Hamilton trajectories under a long-range force

Written by GPT-6.1 Sol (OpenAI) and GPT-6 Astra (OpenAI). Self-checked by the writing AI. Original exposition: CC0.

Working question: Can position drift be large while the change of momentum stays small? For P0(ξ)=ξP_0(\xi)=\xi and a potential depending only on position, the exact ray is x(t)=t+Twx(t)=t+Tw, while momentum changes by a difference of potential values. Dividing position by time exposes a decaying relative displacement even when an accumulated phase grows. This is why trajectory data and time-derivative estimates need their own scaling.

A long-range force can accumulate over an infinite interval even when its derivatives are integrable. We compare Hamilton trajectories with free rays by dividing their position error by time. This reveals a decaying displacement, a uniformly small change of frequency, and precise estimates for every derivative of the initial data. We also determine which time derivative estimates require the trajectory to start on the free graph.

The prerequisite proofs are finite-dimensional linear algebra and the differential rules, compactness and the scalar mean-value theorem, the continuous fundamental theorem of calculus, and exponentials, real powers and trigonometric functions. The short-interval construction of the smooth flow and the derivative-exponent calculation are proved below. The later lesson Regularizing long-range coefficients develops related decay classes.

For background on smooth flows see Teschl [T]; Hamiltonian characteristics are discussed by Oh [O], and long-range polynomial trajectories by Hörmander [HW]. We use Hamilton's equations x′=Hξx'=H_\xi, ξ′=−Hx\xi'=-H_x, and write X=(1+∣x∣2)1/2X=(1+|x|^2)^{1/2}. Derivative estimates are in ordinary real coordinates; replacing ∂\partial by D=−i∂D=-i\partial leaves their magnitudes unchanged.

Fix an integer κ≥2\kappa\ge2 and 0<δ<1/(κ+1)0<\delta<1/(\kappa+1). The full position-decay sequence is

m(j)={j+δ,0≤j≤κ,1+(κ−1+δ)j/κ,j≥κ.(1) m(j)= \begin{cases} j+\delta,&0\le j\le\kappa,\\ 1+(\kappa-1+\delta)j/\kappa,&j\ge\kappa. \end{cases} \tag{1}

The two formulas agree at the joining index. Put μ(k)=k+1−m(k+1),θ=(1−δ)/κ,a(k)=max⁡(μ(k),0).(2) \begin{gathered} \mu(k)=k+1-m(k+1),\\ \theta=(1-\delta)/\kappa,\\ a(k)=\max(\mu(k),0). \end{gathered} \tag{2} Thus μ(k)=−δ\mu(k)=-\delta for k<κk<\kappa, while μ(k)=θ(k+1)−1>0\mu(k)=\theta(k+1)-1>0 for k≥κk\ge\kappa. The strict upper bound on δ\delta makes μ(κ)>0\mu(\kappa)>0, so the integral estimates below have no zero exponent or logarithmic case. Also 0<θ<1/20<\theta<1/2.

1. A trajectory that can be solved exactly

Consider P0(ξ)=ξP_0(\xi)=\xi on the line and VL(x,ξ)=v(x)V_L(x,\xi)=v(x), where v(x)=a(1+x2)−δ/2v(x)=a(1+x^2)^{-\delta/2}. Hamilton's equations give x′=1x'=1 and ξ′=−v′(x)\xi'=-v'(x). Start at time TT with x(T)=T(1+w)x(T)=T(1+w) and ξ(T)=η\xi(T)=\eta. Then

x(t)=t+Tw,z(t)=x(t)/t−1=Tw/t,ξ(t)=η−v(t+Tw)+v(T(1+w)).(3) \begin{aligned} x(t)&=t+Tw,\\ z(t)&=x(t)/t-1=Tw/t,\\ \xi(t)&=\eta-v(t+Tw)+v(T(1+w)). \end{aligned} \tag{3}

For ∣w∣<1/2|w|<1/2, the frequency correction and its first data derivatives are O(T−δ)O(T^{-\delta}), while the displacement derivative keeps the exact factor T/tT/t. The trajectory has a uniformly small change of frequency even on an infinite future interval. Its position can still differ from the free ray by a long-range amount. These two features motivate the scaled variables below.

