ge e_{*}N p 0 ≥ e ∗ N . Dividing r N ( y ) 2 r_{N}(y)^{2} r N ( y ) 2 by N N N ,
r N ( y ) 2 N = R τ 2 + 2 τ ( P N ( y ) − p 0 ) N 2 ( y ∈ W N ) . (R) \frac{r_{N}(y)^{2}}{N}=R_{\tau}^{2}+\frac{2\tau\bigl(P_{N}(y)-p_{0}\bigr)}{N^{2}}\qquad(y\in W_{N}).\qquad\text{(R)} N r N ( y ) 2 = R τ 2 + N 2 2 τ ( P N ( y ) − p 0 ) ( y ∈ W N ) . (R)
Step 2 (Clause 1). Fix N ≥ N 0 N\ge N_{0} N ≥ N 0 and x , y ∈ W N x,y\in W_{N} x , y ∈ W N .
(i) By Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §sub-bounds and p 0 ≥ e ∗ N p_{0}\ge e_{*}N p 0 ≥ e ∗ N , v N ( x ) − 1 N P N ( x ) ≤ w ‾ 0 ( x ) ≤ λ − 1 N b g − p 0 N ≤ λ − 1 N b g + ∣ e ∗ ∣ v_{N}(x)-\frac{1}{N}P_{N}(x)\le\overline{w}^{0}(x)\le\lambda^{-1}Nb_{g}-\frac{p_{0}}{N}\le\lambda^{-1}Nb_{g}+|e_{*}| v N ( x ) − N 1 P N ( x ) ≤ w 0 ( x ) ≤ λ − 1 N b g − N p 0 ≤ λ − 1 N b g + ∣ e ∗ ∣ . As − L N < 0 ≤ λ − 1 N b g + ∣ e ∗ ∣ -L_{N}<0\le\lambda^{-1}Nb_{g}+|e_{*}| − L N < 0 ≤ λ − 1 N b g + ∣ e ∗ ∣ and N ≥ 1 N\ge1 N ≥ 1 ,
− L N ≤ w ‾ ( x ) ≤ λ − 1 N b g + ∣ e ∗ ∣ ≤ N ( λ − 1 b g + ∣ e ∗ ∣ ) , v N ( x ) − 1 N P N ( x ) ≤ w ‾ ( x ) . (1a) -L_{N}\le\overline{w}(x)\le\lambda^{-1}Nb_{g}+|e_{*}|\le N(\lambda^{-1}b_{g}+|e_{*}|),\qquad v_{N}(x)-\tfrac{1}{N}P_{N}(x)\le\overline{w}(x).\qquad\text{(1a)} − L N ≤ w ( x ) ≤ λ − 1 N b g + ∣ e ∗ ∣ ≤ N ( λ − 1 b g + ∣ e ∗ ∣ ) , v N ( x ) − N 1 P N ( x ) ≤ w ( x ) . (1a)
By Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §inf-bounds , − λ − 1 N b g − ∣ e ∗ ∣ ≤ − M + p 0 N ≤ w ‾ 0 ( x ) ≤ v N ( x ) + 1 N P N ( x ) -\lambda^{-1}Nb_{g}-|e_{*}|\le-M+\frac{p_{0}}{N}\le\underline{w}^{0}(x)\le v_{N}(x)+\frac{1}{N}P_{N}(x) − λ − 1 N b g − ∣ e ∗ ∣ ≤ − M + N p 0 ≤ w 0 ( x ) ≤ v N ( x ) + N 1 P N ( x ) , and L N > 0 L_{N}>0 L N > 0 , so
− N ( λ − 1 b g + ∣ e ∗ ∣ ) ≤ − λ − 1 N b g − ∣ e ∗ ∣ ≤ w ‾ ( x ) ≤ L N , w ‾ ( x ) ≤ v N ( x ) + 1 N P N ( x ) . (1b) -N(\lambda^{-1}b_{g}+|e_{*}|)\le-\lambda^{-1}Nb_{g}-|e_{*}|\le\underline{w}(x)\le L_{N},\qquad\underline{w}(x)\le v_{N}(x)+\tfrac{1}{N}P_{N}(x).\qquad\text{(1b)} − N ( λ − 1 b g + ∣ e ∗ ∣ ) ≤ − λ − 1 N b g − ∣ e ∗ ∣ ≤ w ( x ) ≤ L N , w ( x ) ≤ v N ( x ) + N 1 P N ( x ) . (1b)
With c = λ − 1 b g + ∣ e ∗ ∣ + 1 c=\lambda^{-1}b_{g}+|e_{*}|+1 c = λ − 1 b g + ∣ e ∗ ∣ + 1 this gives − c ( N + ∣ P N ( x ) ∣ ) ≤ − c N ≤ − L N ≤ w ‾ ( x ) ≤ c N -c(N+|P_{N}(x)|)\le-cN\le-L_{N}\le\overline{w}(x)\le cN − c ( N + ∣ P N ( x ) ∣ ) ≤ − c N ≤ − L N ≤ w ( x ) ≤ c N and − c N ≤ w ‾ ( x ) ≤ L N ≤ c N ≤ c ( N + ∣ P N ( x ) ∣ ) -cN\le\underline{w}(x)\le L_{N}\le cN\le c(N+|P_{N}(x)|) − c N ≤ w ( x ) ≤ L N ≤ c N ≤ c ( N + ∣ P N ( x ) ∣ ) , the growth conditions of Upper and Lower Half-Relaxed Limits along Empirical Measures of Functions on the Weyl Chambers §upper and Upper and Lower Half-Relaxed Limits along Empirical Measures of Functions on the Weyl Chambers §lower ; so u ˉ τ \bar{u}_{\tau} u ˉ τ and u ‾ τ \underline{u}_{\tau} u τ are defined.
(ii) By Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §sub-semiconvex and Semiconvex Function on a Convex Subset of R n \mathbb{R}^n R n , h ( z ) = w ‾ 0 ( z ) + 1 2 τ ∥ z ∥ 2 h(z)=\overline{w}^{0}(z)+\frac{1}{2\tau}\lVert z\rVert^{2} h ( z ) = w 0 ( z ) + 2 τ 1 ∥ z ∥ 2 is convex on W N W_{N} W N . So is k ( z ) = − L N + 1 2 τ ∥ z ∥ 2 k(z)=-L_{N}+\frac{1}{2\tau}\lVert z\rVert^{2} k ( z ) = − L N + 2 τ 1 ∥ z ∥ 2 , because t ∥ a ∥ 2 + ( 1 − t ) ∥ b ∥ 2 − ∥ t a + ( 1 − t ) b ∥ 2 = t ( 1 − t ) ∥ a − b ∥ 2 ≥ 0 t\lVert a\rVert^{2}+(1-t)\lVert b\rVert^{2}-\lVert ta+(1-t)b\rVert^{2}=t(1-t)\lVert a-b\rVert^{2}\ge0 t ∥ a ∥ 2 + ( 1 − t ) ∥ b ∥ 2 − ∥ t a + ( 1 − t ) b ∥ 2 = t ( 1 − t ) ∥ a − b ∥ 2 ≥ 0 for 0 ≤ t ≤ 1 0\le t\le1 0 ≤ t ≤ 1 . For a , b ∈ W N a,b\in W_{N} a , b ∈ W N , 0 ≤ t ≤ 1 0\le t\le1 0 ≤ t ≤ 1 and z = t a + ( 1 − t ) b z=ta+(1-t)b z = t a + ( 1 − t ) b ,
max ( h ( z ) , k ( z ) ) ≤ max ( t h ( a ) + ( 1 − t ) h ( b ) , t k ( a ) + ( 1 − t ) k ( b ) ) ≤ t max ( h ( a ) , k ( a ) ) + ( 1 − t ) max ( h ( b ) , k ( b ) ) , \max(h(z),k(z))\le\max\bigl(th(a)+(1-t)h(b),\,tk(a)+(1-t)k(b)\bigr)\le t\max(h(a),k(a))+(1-t)\max(h(b),k(b)), max ( h ( z ) , k ( z )) ≤ max ( t h ( a ) + ( 1 − t ) h ( b ) , t k ( a ) + ( 1 − t ) k ( b ) ) ≤ t max ( h ( a ) , k ( a )) + ( 1 − t ) max ( h ( b ) , k ( b )) ,
so max ( h , k ) = w ‾ + 1 2 τ ∥ ⋅ ∥ 2 \max(h,k)=\overline{w}+\frac{1}{2\tau}\lVert\cdot\rVert^{2} max ( h , k ) = w + 2 τ 1 ∥ ⋅ ∥ 2 is convex, that is, w ‾ \overline{w} w is semiconvex on W N W_{N} W N with constant τ − 1 \tau^{-1} τ − 1 . By The Maximum of Two Upper Semicontinuous Functions §duality , − w ‾ = max ( − w ‾ 0 , − L N ) -\underline{w}=\max(-\underline{w}^{0},-L_{N}) − w = max ( − w 0 , − L N ) pointwise, and − w ‾ 0 -\underline{w}^{0} − w 0 is semiconvex with constant τ − 1 \tau^{-1} τ − 1 by Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §inf-semiconcave ; the same argument applies.
(iii) Let w ‾ \overline{w} w be differentiable at x x x . By claim 1 of A Derivative Matrix is the Jacobian Matrix, and is Unique all partial derivatives of w ‾ \overline{w} w exist at x x x , and D w ‾ ( x ) D\overline{w}(x) D w ( x ) is the vector of them (Gradient of a Real-Valued Function on a Euclidean Open Set ). If w ‾ 0 ( x ) > − L N \overline{w}^{0}(x)>-L_{N} w 0 ( x ) > − L N : w ‾ 0 \overline{w}^{0} w 0 is semiconvex on the open convex set W N W_{N} W N by Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §sub-semiconvex , hence continuous by Local Lipschitz Bound and Continuity for a Semiconvex Function on an Open Convex Set §continuity (with S = W N S=W_{N} S = W N ); so there is δ > 0 \delta>0 δ > 0 such that every z z z with ∥ z − x ∥ < δ \lVert z-x\rVert<\delta ∥ z − x ∥ < δ lies in W N W_{N} W N and satisfies w ‾ 0 ( z ) > − L N \overline{w}^{0}(z)>-L_{N} w 0 ( z ) > − L N , hence w ‾ ( z ) = w ‾ 0 ( z ) \overline{w}(z)=\overline{w}^{0}(z) w ( z ) = w 0 ( z ) . For 0 < ∣ s ∣ < δ 0<|s|<\delta 0 < ∣ s ∣ < δ the difference quotients of w ‾ \overline{w} w and w ‾ 0 \overline{w}^{0} w 0 at x x x in each coordinate direction coincide, so the partial derivatives of w ‾ 0 \overline{w}^{0} w 0 exist at x x x and equal those of w ‾ \overline{w} w , and Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §sub-gradient gives ∥ D w ‾ ( x ) ∥ = ∥ D w ‾ 0 ( x ) ∥ ≤ τ − 1 r N ( x ) \lVert D\overline{w}(x)\rVert=\lVert D\overline{w}^{0}(x)\rVert\le\tau^{-1}r_{N}(x) ∥ D w ( x )∥ = ∥ D w 0 ( x )∥ ≤ τ − 1 r N ( x ) . If w ‾ 0 ( x ) ≤ − L N \overline{w}^{0}(x)\le-L_{N} w 0 ( x ) ≤ − L N : then w ‾ ( x ) = − L N ≤ w ‾ ( z ) \overline{w}(x)=-L_{N}\le\overline{w}(z) w ( x ) = − L N ≤ w ( z ) for all z ∈ W N z\in W_{N} z ∈ W N by (1a), so for each i i i the quotients ( w ‾ ( x + s e i ) − w ‾ ( x ) ) / s (\overline{w}(x+se_{i})-\overline{w}(x))/s ( w ( x + s e i ) − w ( x )) / s are nonnegative for small s > 0 s>0 s > 0 and nonpositive for small s < 0 s<0 s < 0 ; their limit ∂ i w ‾ ( x ) \partial_{i}\overline{w}(x) ∂ i w ( x ) is 0 0 0 , and ∥ D w ‾ ( x ) ∥ = 0 ≤ τ − 1 r N ( x ) \lVert D\overline{w}(x)\rVert=0\le\tau^{-1}r_{N}(x) ∥ D w ( x )∥ = 0 ≤ τ − 1 r N ( x ) . For w ‾ \underline{w} w the argument is the same with Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §inf-gradient , the continuity of w ‾ 0 \underline{w}^{0} w 0 following from that of the semiconvex function − w ‾ 0 -\underline{w}^{0} − w 0 , and in the case w ‾ 0 ( x ) ≥ L N \underline{w}^{0}(x)\ge L_{N} w 0 ( x ) ≥ L N the point x x x being a maximum point of w ‾ \underline{w} w by (1b).
(iv) Let Δ = 1 2 τ ∥ x − y ∥ ( 3 ∥ x − y ∥ + 2 r N ( y ) ) ≥ 0 \Delta=\frac{1}{2\tau}\lVert x-y\rVert(3\lVert x-y\rVert+2r_{N}(y))\ge0 Δ = 2 τ 1 ∥ x − y ∥ ( 3 ∥ x − y ∥ + 2 r N ( y )) ≥ 0 . By Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §sub-transfer , w ‾ ( x ) = max ( w ‾ 0 ( x ) , − L N ) ≤ max ( w ‾ 0 ( y ) + Δ , − L N + Δ ) = w ‾ ( y ) + Δ \overline{w}(x)=\max(\overline{w}^{0}(x),-L_{N})\le\max(\overline{w}^{0}(y)+\Delta,-L_{N}+\Delta)=\overline{w}(y)+\Delta w ( x ) = max ( w 0 ( x ) , − L N ) ≤ max ( w 0 ( y ) + Δ , − L N + Δ ) = w ( y ) + Δ . By Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §inf-transfer , w ‾ ( x ) ≥ min ( w ‾ 0 ( y ) − Δ , L N − Δ ) = w ‾ ( y ) − Δ \underline{w}(x)\ge\min(\underline{w}^{0}(y)-\Delta,L_{N}-\Delta)=\underline{w}(y)-\Delta w ( x ) ≥ min ( w 0 ( y ) − Δ , L N − Δ ) = w ( y ) − Δ .
(v) The function w ‾ 0 \overline{w}^{0} w 0 is upper semicontinuous on W N W_{N} W N , being a viscosity subsolution of F 1 F_{1} F 1 by Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §subsolution (see Viscosity Subsolution and Supersolution of a Second-Order Equation ); the constant − L N -L_{N} − L N is upper semicontinuous ; so w ‾ \overline{w} w is upper semicontinuous by The Maximum of Two Upper Semicontinuous Functions §max-usc . Let φ : W N → R \varphi:W_{N}\to\mathbb{R} φ : W N → R be of class C 2 C^{2} C 2 and let w ‾ − φ \overline{w}-\varphi w − φ have a local maximum at x x x relative to W N W_{N} W N : there is δ > 0 \delta>0 δ > 0 with w ‾ ( z ) − φ ( z ) ≤ w ‾ ( x ) − φ ( x ) \overline{w}(z)-\varphi(z)\le\overline{w}(x)-\varphi(x) w ( z ) − φ ( z ) ≤ w ( x ) − φ ( x ) for z ∈ W N z\in W_{N} z ∈ W N , ∥ z − x ∥ < δ \lVert z-x\rVert<\delta ∥ z − x ∥ < δ . If w ‾ 0 ( x ) ≥ − L N \overline{w}^{0}(x)\ge-L_{N} w 0 ( x ) ≥ − L N , then w ‾ ( x ) = w ‾ 0 ( x ) \overline{w}(x)=\overline{w}^{0}(x) w ( x ) = w 0 ( x ) and for such z z z , w ‾ 0 ( z ) − φ ( z ) ≤ w ‾ ( z ) − φ ( z ) ≤ w ‾ 0 ( x ) − φ ( x ) \overline{w}^{0}(z)-\varphi(z)\le\overline{w}(z)-\varphi(z)\le\overline{w}^{0}(x)-\varphi(x) w 0 ( z ) − φ ( z ) ≤ w ( z ) − φ ( z ) ≤ w 0 ( x ) − φ ( x ) ; so w ‾ 0 − φ \overline{w}^{0}-\varphi w 0 − φ has a local maximum at x x x and Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §subsolution gives F 1 ( x , w ‾ ( x ) , D φ ( x ) , D 2 φ ( x ) ) ≤ 0 F_{1}(x,\overline{w}(x),D\varphi(x),D^{2}\varphi(x))\le0 F 1 ( x , w ( x ) , D φ ( x ) , D 2 φ ( x )) ≤ 0 . If w ‾ 0 ( x ) < − L N \overline{w}^{0}(x)<-L_{N} w 0 ( x ) < − L N , then w ‾ ( x ) = − L N \overline{w}(x)=-L_{N} w ( x ) = − L N and for such z z z , − L N − φ ( z ) ≤ w ‾ ( z ) − φ ( z ) ≤ − L N − φ ( x ) -L_{N}-\varphi(z)\le\overline{w}(z)-\varphi(z)\le-L_{N}-\varphi(x) − L N − φ ( z ) ≤ w ( z ) − φ ( z ) ≤ − L N − φ ( x ) ; so φ \varphi φ has a local minimum at x x x relative to the open set W N W_{N} W N , and claim 2 of First- and Second-Order Conditions at a Local Extremum of a Function of Class C 2 C^2 C 2 gives D φ ( x ) = 0 D\varphi(x)=0 D φ ( x ) = 0 and 0 ⪯ D 2 φ ( x ) 0\preceq D^{2}\varphi(x) 0 ⪯ D 2 φ ( x ) . Then D 2 φ ( x ) D^{2}\varphi(x) D 2 φ ( x ) is positive semidefinite by The Positive Semidefinite Ordering Compared by Differences , so its diagonal entries e i ⋅ D 2 φ ( x ) e i e_{i}\cdot D^{2}\varphi(x)e_{i} e i ⋅ D 2 φ ( x ) e i , and hence its trace, are nonnegative. Since g N + ( x ) ≥ − N b g g^{+}_{N}(x)\ge-Nb_{g} g N + ( x ) ≥ − N b g (as ∣ g ∣ ≤ b g |g|\le b_{g} ∣ g ∣ ≤ b g , C 0 ≥ 0 C_{0}\ge0 C 0 ≥ 0 , ω g ≥ 0 \omega_{g}\ge0 ω g ≥ 0 ) and κ N ≥ 0 \kappa_{N}\ge0 κ N ≥ 0 , the formula of The Penalty-Drift Hamilton-Jacobi Equation on an Open Subset of Euclidean Space §operator gives
F 1 ( x , − L N , 0 , D 2 φ ( x ) ) = − λ L N − κ N 2 tr ( D 2 φ ( x ) ) − g N + ( x ) ≤ − λ L N + N b g = − λ N < 0. F_{1}(x,-L_{N},0,D^{2}\varphi(x))=-\lambda L_{N}-\tfrac{\kappa_{N}}{2}\operatorname{tr}\bigl(D^{2}\varphi(x)\bigr)-g^{+}_{N}(x)\le-\lambda L_{N}+Nb_{g}=-\lambda N<0. F 1 ( x , − L N , 0 , D 2 φ ( x )) = − λ L N − 2 κ N tr ( D 2 φ ( x ) ) − g N + ( x ) ≤ − λ L N + N b g = − λ N < 0.
Hence w ‾ \overline{w} w is a viscosity subsolution of F 1 F_{1} F 1 on W N W_{N} W N . Symmetrically, w ‾ 0 \underline{w}^{0} w 0 is lower semicontinuous by Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §supersolution , so w ‾ \underline{w} w is lower semicontinuous by The Maximum of Two Upper Semicontinuous Functions §min-lsc ; if w ‾ − φ \underline{w}-\varphi w − φ has a local minimum at x x x relative to W N W_{N} W N , then either w ‾ 0 ( x ) ≤ L N \underline{w}^{0}(x)\le L_{N} w 0 ( x ) ≤ L N , w ‾ 0 − φ \underline{w}^{0}-\varphi w 0 − φ has a local minimum at x x x and Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty §supersolution gives F 2 ( x , w ‾ ( x ) , D φ ( x ) , D 2 φ ( x ) ) ≥ 0 F_{2}(x,\underline{w}(x),D\varphi(x),D^{2}\varphi(x))\ge0 F 2 ( x , w ( x ) , D φ ( x ) , D 2 φ ( x )) ≥ 0 , or w ‾ 0 ( x ) > L N \underline{w}^{0}(x)>L_{N} w 0 ( x ) > L N , φ \varphi φ has a local maximum at x x x , claim 1 of First- and Second-Order Conditions at a Local Extremum of a Function of Class C 2 C^2 C 2 gives D φ ( x ) = 0 D\varphi(x)=0 D φ ( x ) = 0 and D 2 φ ( x ) ⪯ 0 D^{2}\varphi(x)\preceq0 D 2 φ ( x ) ⪯ 0 , so tr ( D 2 φ ( x ) ) ≤ 0 \operatorname{tr}(D^{2}\varphi(x))\le0 tr ( D 2 φ ( x )) ≤ 0 , and with g N − ( x ) ≤ N b g g^{-}_{N}(x)\le Nb_{g} g N − ( x ) ≤ N b g
F 2 ( x , L N , 0 , D 2 φ ( x ) ) ≥ λ L N − N b g = λ N > 0. F_{2}(x,L_{N},0,D^{2}\varphi(x))\ge\lambda L_{N}-Nb_{g}=\lambda N>0. F 2 ( x , L N , 0 , D 2 φ ( x )) ≥ λ L N − N b g = λ N > 0.
