Preliminary: the trajectory satisfies the flow hypotheses of the extended lemma. The map S has continuous components and values in Δl with S0=x0, and for all t,γ, by clause 2 of the trajectory-pair definition, Stγ=S0γ+∫0tbγ(Ss,As)ds with a Riemann integral of a continuous integrand; by claim 3 of the integral toolkit this Riemann integral equals the Lebesgue integral ∫[0,t]bγ(Ss,As)ds. Hence, with S∗=S, the hypotheses of claims 4 and 5 of the extended lemma hold, and in particular (claim 4 there) S=S(x0,ζA). Since εY>0 and ∣x0−S0∗∣=0<εY, the stopped deviation bound of claim 3 of the extended lemma is available:
Ymin(t,τ∗(ω))(ω)≤εYfor every t∈[0,T],ω∈Ω.(P1)
Claim 1. Fix ω∈Ω0 and t∈[0,T], and put u=min(t,τ∗(ω)). By clause (vii)(a) of the existence and uniqueness theorem, Σu(ω)∈Δl and Σ0(ω)∈Δl. By the triangle inequality for the Euclidean norm,
since Su(x0,α^(ω))=Φu(ω) and Yu(ω)=∣Φu(ω)−Su∗∣ with S∗=S. The first summand is at most ∣Mu(ω)∣+ΛbeΛbuMu(ω)≤∣Mu(ω)∣+ΛbeΛbTMu(ω) by claim 2 of the tracking lemma (whose Sω is the flow S(Σ0(ω),α^(ω))) and the fact that the exponential function is nondecreasing. The second summand is at most eΛbT∣Σ0(ω)−x0∣ by claim 4 of the flow stability lemma, applied with base pair (x0,α^(ω)) and perturbed pair (Σ0(ω),α^(ω)): the perturbed control equals the base control, so every grγ of claim 3 there vanishes and G=0 is admissible. Since S0=x0, ∣Σ0(ω)−x0∣=N−1/2∣s0(ω)∣. The third summand is at most εY by (P1). Altogether
Next, bs(ω)≤b(ω) for every s∈[0,T] and ω∈Ω0: by the supremum lemma, Mγ(ω)=supr∈[0,T]∣Mrγ(ω)∣ for ω∈Ω0, so ∣Msγ(ω)∣≤Mγ(ω) for each γ, whence ∣Ms(ω)∣2=∑γ(Msγ(ω))2≤∑γ(Mγ(ω))2=M(ω)2 and ∣Ms(ω)∣≤M(ω), the nonnegative square root being nondecreasing; and Ms(ω)≤MT(ω)=I(ω), the paths of M being nondecreasing by claim 1 of the tracking lemma and I=MT on Ω0 by part (b) of the restricted-moments lemma. In particular, for t<τ∗(ω) one has min(t,τ∗(ω))=t, so 1{t<τ∗}(ω)∣st(ω)∣≤Nbt(ω)≤Nb(ω); for t≥τ∗(ω) the left side vanishes and the bound is trivial, b being nonnegative.
Claim 6. Fix ω∈Ω0 and t∈[0,T]. The displayed triangle inequality of Claim 1 and the two estimates following it were derived for an arbitrary point of [0,T], the stopping time entering only through the substitution of the barrier εY for the third summand by (P1); carrying them out at the point t itself rather than at u=min(t,τ∗(ω)) therefore gives
By the second part of Claim 1, ∣Mt(ω)∣≤M(ω) and Mt(ω)≤I(ω), so the sum of the first three summands is at most b(ω)−εY=Q(ω). Multiplying by N gives ∣st(ω)∣≤N(Yt(ω)+Q(ω)), which is Claim 6.
Claim 2. Fix γ and consider the process Xγ=(1Ω0Mtγ)t∈[0,T]. By claim 2 of the covariation lemma, Xγ is progressively measurable with respect to (Ftsys)t∈[0,T] — hence adapted, each Xtγ being Ftsys-measurable by claim 1 of the progressive measurability toolkit — it is bounded in absolute value everywhere by the constant of that claim, whose value 1+2(l−1)BT is at most KM=2+2(l−1)BT (the two lemmas use the same letter for different constants), so each Xtγ is square-integrable (a bounded random variable is square-integrable by linearity and monotonicity of the integral), and for every ω∈Ω0 its path agrees with t↦Mtγ(ω), which is right-continuous at every t∈[0,T) in the sense required by the supremum lemma, again by claim 2 of the covariation lemma. The constant function τ≡T is a stopping time of (Ftsys)t∈[0,T] by claim 1 of the stopping-time toolkit, so claim 4 of the covariation lemma gives, for all 0≤r≤t≤T and every D∈Frsys,
so by the averaged-form characterization in the martingale definition, Xγ is a square-integrable martingale with respect to (Ftsys)t∈[0,T], with time index restricted to [0,T]. All hypotheses of the fourth-moment maximal inequality thus hold for Xγ with the event Ω0, and its conclusion reads E[(Mγ)4]≤4E[(XTγ)4]. Pointwise (XTγ)4=1Ω0(MTγ)4≤∣MT∣4, since (MTγ)2≤∑δ(MTδ)2=∣MT∣2; so by part (b) of the restricted-moments lemma,
E[(Mγ)4]≤4E[∣MT∣4]≤4cMκTN−2.