All derivatives of this model potential satisfy ∣v(j)(x)∣≤CjX−j−δ|v^{(j)}(x)|\le C_j X^{-j-\delta}. To see this, each term after jj differentiations has the form Cxℓ(1+x2)−δ/2−rC x^\ell(1+x^2)^{-\delta/2-r}, with nonnegative integers ℓ,r\ell,r satisfying 2r−ℓ=j2r-\ell=j. Differentiating either factor preserves this form with jj increased by one; a term with ℓ=0\ell=0 has no derivative contribution from that factor. Its modulus is at most CXℓ−δ−2r=CX−j−δC X^{\ell-\delta-2r}=C X^{-j-\delta}. Since m(j)≤j+δm(j)\le j+\delta, these bounds imply every required position estimate in (4), including the joining index and all higher orders.

2. Scaling the Hamilton equations

Take a real smooth long-range polynomial VL(x,ξ)=∑bα(x)ξαV_L(x,\xi)=\sum b_\alpha(x)\xi^\alpha, of any finite frequency order, with all mixed bounds ∣∂ξα∂xβVL(x,ξ)∣≤Cαβ,KX−m(∣β∣)(ξ∈K)(4) |\partial_\xi^\alpha\partial_x^\beta V_L(x,\xi)| \le C_{\alpha\beta,K}X^{-m(|\beta|)} \quad(\xi\in K) \tag{4} on each compact frequency set KK. Let P0P_0 be any real polynomial; no ellipticity is needed for these flow statements. In a compact regular-velocity region assume ∣∇P0(ξ)∣≥c>0|\nabla P_0(\xi)|\ge c>0 and ∣z∣≤c/2|z|\le c/2. Define x=t(∇P0(ξ)+z),U(t,z,ξ)=t−1VL(t(∇P0(ξ)+z),ξ),t>0.(5) \begin{gathered} x=t(\nabla P_0(\xi)+z),\\ U(t,z,\xi)=t^{-1}V_L(t(\nabla P_0(\xi)+z),\xi),\\ t>0. \end{gathered} \tag{5} The Hamilton equations x′=∂ξ(P0+VL)x'=\partial_\xi(P_0+V_L), ξ′=−∂xVL\xi'=-\partial_x V_L are exactly z′=−z/t+∂ξU,ξ′=−∂zU.(6) z'=-z/t+\partial_\xi U,\qquad \xi'=-\partial_z U. \tag{6} Indeed x′=∇P0+z+t(P0′′ξ′+z′)x'=\nabla P_0+z+t(P_0''\xi'+z'), while ∂ξU=t−1∂ξVL+P0′′∂xVL\partial_\xi U=t^{-1}\partial_\xi V_L+P_0''\partial_x V_L and ∂zU=∂xVL\partial_z U=\partial_x V_L. Substitution proves both signs and the damping term.

On this region ∣x∣≥ct/2|x|\ge ct/2. Each total parameter derivative of order qq of UU is a finite sum of terms tj−1c(ξ) ∂xβ∂ξγVL(x,ξ),j=∣β∣≤q,∣β∣+∣γ∣≤q,(7) \begin{gathered} t^{j-1}c(\xi)\,\partial_x^\beta\partial_\xi^\gamma V_L(x,\xi),\\ j=|\beta|\le q,\quad |\beta|+|\gamma|\le q, \end{gathered} \tag{7} with bounded smooth coefficients on compact frequency sets. Since j−m(j)j-m(j) is nondecreasing, ∣∂z,ξαU∣≤Cαt∣α∣−m(∣α∣)−1.(8) |\partial_{z,\xi}^\alpha U|\le C_\alpha t^{|\alpha|-m(|\alpha|)-1}. \tag{8} Repeated logarithmic time derivatives of tUtU, at fixed z,ξz,\xi, also have finite expansions with at most one new position derivative and one factor tt at each step. Hence, for E=t∂tE=t\partial_t, ∣∂z,ξαEτ(tU)∣≤Cατt∣α∣+τ−m(∣α∣+τ).(9) |\partial_{z,\xi}^\alpha E^\tau(tU)| \le C_{\alpha\tau}t^{|\alpha|+\tau-m(|\alpha|+\tau)}. \tag{9} This includes τ=0\tau=0. These complete parameter estimates concern actual coefficients with no independent time dependence.

3. How the derivative exponents combine

If q≥1q\ge1, ki≥1k_i\ge1 and ∑i=1qki=k\sum_{i=1}^q k_i=k, then μ(q)+∑i=1qa(ki)≤μ(k).(10) \mu(q)+\sum_{i=1}^q a(k_i)\le\mu(k). \tag{10} To prove this, first suppose k<κk<\kappa. Then all ki,q<κk_i,q<\kappa, and the left side is −δ=μ(k)-\delta=\mu(k). If k≥κk\ge\kappa and none of the kik_i reaches κ\kappa, the left side is μ(q)≤μ(k)\mu(q)\le\mu(k).

In the remaining cases let ℓ≥1\ell\ge1 be the number of ki≥κk_i\ge\kappa. All other kik_i are at least one, so ∑ki≥κki≤k−q+ℓ,∑ia(ki)≤θ(k−q+2ℓ)−ℓ.(11) \begin{gathered} \sum_{k_i\ge\kappa}k_i\le k-q+\ell,\\ \sum_i a(k_i)\le\theta(k-q+2\ell)-\ell. \end{gathered} \tag{11} If q≥κq\ge\kappa, adding μ(q)=θ(q+1)−1\mu(q)=\theta(q+1)-1 gives a bound μ(k)+ℓ(2θ−1)≤μ(k)\mu(k)+\ell(2\theta-1)\le\mu(k). If q<κq<\kappa, subtracting μ(k)=θ(k+1)−1\mu(k)=\theta(k+1)-1 from that bound plus −δ-\delta gives at most 1−δ−θ(q+1)+ℓ(2θ−1)≤−δ−θ(q−1)≤0.(12) \begin{gathered} 1-\delta-\theta(q+1)+\ell(2\theta-1)\\ \le-\delta-\theta(q-1)\le0. \end{gathered} \tag{12} This proves (10) in all cases, including q=1q=1.

Consequently a smooth outer function with derivative order qq bounded by tμ(q)+bt^{\mu(q)+b}, composed with an inner map whose positive-order derivatives kik_i are bounded by ta(ki)t^{a(k_i)}, has derivatives of total order kk bounded by Ctμ(k)+bCt^{\mu(k)+b}. To justify the composition formula, differentiate repeatedly: every positive-order derivative is a finite sum of an outer derivative of order qq, evaluated on the inner map, times qq inner derivatives of positive orders summing to kk. This follows by induction using only the finite product and chain rules. (10) bounds each term. Constants depend on the finite derivative order, independently of tt and the initial time TT.

4. A future flow with constants uniform in its starting time

Theorem 4.1 (uniform future flow). Let ω⊂R2n\omega\subset\mathbb R^{2n} be open and closed under contractions of its first coordinate: (z,ξ)∈ω⇒(sz,ξ)∈ω(z,\xi)\in\omega\Rightarrow(sz,\xi)\in\omega for 0≤s≤10\le s\le1. Let ω′⋐ω\omega'\Subset\omega. Assume real smooth UU obeys (8) uniformly on ω\omega for all sufficiently large tt. For all sufficiently large TT, the equations with (z(T),ξ(T))=(w,η)∈ω′(z(T),\xi(T))=(w,\eta)\in\omega' have a unique solution in ω\omega for every t≥Tt\ge T, and constants independent of TT give ∣∂w,ηα(z,ξ)∣≤Cαtμ(∣α∣),∣α∣≥κ,∣∂w,ηα(ξ−η)∣≤CαTμ(∣α∣),∣α∣<κ,∣∂w,ηαz∣≤(T/t)∣∂w,ηαw∣+Cαtμ(∣α∣),∣α∣<κ.(13) \begin{gathered} |\partial_{w,\eta}^\alpha(z,\xi)|\le C_\alpha t^{\mu(|\alpha|)},\\ |\alpha|\ge\kappa,\\ |\partial_{w,\eta}^\alpha(\xi-\eta)|\le C_\alpha T^{\mu(|\alpha|)},\\ |\alpha|<\kappa,\\ |\partial_{w,\eta}^\alpha z|\\ \le (T/t)|\partial_{w,\eta}^\alpha w|+C_\alpha t^{\mu(|\alpha|)},\\ |\alpha|<\kappa. \end{gathered} \tag{13}

Proof. On a closed coordinate ball and a sufficiently short time interval, the vector field F(t,Y)=(−z/t+Uξ,−Uz)F(t,Y)=(-z/t+U_\xi,-U_z) has bounded size MM and Lipschitz constant LL; the latter follows by integrating DYFD_YF along segments. Start in the concentric ball of half the radius. Choose the interval length hh so that hMhM is at most half the radius and hL<1hL<1. Then the integral map takes continuous paths in the closed ball to paths in the same ball and is a contraction in the supremum norm. Its iterates have geometrically summable differences. Completeness follows coordinate by coordinate: a uniformly Cauchy sequence has pointwise limits, convergence to them is uniform, and the uniform limit is continuous and remains in the closed ball. The Lipschitz estimate permits passage to the limit in the integral, so the limit solves the path equation. The contraction inequality proves uniqueness. These choices work uniformly for the initial points in the smaller ball.

We will use the following integral estimate. If N,b,f≥0N,b,f\ge0 are continuous and

N(t)≤A+∫Tt(b(s)N(s)+f(s)) ds,A≥0, N(t)\le A+\int_T^t\bigl(b(s)N(s)+f(s)\bigr)\,ds, \qquad A\ge0,

call the right side G(t)G(t). Then N≤GN\le G, G(T)=AG(T)=A, and G′≤bG+fG'\le bG+f. Multiplying by e−B(t)e^{-B(t)}, where B(t)=∫Ttb(s) dsB(t)=\int_T^t b(s)\,ds, and integrating gives

N(t)≤eB(t)(A+∫Tte−B(s)f(s) ds). N(t)\le e^{B(t)}\left(A+\int_T^t e^{-B(s)}f(s)\,ds\right).

This proves the precise integrating-factor estimate needed below, including zero initial value and a nonconstant forcing. It also applies to an integrated differential inequality; the regularized norms used below are differentiable before their regularization is removed.

We justify data differentiation before estimating any jet. Write Y(t,a)Y(t,a) for this solution with initial data a=(w,η)a=(w,\eta). Apply the just-proved estimate with b=Lb=L, f=0f=0, A=∣h∣A=|h| to the difference of two path equations. It gives ∣Y(t,a+h)−Y(t,a)∣≤C∣h∣|Y(t,a+h)-Y(t,a)|\le C|h| on the fixed interval. Let J(t,a)J(t,a) solve

J(t,a)=I+∫TtDYF(s,Y(s,a))J(s,a) ds. J(t,a)=I+\int_T^t D_YF(s,Y(s,a))J(s,a)\,ds.

Its Picard series converges uniformly, since its term of order jj is bounded by Lj∣t−T∣j/j!L^j|t-T|^j/j!. Put Δh=Y(t,a+h)−Y(t,a)\Delta_h=Y(t,a+h)-Y(t,a). The segment form of Taylor's theorem writes the difference of the two vector fields as DYF(s,Y(s,a))Δh+Rh(s)ΔhD_YF(s,Y(s,a))\Delta_h+R_h(s)\Delta_h, with sup⁡s∥Rh(s)∥→0\sup_s\|R_h(s)\|\to0: all paths lie in one compact neighborhood and DYFD_YF is uniformly continuous there. Subtract the equation for JhJ h and divide by ∣h∣|h|. The resulting remainder has zero initial value, a bounded linear coefficient, and a forcing term tending uniformly to zero. The same integrating-factor estimate makes its uniform norm tend to zero. Thus DaY=JD_aY=J; continuity follows from its integral equation. This proves an actual derivative, rather than only a candidate variational equation.

For higher orders, induct on the regularity of the vector field in arbitrary finite dimension. The first-derivative argument just proved the C1C^1 step. Suppose the assertion is known for every CkC^k vector field, and let FF be Ck+1C^{k+1}. The augmented equation for the pair (Y,J)(Y,J) has vector field (F(t,Y),DYF(t,Y)J)(F(t,Y),D_YF(t,Y)J), which is CkC^k in its finite-dimensional variables. Its local flow is therefore CkC^k in the initial values by the induction hypothesis. Restrict the initial matrix to J(T)=IJ(T)=I; uniqueness identifies its matrix component with the first derivative DaYD_aY already constructed. Thus DaYD_aY is CkC^k, which makes YY a Ck+1C^{k+1} function of its initial data. This closes the induction without presupposing differentiability of a higher jet. Uniqueness patches the argument across successive short intervals. Time smoothness on finite intervals then follows from ∂tY=F(t,Y)\partial_tY=F(t,Y). Repeated product and chain rules give the equations linear in the highest data derivative, with lower-derivative terms estimated below.

Local uniqueness glues all extensions to a maximal future interval. Indeed, two extensions with the same initial data cannot first cease to agree at an interior time: continuity gives equal data there, and local uniqueness extends their agreement further. Their union is therefore a single solution wherever either is defined.

The first derivatives of UU obey Ct−1−δCt^{-1-\delta}. As long as the solution stays in ω\omega, ∣z(t)−(T/t)w∣≤t−1C∫Tts−δ ds≤Ct−δ,∣ξ(t)−η∣≤C∫Tts−1−δ ds≤CT−δ.(14) \begin{gathered} |z(t)-(T/t)w|\\ \le t^{-1}C\int_T^t s^{-\delta}\,ds\le Ct^{-\delta},\\ |\xi(t)-\eta|\\ \le C\int_T^t s^{-1-\delta}\,ds\le CT^{-\delta}. \end{gathered} \tag{14} The contraction tube {(sw,η):(w,η)∈ω′‾, 0≤s≤1}\{(sw,\eta):(w,\eta)\in\overline{\omega'},\,0\le s\le1\} is a compact subset of ω\omega. Choose a positive distance from it to the complement. For sufficiently large TT, (14) keeps the solution in a fixed compact interior neighborhood of that tube. A finite endpoint of existence would have a limit in this compact neighborhood, because its vector field is bounded on the corresponding finite time interval; the local contraction argument extends it. Hence the solution exists for all t≥Tt\ge T. This also proves the two low-order estimates when α=0\alpha=0.

For a first data derivative Yα=(zα,ξα)Y_\alpha=(z_\alpha,\xi_\alpha), the equations are zα′=−zα/t+Uξξξα+Uξzzα,ξα′=−Uzξξα−Uzzzα.(15) \begin{gathered} z_\alpha'=-z_\alpha/t+U_{\xi\xi}\xi_\alpha+U_{\xi z}z_\alpha,\\ \xi_\alpha'=-U_{z\xi}\xi_\alpha-U_{zz}z_\alpha. \end{gathered} \tag{15} All Hessian entries are bounded by Ct1−m(2)=Ct−1−δCt^{1-m(2)}=Ct^{-1-\delta}. In the squared Euclidean norm of all first data derivatives, the contribution of −zα/t-z_\alpha/t is nonpositive. Thus N′(t)≤Ct−1−δN(t),N(T)=2n.(16) N'(t)\le Ct^{-1-\delta}N(t),\qquad N(T)=\sqrt{2n}. \tag{16} The integral of the coefficient from TT to infinity is bounded independently of T≥1T\ge1, so N(t)≤CN(t)\le C. Equation (15) then gives ∣(tzα)′∣≤Ct−δ,∣ξα′∣≤Ct−1−δ.(17) |(tz_\alpha)'|\le Ct^{-\delta},\qquad |\xi_\alpha'|\le Ct^{-1-\delta}. \tag{17} Their integrations prove the two estimates for ∣α∣=1|\alpha|=1.

Suppose all data derivatives below order k≥2k\ge2 have been bounded. In particular their norms are at most Cta(j)Ct^{a(j)} at order j<kj<k. Differentiating the equations kk times gives (15) for the highest derivative, with additional terms FαF_\alpha. Each such term has an outer derivative of ∇U\nabla U of order q≥2q\ge2, bounded by Ctμ(q)−1Ct^{\mu(q)-1}, times lower data derivatives whose positive orders sum to kk. By (10), ∣Fα∣≤Cktμ(k)−1.(18) |F_\alpha|\le C_k t^{\mu(k)-1}. \tag{18} The combined highest-derivative norm consequently satisfies Nk′(t)≤Ct−1−δNk(t)+Cktμ(k)−1,Nk(T)=0.(19) \begin{gathered} N_k'(t)\le Ct^{-1-\delta}N_k(t)+C_k t^{\mu(k)-1},\\ N_k(T)=0. \end{gathered} \tag{19} The norm inequality at zeros follows, for example, by first using (Nk2+ε2)1/2(N_k^2+\varepsilon^2)^{1/2} and then letting ε↓0\varepsilon\downarrow0. Variation of constants, with the integrable coefficient, gives a bounded NkN_k if k<κk<\kappa, since μ(k)=−δ\mu(k)=-\delta. If k≥κk\ge\kappa, its positive exponent gives Nk(t)≤Cktμ(k)N_k(t)\le C_k t^{\mu(k)}. For the remaining low-order refinements 2≤k<κ2\le k<\kappa, return to the differentiated equations: their Hessian terms have size Ct−1−δCt^{-1-\delta} by the bounded NkN_k, and so do their remainders by (18). Therefore ∣(tzα)′∣≤Ct−δ,∣ξα′∣≤Ct−1−δ.(20) |(tz_\alpha)'|\le Ct^{-\delta},\qquad |\xi_\alpha'|\le Ct^{-1-\delta}. \tag{20} Their initial values vanish at these orders; integration proves the final two lines of (13). This completes the induction and the entire abstract spatial-data lemma.