The functions g N ± g^{\pm}_{N} g N ± are bounded: ∣ g N ± ( x ) ∣ ≤ N b g + C 0 + 2 N b g |g^{\pm}_{N}(x)|\le Nb_{g}+C_{0}+2Nb_{g} ∣ g N ± ( x ) ∣ ≤ N b g + C 0 + 2 N b g . They are Borel, that is, measurable with respect to the Borel σ \sigma σ -algebra B ( W N ) \mathcal{B}(W_{N}) B ( W N ) of the metric subspace W N W_{N} W N of R N \mathbb{R}^{N} R N and B ( R ) \mathcal{B}(\mathbb{R}) B ( R ) . Indeed, G 1 ( x ) = G ( x ) ± C 0 G_{1}(x)=G(x)\pm C_{0} G 1 ( x ) = G ( x ) ± C 0 is continuous on W N W_{N} W N by Running Costs for N-Particle Systems: Integrals of Bounded Uniformly Continuous Functions and Costs of the Empirical Measure §empirical , and P N P_{N} P N is continuous on W N W_{N} W N (as recorded in Sup- and Inf-Convolutions of Bounded Viscosity Sub- and Supersolutions of the Penalty-Drift Equation with a Convex Penalty ); both are therefore measurable by claims 3 and 2 of Borel Measurability and Bounded Integration on a Metric Space . Let T ( p ) = N ω g ( ( 2 τ ( 2 λ − 1 N b g + ( p − p 0 ) / N ) ) 1 / 2 / N ) T(p)=N\,\omega_{g}\bigl((2\tau(2\lambda^{-1}Nb_{g}+(p-p_{0})/N))^{1/2}/\sqrt{N}\bigr) T ( p ) = N ω g ( ( 2 τ ( 2 λ − 1 N b g + ( p − p 0 ) / N ) ) 1/2 / N ) for p ≥ p 0 p\ge p_{0} p ≥ p 0 and T ( p ) = 0 T(p)=0 T ( p ) = 0 for p < p 0 p<p_{0} p < p 0 ; then T ( P N ( x ) ) = N ω g ( r N ( x ) / N ) T(P_{N}(x))=N\,\omega_{g}(r_{N}(x)/\sqrt{N}) T ( P N ( x )) = N ω g ( r N ( x ) / N ) . On the closed set E = [ p 0 , ∞ ) E=[p_{0},\infty) E = [ p 0 , ∞ ) , which lies in B ( R ) \mathcal{B}(\mathbb{R}) B ( R ) by claims 4 and 5 of The Borel Sigma-Algebra of a Euclidean Space as a Product, and Measurability of Projections, Sequentially Continuous Maps, and Open and Closed Sets , T T T is nondecreasing (the radicand is nondecreasing in p p p , square roots of nonnegative numbers preserve order, and ω g \omega_{g} ω g is nondecreasing), so T T T is measurable by A Function Nondecreasing on a Borel Subset of the Real Line and Vanishing Outside It is Borel §borel , and G 2 = T ∘ P N G_{2}=T\circ P_{N} G 2 = T ∘ P N is measurable since G 2 − 1 ( B ) = P N − 1 ( T − 1 ( B ) ) G_{2}^{-1}(B)=P_{N}^{-1}(T^{-1}(B)) G 2 − 1 ( B ) = P N − 1 ( T − 1 ( B )) . By claims 2 and 5 of The Borel Sigma-Algebra of a Euclidean Space as a Product, and Measurability of Projections, Sequentially Continuous Maps, and Open and Closed Sets , x ↦ ( G 1 ( x ) , ± G 2 ( x ) ) x\mapsto(G_{1}(x),\pm G_{2}(x)) x ↦ ( G 1 ( x ) , ± G 2 ( x )) is measurable into B ( R 2 ) \mathcal{B}(\mathbb{R}^{2}) B ( R 2 ) (the map s ↦ − s s\mapsto-s s ↦ − s being continuous, − G 2 -G_{2} − G 2 is measurable in the same way), and the addition map R 2 → R \mathbb{R}^{2}\to\mathbb{R} R 2 → R , being continuous, is measurable by claim 3(a) of that lemma; composing as before, g N ± = G 1 ± G 2 g^{\pm}_{N}=G_{1}\pm G_{2} g N ± = G 1 ± G 2 is measurable.
Step 3 (Clause 2). Two general remarks. For ν ∈ D \nu\in\mathcal{D} ν ∈ D , positive ρ ≤ ρ ′ \rho\le\rho' ρ ≤ ρ ′ and N 1 ≥ N 1 ′ ≥ N 0 N_{1}\ge N_{1}'\ge N_{0} N 1 ≥ N 1 ′ ≥ N 0 , the sets of Upper and Lower Half-Relaxed Limits along Empirical Measures of Functions on the Weyl Chambers satisfy S ( ν , ρ , N 1 ) ⊆ S ( ν , ρ ′ , N 1 ′ ) S(\nu,\rho,N_{1})\subseteq S(\nu,\rho',N_{1}') S ( ν , ρ , N 1 ) ⊆ S ( ν , ρ ′ , N 1 ′ ) , so
s + ( ν , ρ , N 1 ) ≤ s + ( ν , ρ ′ , N 1 ′ ) , s − ( ν , ρ , N 1 ) ≥ s − ( ν , ρ ′ , N 1 ′ ) . (M) s^{+}(\nu,\rho,N_{1})\le s^{+}(\nu,\rho',N_{1}'),\qquad s^{-}(\nu,\rho,N_{1})\ge s^{-}(\nu,\rho',N_{1}').\qquad\text{(M)} s + ( ν , ρ , N 1 ) ≤ s + ( ν , ρ ′ , N 1 ′ ) , s − ( ν , ρ , N 1 ) ≥ s − ( ν , ρ ′ , N 1 ′ ) . (M)
For ν ∈ D \nu\in\mathcal{D} ν ∈ D and positive ρ \rho ρ let N ′ ( ν , ρ ) N'(\nu,\rho) N ′ ( ν , ρ ) be the natural number N 1 N_{1} N 1 given by The Discrete Dyson Energy per Particle: Bounds, Compactness with a Lower Limit, and Recovery Configurations with Separated Particles §recovery for ν \nu ν and ε = min ( ρ , 1 ) \varepsilon=\min(\rho,1) ε = min ( ρ , 1 ) : for every N ≥ N ′ ( ν , ρ ) N\ge N'(\nu,\rho) N ≥ N ′ ( ν , ρ ) there is y ∈ W N y\in W_{N} y ∈ W N with
W 2 ( μ y N , ν ) < ρ , P N ( y ) ≤ N ( E ( ν ) + min ( ρ , 1 ) ) ≤ N ( ∣ E ( ν ) ∣ + 1 ) . (Rec) W_{2}(\mu^{N}_{y},\nu)<\rho,\qquad P_{N}(y)\le N\bigl(\mathcal{E}(\nu)+\min(\rho,1)\bigr)\le N\bigl(|\mathcal{E}(\nu)|+1\bigr).\qquad\text{(Rec)} W 2 ( μ y N , ν ) < ρ , P N ( y ) ≤ N ( E ( ν ) + min ( ρ , 1 ) ) ≤ N ( ∣ E ( ν ) ∣ + 1 ) . (Rec)
Let μ ∈ D \mu\in\mathcal{D} μ ∈ D , ρ > 0 \rho>0 ρ > 0 and N 1 ≥ N 0 N_{1}\ge N_{0} N 1 ≥ N 0 . Every element w ‾ N , τ ( x ) / N \overline{w}_{N,\tau}(x)/N w N , τ ( x ) / N of the set S ( μ , ρ , N 1 ) S(\mu,\rho,N_{1}) S ( μ , ρ , N 1 ) formed with f N = w ‾ N , τ f_{N}=\overline{w}_{N,\tau} f N = w N , τ satisfies, by (1a), w ‾ N , τ ( x ) / N ≤ λ − 1 b g + ∣ e ∗ ∣ / N ≤ λ − 1 b g + ∣ e ∗ ∣ / N 1 \overline{w}_{N,\tau}(x)/N\le\lambda^{-1}b_{g}+|e_{*}|/N\le\lambda^{-1}b_{g}+|e_{*}|/N_{1} w N , τ ( x ) / N ≤ λ − 1 b g + ∣ e ∗ ∣/ N ≤ λ − 1 b g + ∣ e ∗ ∣/ N 1 ; so u ˉ τ ( μ ) ≤ s + ( μ , ρ , N 1 ) ≤ λ − 1 b g + ∣ e ∗ ∣ / N 1 \bar{u}_{\tau}(\mu)\le s^{+}(\mu,\rho,N_{1})\le\lambda^{-1}b_{g}+|e_{*}|/N_{1} u ˉ τ ( μ ) ≤ s + ( μ , ρ , N 1 ) ≤ λ − 1 b g + ∣ e ∗ ∣/ N 1 for every N 1 ≥ N 0 N_{1}\ge N_{0} N 1 ≥ N 0 , whence u ˉ τ ( μ ) ≤ λ − 1 b g \bar{u}_{\tau}(\mu)\le\lambda^{-1}b_{g} u ˉ τ ( μ ) ≤ λ − 1 b g . Next, for N ≥ max ( N 1 , N ′ ( μ , ρ ) ) N\ge\max(N_{1},N'(\mu,\rho)) N ≥ max ( N 1 , N ′ ( μ , ρ )) take y y y as in (Rec) for ν = μ \nu=\mu ν = μ ; then w ‾ N , τ ( y ) / N ∈ S ( μ , ρ , N 1 ) \overline{w}_{N,\tau}(y)/N\in S(\mu,\rho,N_{1}) w N , τ ( y ) / N ∈ S ( μ , ρ , N 1 ) and, by (1a) and ∣ v N ∣ ≤ λ − 1 N b g |v_{N}|\le\lambda^{-1}Nb_{g} ∣ v N ∣ ≤ λ − 1 N b g (The N-Particle Dyson Game and its Mean-Field Limit: Standing Data and Equations §particle-equation ),
w ‾ N , τ ( y ) N ≥ v N ( y ) N − P N ( y ) N 2 ≥ − λ − 1 b g − ∣ E ( μ ) ∣ + 1 N . \frac{\overline{w}_{N,\tau}(y)}{N}\ge\frac{v_{N}(y)}{N}-\frac{P_{N}(y)}{N^{2}}\ge-\lambda^{-1}b_{g}-\frac{|\mathcal{E}(\mu)|+1}{N}. N w N , τ ( y ) ≥ N v N ( y ) − N 2 P N ( y ) ≥ − λ − 1 b g − N ∣ E ( μ ) ∣ + 1 .
As N N N is arbitrarily large, s + ( μ , ρ , N 1 ) ≥ − λ − 1 b g s^{+}(\mu,\rho,N_{1})\ge-\lambda^{-1}b_{g} s + ( μ , ρ , N 1 ) ≥ − λ − 1 b g , and taking the greatest lower bound, u ˉ τ ( μ ) ≥ − λ − 1 b g \bar{u}_{\tau}(\mu)\ge-\lambda^{-1}b_{g} u ˉ τ ( μ ) ≥ − λ − 1 b g . For f N = w ‾ N , τ f_{N}=\underline{w}_{N,\tau} f N = w N , τ , (1b) gives s − ( μ , ρ , N 1 ) ≥ − λ − 1 b g − ∣ e ∗ ∣ / N 1 s^{-}(\mu,\rho,N_{1})\ge-\lambda^{-1}b_{g}-|e_{*}|/N_{1} s − ( μ , ρ , N 1 ) ≥ − λ − 1 b g − ∣ e ∗ ∣/ N 1 , hence u ‾ τ ( μ ) ≥ − λ − 1 b g \underline{u}_{\tau}(\mu)\ge-\lambda^{-1}b_{g} u τ ( μ ) ≥ − λ − 1 b g as N 1 N_{1} N 1 is arbitrary; and with y y y as above, w ‾ N , τ ( y ) / N ≤ v N ( y ) / N + P N ( y ) / N 2 ≤ λ − 1 b g + ( ∣ E ( μ ) ∣ + 1 ) / N \underline{w}_{N,\tau}(y)/N\le v_{N}(y)/N+P_{N}(y)/N^{2}\le\lambda^{-1}b_{g}+(|\mathcal{E}(\mu)|+1)/N w N , τ ( y ) / N ≤ v N ( y ) / N + P N ( y ) / N 2 ≤ λ − 1 b g + ( ∣ E ( μ ) ∣ + 1 ) / N for all N ≥ max ( N 1 , N ′ ( μ , ρ ) ) N\ge\max(N_{1},N'(\mu,\rho)) N ≥ max ( N 1 , N ′ ( μ , ρ )) , so s − ( μ , ρ , N 1 ) ≤ λ − 1 b g s^{-}(\mu,\rho,N_{1})\le\lambda^{-1}b_{g} s − ( μ , ρ , N 1 ) ≤ λ − 1 b g and u ‾ τ ( μ ) ≤ λ − 1 b g \underline{u}_{\tau}(\mu)\le\lambda^{-1}b_{g} u τ ( μ ) ≤ λ − 1 b g .
Step 4 (Transfer at a level). Let N ≥ N 0 N\ge N_{0} N ≥ N 0 and x , y ∈ W N x,y\in W_{N} x , y ∈ W N , and put d = ∥ x − y ∥ / N d=\lVert x-y\rVert/\sqrt{N} d = ∥ x − y ∥ / N and Φ ( d , R ) = 1 2 τ d ( 3 d + 2 R ) \Phi(d,R)=\frac{1}{2\tau}d(3d+2R) Φ ( d , R ) = 2 τ 1 d ( 3 d + 2 R ) , which is nondecreasing in each of d ≥ 0 d\ge0 d ≥ 0 and R ≥ 0 R\ge0 R ≥ 0 . Dividing clause (iv) by N N N ,
w ‾ N , τ ( x ) N ≤ w ‾ N , τ ( y ) N + Φ ( d , r N ( y ) N ) , w ‾ N , τ ( x ) N ≥ w ‾ N , τ ( y ) N − Φ ( d , r N ( y ) N ) . (T) \frac{\overline{w}_{N,\tau}(x)}{N}\le\frac{\overline{w}_{N,\tau}(y)}{N}+\Phi\Bigl(d,\frac{r_{N}(y)}{\sqrt{N}}\Bigr),\qquad\frac{\underline{w}_{N,\tau}(x)}{N}\ge\frac{\underline{w}_{N,\tau}(y)}{N}-\Phi\Bigl(d,\frac{r_{N}(y)}{\sqrt{N}}\Bigr).\qquad\text{(T)} N w N , τ ( x ) ≤ N w N , τ ( y ) + Φ ( d , N r N ( y ) ) , N w N , τ ( x ) ≥ N w N , τ ( y ) − Φ ( d , N r N ( y ) ) . (T)
If P N ( y ) ≤ c ′ N P_{N}(y)\le c'N P N ( y ) ≤ c ′ N for a real c ′ c' c ′ , then ( P N ( y ) − p 0 ) / N 2 ≤ ( ∣ c ′ ∣ + ∣ e ∗ ∣ ) / N (P_{N}(y)-p_{0})/N^{2}\le(|c'|+|e_{*}|)/N ( P N ( y ) − p 0 ) / N 2 ≤ ( ∣ c ′ ∣ + ∣ e ∗ ∣ ) / N since p 0 ≥ e ∗ N p_{0}\ge e_{*}N p 0 ≥ e ∗ N , so by (R) and monotonicity of square roots
r N ( y ) N ≤ ( R τ 2 + 2 τ ( ∣ c ′ ∣ + ∣ e ∗ ∣ ) N ) 1 / 2 . (B) \frac{r_{N}(y)}{\sqrt{N}}\le\Bigl(R_{\tau}^{2}+\frac{2\tau(|c'|+|e_{*}|)}{N}\Bigr)^{1/2}.\qquad\text{(B)} N r N ( y ) ≤ ( R τ 2 + N 2 τ ( ∣ c ′ ∣ + ∣ e ∗ ∣ ) ) 1/2 . (B)
Step 5 (Clause 3). Let μ , μ ′ ∈ D \mu,\mu'\in\mathcal{D} μ , μ ′ ∈ D , W = W 2 ( μ , μ ′ ) W=W_{2}(\mu,\mu') W = W 2 ( μ , μ ′ ) and K ′ = ∣ E ( μ ′ ) ∣ + 1 + ∣ e ∗ ∣ K'=|\mathcal{E}(\mu')|+1+|e_{*}| K ′ = ∣ E ( μ ′ ) ∣ + 1 + ∣ e ∗ ∣ . The choices are made in the order θ ′ \theta' θ ′ , ρ \rho ρ , N 1 N_{1} N 1 . Let θ ′ > 0 \theta'>0 θ ′ > 0 . As u ˉ τ ( μ ′ ) \bar{u}_{\tau}(\mu') u ˉ τ ( μ ′ ) is a greatest lower bound, there are ρ 0 > 0 \rho_{0}>0 ρ 0 > 0 and N 1 0 ≥ N 0 N_{1}^{0}\ge N_{0} N 1 0 ≥ N 0 with s + ( μ ′ , ρ 0 , N 1 0 ) ≤ u ˉ τ ( μ ′ ) + θ ′ s^{+}(\mu',\rho_{0},N_{1}^{0})\le\bar{u}_{\tau}(\mu')+\theta' s + ( μ ′ , ρ 0 , N 1 0 ) ≤ u ˉ τ ( μ ′ ) + θ ′ . Let 0 < ρ ≤ min ( ρ 0 , 1 ) 0<\rho\le\min(\rho_{0},1) 0 < ρ ≤ min ( ρ 0 , 1 ) , and let N 1 ≥ max ( N 1 0 , N ′ ( μ ′ , ρ ) ) N_{1}\ge\max(N_{1}^{0},N'(\mu',\rho)) N 1 ≥ max ( N 1 0 , N ′ ( μ ′ , ρ )) . Since u ˉ τ ( μ ) ≤ s + ( μ , ρ , N 1 ) \bar{u}_{\tau}(\mu)\le s^{+}(\mu,\rho,N_{1}) u ˉ τ ( μ ) ≤ s + ( μ , ρ , N 1 ) , which is a least upper bound, there are N ≥ N 1 N\ge N_{1} N ≥ N 1 and x ∈ W N x\in W_{N} x ∈ W N with W 2 ( μ x , μ ) < ρ W_{2}(\mu_{x},\mu)<\rho W 2 ( μ x , μ ) < ρ and w ‾ N , τ ( x ) / N > u ˉ τ ( μ ) − ρ \overline{w}_{N,\tau}(x)/N>\bar{u}_{\tau}(\mu)-\rho w N , τ ( x ) / N > u ˉ τ ( μ ) − ρ . By (Rec) for ν = μ ′ \nu=\mu' ν = μ ′ at this level N ≥ N ′ ( μ ′ , ρ ) N\ge N'(\mu',\rho) N ≥ N ′ ( μ ′ , ρ ) there is y ∈ W N y\in W_{N} y ∈ W N with W 2 ( μ y , μ ′ ) < ρ W_{2}(\mu_{y},\mu')<\rho W 2 ( μ y , μ ′ ) < ρ and P N ( y ) ≤ N ( ∣ E ( μ ′ ) ∣ + 1 ) P_{N}(y)\le N(|\mathcal{E}(\mu')|+1) P N ( y ) ≤ N ( ∣ E ( μ ′ ) ∣ + 1 ) . Then w ‾ N , τ ( y ) / N ∈ S ( μ ′ , ρ , N 1 ) \overline{w}_{N,\tau}(y)/N\in S(\mu',\rho,N_{1}) w N , τ ( y ) / N ∈ S ( μ ′ , ρ , N 1 ) , so by (M) w ‾ N , τ ( y ) / N ≤ s + ( μ ′ , ρ 0 , N 1 0 ) ≤ u ˉ τ ( μ ′ ) + θ ′ \overline{w}_{N,\tau}(y)/N\le s^{+}(\mu',\rho_{0},N_{1}^{0})\le\bar{u}_{\tau}(\mu')+\theta' w N , τ ( y ) / N ≤ s + ( μ ′ , ρ 0 , N 1 0 ) ≤ u ˉ τ ( μ ′ ) + θ ′ . By (Q) with ν = μ \nu=\mu ν = μ , The Quadratic Wasserstein Distance is a Metric on the Wasserstein Space §triangle and The Quadratic Wasserstein Distance is a Metric on the Wasserstein Space §symmetry , d ≤ W 2 ( μ x , μ ) + W 2 ( μ y , μ ′ ) + W < W + 2 ρ d\le W_{2}(\mu_{x},\mu)+W_{2}(\mu_{y},\mu')+W<W+2\rho d ≤ W 2 ( μ x , μ ) + W 2 ( μ y , μ ′ ) + W < W + 2 ρ ; by (B) with c ′ = ∣ E ( μ ′ ) ∣ + 1 c'=|\mathcal{E}(\mu')|+1 c ′ = ∣ E ( μ ′ ) ∣ + 1 , r N ( y ) / N ≤ ( R τ 2 + 2 τ K ′ / N 1 ) 1 / 2 r_{N}(y)/\sqrt{N}\le(R_{\tau}^{2}+2\tau K'/N_{1})^{1/2} r N ( y ) / N ≤ ( R τ 2 + 2 τ K ′ / N 1 ) 1/2 . So (T) gives
u ˉ τ ( μ ) − ρ < u ˉ τ ( μ ′ ) + θ ′ + Φ ( W + 2 ρ , ( R τ 2 + 2 τ K ′ / N 1 ) 1 / 2 ) . \bar{u}_{\tau}(\mu)-\rho<\bar{u}_{\tau}(\mu')+\theta'+\Phi\Bigl(W+2\rho,\bigl(R_{\tau}^{2}+2\tau K'/N_{1}\bigr)^{1/2}\Bigr). u ˉ τ ( μ ) − ρ < u ˉ τ ( μ ′ ) + θ ′ + Φ ( W + 2 ρ , ( R τ 2 + 2 τ K ′ / N 1 ) 1/2 ) .
The right side depends continuously on 1 / N 1 ≥ 0 1/N_{1}\ge0 1/ N 1 ≥ 0 ; letting N 1 → ∞ N_{1}\to\infty N 1 → ∞ , then ρ → 0 \rho\to0 ρ → 0 , then θ ′ → 0 \theta'\to0 θ ′ → 0 yields u ˉ τ ( μ ) ≤ u ˉ τ ( μ ′ ) + Φ ( W , R τ ) \bar{u}_{\tau}(\mu)\le\bar{u}_{\tau}(\mu')+\Phi(W,R_{\tau}) u ˉ τ ( μ ) ≤ u ˉ τ ( μ ′ ) + Φ ( W , R τ ) , the first inequality of clause 3. For the second: given θ ′ > 0 \theta'>0 θ ′ > 0 choose ρ 0 , N 1 0 \rho_{0},N_{1}^{0} ρ 0 , N 1 0 with s − ( μ ′ , ρ 0 , N 1 0 ) ≥ u ‾ τ ( μ ′ ) − θ ′ s^{-}(\mu',\rho_{0},N_{1}^{0})\ge\underline{u}_{\tau}(\mu')-\theta' s − ( μ ′ , ρ 0 , N 1 0 ) ≥ u τ ( μ ′ ) − θ ′ ; for ρ , N 1 \rho,N_{1} ρ , N 1 as above, since s − ( μ , ρ , N 1 ) ≤ u ‾ τ ( μ ) s^{-}(\mu,\rho,N_{1})\le\underline{u}_{\tau}(\mu) s − ( μ , ρ , N 1 ) ≤ u τ ( μ ) is a greatest lower bound there are N ≥ N 1 N\ge N_{1} N ≥ N 1 and x ∈ W N x\in W_{N} x ∈ W N with W 2 ( μ x , μ ) < ρ W_{2}(\mu_{x},\mu)<\rho W 2 ( μ x , μ ) < ρ and w ‾ N , τ ( x ) / N < u ‾ τ ( μ ) + ρ \underline{w}_{N,\tau}(x)/N<\underline{u}_{\tau}(\mu)+\rho w N , τ ( x ) / N < u τ ( μ ) + ρ ; with y y y from (Rec) for μ ′ \mu' μ ′ , (M) gives w ‾ N , τ ( y ) / N ≥ u ‾ τ ( μ ′ ) − θ ′ \underline{w}_{N,\tau}(y)/N\ge\underline{u}_{\tau}(\mu')-\theta' w N , τ ( y ) / N ≥ u τ ( μ ′ ) − θ ′ , and the second inequality of (T) gives u ‾ τ ( μ ) + ρ > u ‾ τ ( μ ′ ) − θ ′ − Φ ( W + 2 ρ , ( R τ 2 + 2 τ K ′ / N 1 ) 1 / 2 ) \underline{u}_{\tau}(\mu)+\rho>\underline{u}_{\tau}(\mu')-\theta'-\Phi(W+2\rho,(R_{\tau}^{2}+2\tau K'/N_{1})^{1/2}) u τ ( μ ) + ρ > u τ ( μ ′ ) − θ ′ − Φ ( W + 2 ρ , ( R τ 2 + 2 τ K ′ / N 1 ) 1/2 ) ; the same limits give u ‾ τ ( μ ) ≥ u ‾ τ ( μ ′ ) − Φ ( W , R τ ) \underline{u}_{\tau}(\mu)\ge\underline{u}_{\tau}(\mu')-\Phi(W,R_{\tau}) u τ ( μ ) ≥ u τ ( μ ′ ) − Φ ( W , R τ ) .
Step 6 (Clause 4). Since ( N k ) (N_{k}) ( N k ) is a strictly increasing sequence of natural numbers, N k ≥ N 1 + k − 1 ≥ k N_{k}\ge N_{1}+k-1\ge k N k ≥ N 1 + k − 1 ≥ k . Let ε > 0 \varepsilon>0 ε > 0 . Choose ρ > 0 \rho>0 ρ > 0 and N ^ ≥ N 0 \hat{N}\ge N_{0} N ^ ≥ N 0 with s + ( μ , ρ , N ^ ) < u ˉ τ ( μ ) + ε / 2 s^{+}(\mu,\rho,\hat{N})<\bar{u}_{\tau}(\mu)+\varepsilon/2 s + ( μ , ρ , N ^ ) < u ˉ τ ( μ ) + ε /2 (greatest lower bound), and then k 1 k_{1} k 1 with N k ≥ N ^ N_{k}\ge\hat{N} N k ≥ N ^ and W 2 ( μ x k N k , μ ) < ρ W_{2}(\mu^{N_{k}}_{x^{k}},\mu)<\rho W 2 ( μ x k N k , μ ) < ρ for k ≥ k 1 k\ge k_{1} k ≥ k 1 . For such k k k , w ‾ N k , τ ( x k ) / N k ∈ S ( μ , ρ , N ^ ) \overline{w}_{N_{k},\tau}(x^{k})/N_{k}\in S(\mu,\rho,\hat{N}) w N k , τ ( x k ) / N k ∈ S ( μ , ρ , N ^ ) , so w ‾ N k , τ ( x k ) / N k < u ˉ τ ( μ ) + ε / 2 \overline{w}_{N_{k},\tau}(x^{k})/N_{k}<\bar{u}_{\tau}(\mu)+\varepsilon/2 w N k , τ ( x k ) / N k < u ˉ τ ( μ ) + ε /2 . Symmetrically, with ρ ′ , N ^ ′ \rho',\hat{N}' ρ ′ , N ^ ′ such that s − ( μ , ρ ′ , N ^ ′ ) > u ‾ τ ( μ ) − ε / 2 s^{-}(\mu,\rho',\hat{N}')>\underline{u}_{\tau}(\mu)-\varepsilon/2 s − ( μ , ρ ′ , N ^ ′ ) > u τ ( μ ) − ε /2 , there is k 2 k_{2} k 2 with w ‾ N k , τ ( x k ) / N k > u ‾ τ ( μ ) − ε / 2 \underline{w}_{N_{k},\tau}(x^{k})/N_{k}>\underline{u}_{\tau}(\mu)-\varepsilon/2 w N k , τ ( x k ) / N k > u τ ( μ ) − ε /2 for k ≥ k 2 k\ge k_{2} k ≥ k 2 . This proves the first display with k 0 = max ( k 1 , k 2 ) k_{0}=\max(k_{1},k_{2}) k 0 = max ( k 1 , k 2 ) . If moreover P N k ( x k ) ≤ c ′ N k P_{N_{k}}(x^{k})\le c'N_{k} P N k ( x k ) ≤ c ′ N k for all k k k , choose k 3 k_{3} k 3 with ∣ c ′ ∣ / k < ε / 2 |c'|/k<\varepsilon/2 ∣ c ′ ∣/ k < ε /2 for k ≥ k 3 k\ge k_{3} k ≥ k 3 ; then by (1a) and (1b), for k ≥ max ( k 1 , k 2 , k 3 ) k\ge\max(k_{1},k_{2},k_{3}) k ≥ max ( k 1 , k 2 , k 3 ) ,
v N k ( x k ) N k ≤ w ‾ N k , τ ( x k ) N k + ∣ c ′ ∣ N k < u ˉ τ ( μ ) + ε , v N k ( x k ) N k ≥ w ‾ N k , τ ( x k ) N k − ∣ c ′ ∣ N k > u ‾ τ ( μ ) − ε . \frac{v_{N_{k}}(x^{k})}{N_{k}}\le\frac{\overline{w}_{N_{k},\tau}(x^{k})}{N_{k}}+\frac{|c'|}{N_{k}}<\bar{u}_{\tau}(\mu)+\varepsilon,\qquad\frac{v_{N_{k}}(x^{k})}{N_{k}}\ge\frac{\underline{w}_{N_{k},\tau}(x^{k})}{N_{k}}-\frac{|c'|}{N_{k}}>\underline{u}_{\tau}(\mu)-\varepsilon. N k v N k ( x k ) ≤ N k w N k , τ ( x k ) + N k ∣ c ′ ∣ < u ˉ τ ( μ ) + ε , N k v N k ( x k ) ≥ N k w N k , τ ( x k ) − N k ∣ c ′ ∣ > u τ ( μ ) − ε .
Step 7 (Clause 5). Let μ ∈ D \mu\in\mathcal{D} μ ∈ D . Define N k N_{k} N k and z k ∈ W N k z^{k}\in W_{N_{k}} z k ∈ W N k recursively: put N ^ 1 = N 0 \hat{N}_{1}=N_{0} N ^ 1 = N 0 ; given N ^ k ≥ N 0 \hat{N}_{k}\ge N_{0} N ^ k ≥ N 0 , since u ˉ τ ( μ ) ≤ s + ( μ , 1 / k , N ^ k ) \bar{u}_{\tau}(\mu)\le s^{+}(\mu,1/k,\hat{N}_{k}) u ˉ τ ( μ ) ≤ s + ( μ , 1/ k , N ^ k ) , which is a least upper bound, choose N k ≥ N ^ k N_{k}\ge\hat{N}_{k} N k ≥ N ^ k and z k ∈ W N k z^{k}\in W_{N_{k}} z k ∈ W N k with W 2 ( μ z k N k , μ ) < 1 / k W_{2}(\mu^{N_{k}}_{z^{k}},\mu)<1/k W 2 ( μ z k N k , μ ) < 1/ k and w ‾ N k , τ ( z k ) / N k > u ˉ τ ( μ ) − 1 / k \overline{w}_{N_{k},\tau}(z^{k})/N_{k}>\bar{u}_{\tau}(\mu)-1/k w N k , τ ( z k ) / N k > u ˉ τ ( μ ) − 1/ k , and put N ^ k + 1 = N k + 1 \hat{N}_{k+1}=N_{k}+1 N ^ k + 1 = N k + 1 . Then ( N k ) (N_{k}) ( N k ) is strictly increasing with N 1 ≥ N 0 N_{1}\ge N_{0} N 1 ≥ N 0 . Let x k ∈ W N k x^{k}\in W_{N_{k}} x k ∈ W N k with α k = W 2 ( μ x k N k , μ ) → 0 \alpha_{k}=W_{2}(\mu^{N_{k}}_{x^{k}},\mu)\to0 α k = W 2 ( μ x k N k , μ ) → 0 and P N k ( x k ) ≤ c ′ N k P_{N_{k}}(x^{k})\le c'N_{k} P N k ( x k ) ≤ c ′ N k . Apply (T) at level N k N_{k} N k with ( x , y ) = ( z k , x k ) (x,y)=(z^{k},x^{k}) ( x , y ) = ( z k , x k ) : by (Q) with ν = μ \nu=\mu ν = μ , d k = ∥ z k − x k ∥ / N k ≤ 1 / k + α k d_{k}=\lVert z^{k}-x^{k}\rVert/\sqrt{N_{k}}\le1/k+\alpha_{k} d k = ∥ z k − x k ∥ / N k ≤ 1/ k + α k , and by (B) with N k ≥ 1 N_{k}\ge1 N k ≥ 1 , r N k ( x k ) / N k ≤ B : = ( R τ 2 + 2 τ ( ∣ c ′ ∣ + ∣ e ∗ ∣ ) ) 1 / 2 r_{N_{k}}(x^{k})/\sqrt{N_{k}}\le B:=(R_{\tau}^{2}+2\tau(|c'|+|e_{*}|))^{1/2} r N k ( x k ) / N k ≤ B := ( R τ 2 + 2 τ ( ∣ c ′ ∣ + ∣ e ∗ ∣ ) ) 1/2 . Hence
w ‾ N k , τ ( x k ) N k ≥ w ‾ N k , τ ( z k ) N k − Φ ( d k , B ) > u ˉ τ ( μ ) − 1 k − Φ ( 1 k + α k , B ) , \frac{\overline{w}_{N_{k},\tau}(x^{k})}{N_{k}}\ge\frac{\overline{w}_{N_{k},\tau}(z^{k})}{N_{k}}-\Phi(d_{k},B)>\bar{u}_{\tau}(\mu)-\frac{1}{k}-\Phi\Bigl(\frac{1}{k}+\alpha_{k},B\Bigr), N k w N k , τ ( x k ) ≥ N k w N k , τ ( z k ) − Φ ( d k , B ) > u ˉ τ ( μ ) − k 1 − Φ ( k 1 + α k , B ) ,
and 1 k + Φ ( 1 k + α k , B ) → 0 \frac{1}{k}+\Phi(\frac{1}{k}+\alpha_{k},B)\to0 k 1 + Φ ( k 1 + α k , B ) → 0 . Given ε > 0 \varepsilon>0 ε > 0 , this bound and clause 4 (Step 6) give k 0 k_{0} k 0 with ∣ w ‾ N k , τ ( x k ) / N k − u ˉ τ ( μ ) ∣ < ε |\overline{w}_{N_{k},\tau}(x^{k})/N_{k}-\bar{u}_{\tau}(\mu)|<\varepsilon ∣ w N k , τ ( x k ) / N k − u ˉ τ ( μ ) ∣ < ε for k ≥ k 0 k\ge k_{0} k ≥ k 0 ; so the sequence converges to u ˉ τ ( μ ) \bar{u}_{\tau}(\mu) u ˉ τ ( μ ) . For the lower limit the construction is repeated independently. Put N ^ 1 ′ = N 0 \hat{N}'_{1}=N_{0} N ^ 1 ′ = N 0 ; given N ^ k ′ ≥ N 0 \hat{N}'_{k}\ge N_{0} N ^ k ′ ≥ N 0 , since s − ( μ , 1 / k , N ^ k ′ ) ≤ u ‾ τ ( μ ) s^{-}(\mu,1/k,\hat{N}'_{k})\le\underline{u}_{\tau}(\mu) s − ( μ , 1/ k , N ^ k ′ ) ≤ u τ ( μ ) and s − ( μ , 1 / k , N ^ k ′ ) s^{-}(\mu,1/k,\hat{N}'_{k}) s − ( μ , 1/ k , N ^ k ′ ) is a greatest lower bound, choose N k ′ ≥ N ^ k ′ N'_{k}\ge\hat{N}'_{k} N k ′ ≥ N ^ k ′ and z ′ k ∈ W N k ′ z'^{k}\in W_{N'_{k}} z ′ k ∈ W N k ′ with W 2 ( μ z ′ k N k ′ , μ ) < 1 / k W_{2}(\mu^{N'_{k}}_{z'^{k}},\mu)<1/k W 2 ( μ z ′ k N k ′ , μ ) < 1/ k and w ‾ N k ′ , τ ( z ′ k ) / N k ′ < u ‾ τ ( μ ) + 1 / k \underline{w}_{N'_{k},\tau}(z'^{k})/N'_{k}<\underline{u}_{\tau}(\mu)+1/k w N k ′ , τ ( z ′ k ) / N k ′ < u τ ( μ ) + 1/ k , and put N ^ k + 1 ′ = N k ′ + 1 \hat{N}'_{k+1}=N'_{k}+1 N ^ k + 1 ′ = N k ′ + 1 ; then ( N k ′ ) (N'_{k}) ( N k ′ ) is strictly increasing with N 1 ′ ≥ N 0 N'_{1}\ge N_{0} N 1 ′ ≥ N 0 . Now let x ′ k ∈ W N k ′ x'^{k}\in W_{N'_{k}} x ′ k ∈ W N k ′ be arbitrary with α k ′ = W 2 ( μ x ′ k N k ′ , μ ) → 0 \alpha'_{k}=W_{2}(\mu^{N'_{k}}_{x'^{k}},\mu)\to0 α k ′ = W 2 ( μ x ′ k N k ′ , μ ) → 0 and P N k ′ ( x ′ k ) ≤ c ′ N k ′ P_{N'_{k}}(x'^{k})\le c'N'_{k} P N k ′ ( x ′ k ) ≤ c ′ N k ′ for every k k k . By (Q) with ν = μ \nu=\mu ν = μ , d k ′ = ∥ z ′ k − x ′ k ∥ / N k ′ ≤ 1 / k + α k ′ d'_{k}=\lVert z'^{k}-x'^{k}\rVert/\sqrt{N'_{k}}\le1/k+\alpha'_{k} d k ′ = ∥ z ′ k − x ′ k ∥ / N k ′ ≤ 1/ k + α k ′ , and by (B), r N k ′ ( x ′ k ) / N k ′ ≤ B r_{N'_{k}}(x'^{k})/\sqrt{N'_{k}}\le B r N k ′ ( x ′ k ) / N k ′ ≤ B with the same B B B . The second inequality of (T) at level N k ′ N'_{k} N k ′ with ( x , y ) = ( z ′ k , x ′ k ) (x,y)=(z'^{k},x'^{k}) ( x , y ) = ( z ′ k , x ′ k ) gives
w ‾ N k ′ , τ ( x ′ k ) N k ′ ≤ w ‾ N k ′ , τ ( z ′ k ) N k ′ + Φ ( d k ′ , B ) < u ‾ τ ( μ ) + 1 k + Φ ( 1 k + α k ′ , B ) , \frac{\underline{w}_{N'_{k},\tau}(x'^{k})}{N'_{k}}\le\frac{\underline{w}_{N'_{k},\tau}(z'^{k})}{N'_{k}}+\Phi(d'_{k},B)<\underline{u}_{\tau}(\mu)+\frac{1}{k}+\Phi\Bigl(\frac{1}{k}+\alpha'_{k},B\Bigr), N k ′ w N k ′ , τ ( x ′ k ) ≤ N k ′ w N k ′ , τ ( z ′ k ) + Φ ( d k ′ , B ) < u τ ( μ ) + k 1 + Φ ( k 1 + α k ′ , B ) ,
and, together with clause 4 applied to the sequences ( N k ′ ) (N'_{k}) ( N k ′ ) and ( x ′ k ) (x'^{k}) ( x ′ k ) , the sequence ( w ‾ N k ′ , τ ( x ′ k ) / N k ′ ) k \bigl(\underline{w}_{N'_{k},\tau}(x'^{k})/N'_{k}\bigr)_{k} ( w N k ′ , τ ( x ′ k ) / N k ′ ) k converges to u ‾ τ ( μ ) \underline{u}_{\tau}(\mu) u τ ( μ ) .