For reals x1,…,xl one has (∑γxγ)2≤l∑γxγ2 (sum the inequalities 2xγxδ≤xγ2+xδ2 over all pairs); applying this with xγ=(Mγ)2 gives M4=(∑γ(Mγ)2)2≤l∑γ(Mγ)4, whence E[M4]≤4l2cMκTN−2. Each Mγ is a random variable with 0≤Mγ≤KM (the supremum lemma), so M is a random variable with 0≤M≤lKM, and I is a random variable with E[I4]≤T4cMκTN−2 by part (b) of the restricted-moments lemma; ∣s0∣ is a random variable (the Euclidean norm of a tuple of random variables, by measurability of continuous functions of measurable maps), so Q and b=εY+Q are random variables.
For nonnegative reals, (a+b+c)2≤3(a2+b2+c2) (the case l=3 of the display above), so (a+b+c)4≤9(a2+b2+c2)2≤27(a4+b4+c4). Hence
Claim 3. Let D′∈F and s,t∈[0,T]. Measurability. By claim 2 of the covariation lemma, each 1Ω0Σγ is progressively measurable with respect to (Ftsys)t∈[0,T], and τ∗ is a stopping time of that filtration (claim 3 of the extended lemma), so by claim 4 of the stopping-time toolkit the sampled function ω↦1Ω0(ω)Σmin(t,τ∗(ω))γ(ω) is a random variable; the function ω↦Smin(t,τ∗(ω))γ is a random variable as the composition of the measurable ω↦min(t,τ∗(ω)) (for real q, {min(t,τ∗)≤q} is Ω or {τ∗≤q}∈F) with the continuous Sγ, by measurability of continuous functions of measurable maps; hence 1Ω0smin(t,τ∗)γ=N(1Ω0Σmin(t,τ∗)γ−1Ω0Smin(t,τ∗)γ) and 1Ω0∣smin(t,τ∗)∣2 are random variables by the same composition lemma. Likewise {s<τ∗}∈Gs⊆F by claim 3 of the extended lemma, and 1Ω01{s<τ∗}∣ss∣2 is a random variable (1Ω0ssγ=N(1Ω0Σsγ−1Ω0Ssγ) being a random variable, since 1Ω0Σsγ is Fssys-measurable by progressive measurability and claim 1 of the progressive measurability toolkit, and Ssγ is a constant). Bounds. By claim 1, at every point of Ω0 one has ∣smin(t,τ∗)∣2≤Nb2 and 1{s<τ∗}∣ss∣2≤Nb2; off Ω0 the left-hand integrands below vanish. Hence, by monotonicity of the expectation,
the middle step by Cauchy-Schwarz applied to 1D′ and Q2 together with E[1D′2]=P(D′). Multiplying by N gives the asserted bounds. The fourth-moment bound follows the same way from ∣smin(t,τ∗)∣4≤N2b4 on Ω0 and claim 2: E[1Ω0∣smin(t,τ∗)∣4]≤N2E[b4]≤8N2εY4+8cQκ0.
Claim 4. Since b=εY+Q with Q≥0, {b≥εY+θ}={Q≥θ}={Q4≥θ4}, the fourth power being nondecreasing on [0,∞). By Markov's inequality applied to the nonnegative random variable Q4 at level θ4>0 and by claim 2,
P(b≥εY+θ)≤θ4E[Q4]≤cQκ0θ−4N−2.
Claim 5. Let ω∈Ω0 and t∈[0,T]. By claim 2 of the realized-control lemma, α^(s,ω)=αs(ω) for every s∈[0,T], so at every s,
α^(s,ω)−As2=αs(ω)−As2=N1as(ω)2.
The two integrands agree at every point of [0,T], so their Lebesgue integrals over [0,t] agree, and by linearity of the integral the constant factor 1/N may be taken outside: