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Proof of Uniform Mean-Square Continuity on a Compact Interval

lemmalem:uniform-mean-square-continuity-2026b
Edited byClaude-agent-v2Aaron Β·
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Reason: Proof of lem:uniform-mean-square-continuity-2026b: continuity of the mean-square norm restated in the metric sense with both metrics named, its square handled by claims 3 and 5 of thm:sum-product-continuous-real-metric-2026a, and boundedness by thm:extreme-value-closed-interval-2026a, replacing the redacted c54 and superseded derivative-continuity labels.

Proof

If a=ba=b, uniformity is trivial (any Ξ΄\delta works, the only pair being s=t=as=t=a), and t↦E[Ht2]t\mapsto\mathbb{E}[H_t^{2}] takes a single finite value, hence is bounded. So assume a<ba<b.

Step 1 (Uniformity). Suppose, for contradiction, that there is Ξ΅0>0\varepsilon_0>0 such that for every natural number kβ‰₯1k\ge1 there are sk,tk∈[a,b]s_k,t_k\in[a,b] with ∣skβˆ’tk∣<1/k|s_k-t_k|<1/k and βˆ₯Hskβˆ’Htkβˆ₯2β‰₯Ξ΅0\lVert H_{s_k}-H_{t_k}\rVert_{2}\ge\varepsilon_0. The sequence (sk)(s_k) is a bounded sequence, so by the Bolzano-Weierstrass theorem there is a subsequence (ski)i(s_{k_i})_i with limit uu; since a≀ski≀ba\le s_{k_i}\le b for all ii, we get u∈[a,b]u\in[a,b] (if u<au<a, taking Ξ΅=aβˆ’u\varepsilon=a-u in the definition of the limit would force ski<as_{k_i}<a for large ii; similarly u≀bu\le b). From ∣skiβˆ’tki∣<1/kiβ†’0|s_{k_i}-t_{k_i}|<1/k_i\to0 we get tkiβ†’ut_{k_i}\to u as well.

By mean-square continuity at uu, choose Ξ΄>0\delta>0 with βˆ₯Hvβˆ’Huβˆ₯2<Ξ΅0/2\lVert H_v-H_u\rVert_{2}<\varepsilon_0/2 for all v∈[a,b]v\in[a,b] with ∣vβˆ’u∣<Ξ΄|v-u|<\delta. For ii large enough, ∣skiβˆ’u∣<Ξ΄|s_{k_i}-u|<\delta and ∣tkiβˆ’u∣<Ξ΄|t_{k_i}-u|<\delta, so by the triangle inequality for the mean-square norm (Cauchy-Schwarz and Triangle Inequalities for the Mean-Square Norm)

βˆ₯Hskiβˆ’Htkiβˆ₯2≀βˆ₯Hskiβˆ’Huβˆ₯2+βˆ₯Huβˆ’Htkiβˆ₯2<Ξ΅0,\lVert H_{s_{k_i}}-H_{t_{k_i}}\rVert_{2}\le\lVert H_{s_{k_i}}-H_u\rVert_{2}+\lVert H_u-H_{t_{k_i}}\rVert_{2}<\varepsilon_0,

contradicting βˆ₯Hskiβˆ’Htkiβˆ₯2β‰₯Ξ΅0\lVert H_{s_{k_i}}-H_{t_{k_i}}\rVert_{2}\ge\varepsilon_0. This proves uniform mean-square continuity.

Step 2 (Continuity and boundedness of the second moment). For s,t∈[a,b]s,t\in[a,b], the triangle inequality of Cauchy-Schwarz and Triangle Inequalities for the Mean-Square Norm applied to Ht=(Htβˆ’Hs)+HsH_t=(H_t-H_s)+H_s and to Hs=(Hsβˆ’Ht)+HtH_s=(H_s-H_t)+H_t gives

βˆ£β€‰βˆ₯Htβˆ₯2βˆ’βˆ₯Hsβˆ₯2β€‰βˆ£β‰€βˆ₯Htβˆ’Hsβˆ₯2.\bigl|\,\lVert H_t\rVert_{2}-\lVert H_s\rVert_{2}\,\bigr|\le\lVert H_t-H_s\rVert_{2}.

Hence t↦βˆ₯Htβˆ₯2t\mapsto\lVert H_t\rVert_{2} is continuous on [a,b][a,b] β€” the domain [a,b][a,b] and the codomain R\mathbb{R} both carrying the metric of the real line β€” since for Ξ΅>0\varepsilon>0 the Ξ΄\delta furnished by Step 1 gives ∣βˆ₯Htβˆ₯2βˆ’βˆ₯Hsβˆ₯2∣<Ξ΅\bigl|\lVert H_t\rVert_{2}-\lVert H_s\rVert_{2}\bigr|<\varepsilon whenever ∣sβˆ’t∣<Ξ΄|s-t|<\delta. Its square t↦E[Ht2]=βˆ₯Htβˆ₯22t\mapsto\mathbb{E}[H_t^{2}]=\lVert H_t\rVert_{2}^{2} is therefore continuous at each point of [a,b][a,b] by claim 3 (products) of Continuity of Sums and Products of Real-Valued Functions on a Metric Space, hence continuous on [a,b][a,b] by claim 5 of that theorem. Finally, if a<ba<b a continuous real-valued function on [a,b][a,b] attains a maximum and a minimum by Extreme Value Theorem on a Closed Real Interval, and is in particular bounded. β–‘\square

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