5. Time derivatives of trajectories starting on the free graph

Theorem 5.1 (mixed time and frequency derivatives). For the Hamilton construction in Section 2, (9) holds. When w=0w=0, for every α\alpha and integer τ>0\tau>0, ∣∂ηα∂tτ(z(t,0,η),ξ(t,0,η))∣≤Cατt∣α∣−m(∣α∣+τ),t≥T.(21) \begin{gathered} |\partial_\eta^\alpha\partial_t^\tau(z(t,0,\eta),\xi(t,0,\eta))|\\ \le C_{\alpha\tau}t^{|\alpha|-m(|\alpha|+\tau)},\\ t\ge T. \end{gathered} \tag{21} The constants remain independent of sufficiently large TT. Here η\eta ranges over any compact subset of the regular-velocity region, with (0,η)(0,\eta) in the initial set of Theorem 4.1. The domain can be chosen as a product of a small ball in zz and a bounded open frequency neighborhood on which ∣∇P0∣≥c|\nabla P_0|\ge c; it is then stable under contraction of zz, and (8)–(9) hold there uniformly.

Proof. First prove the equivalent Euler estimate ∣∂ηαEτ(z,ξ)∣≤Cατt∣α∣+τ−m(∣α∣+τ)=Cατtμ(∣α∣+τ−1).(22) \begin{gathered} |\partial_\eta^\alpha E^\tau(z,\xi)|\\ \le C_{\alpha\tau}t^{|\alpha|+\tau-m(|\alpha|+\tau)}\\ =C_{\alpha\tau}t^{\mu(|\alpha|+\tau-1)}. \end{gathered} \tag{22} The equations are Ez=−z+tUξEz=-z+tU_\xi, Eξ=−tUzE\xi=-tU_z. By (13) with w=0w=0, every pure η\eta derivative of zz is bounded by Ctμ(∣α∣)Ct^{\mu(|\alpha|)}; pure derivatives of the whole pair are bounded by Cta(∣α∣)Ct^{a(|\alpha|)}. By (9), every joint derivative of order qq in (z,ξ,log⁡t)(z,\xi,\log t) of tUξtU_\xi or tUztU_z is bounded by Ctμ(q)Ct^{\mu(q)}.

For τ=1\tau=1, apply the finite composition rule following (10) to the variable η\eta. It bounds ∂ηα(t∇U)\partial_\eta^\alpha(t\nabla U) by Ctμ(∣α∣)Ct^{\mu(|\alpha|)}, and the −z-z term has that same bound. This proves (22), including α=0\alpha=0.

Induct on τ\tau, with all η\eta derivative orders at each preceding time order already available. Apply ∂ηαEτ−1\partial_\eta^\alpha E^{\tau-1} to the Euler equations. Let r=∣α∣+τ−1r=|\alpha|+\tau-1. All derivatives of the inner map (η,log⁡t)↦(z,ξ,log⁡t)(\eta,\log t)\mapsto(z,\xi,\log t) used in this expression have time order below τ\tau. Their total positive derivative order jj is bounded by Cta(j)Ct^{a(j)}: for positive time order the induction gives exponent μ(j−1)≤a(j)\mu(j-1)\le a(j); for zero time order use (13). The last coordinate has first derivative one and all higher derivatives zero, consistent with a(1)=0a(1)=0.

The finite composition rule therefore bounds the differentiated t∇Ut\nabla U by Ctμ(r)Ct^{\mu(r)}. If τ≥2\tau\ge2, the differentiated −z-z is bounded by Ctμ(r−1)≤Ctμ(r)Ct^{\mu(r-1)}\le Ct^{\mu(r)}, by induction. The case τ=1\tau=1 was already proved. This gives (22) at the new time order.

Finally tτ∂tτ=E(E−1)⋯(E−τ+1).(23) t^\tau\partial_t^\tau=E(E-1)\cdots(E-\tau+1). \tag{23} This is proved by induction from E(tℓv)=tℓ(E+ℓ)vE(t^\ell v)=t^\ell(E+\ell)v. It is a finite polynomial in positive Euler powers. The exponent ∣α∣+ℓ−m(∣α∣+ℓ)|\alpha|+\ell-m(|\alpha|+\ell) increases with ℓ\ell, so each term for 1≤ℓ≤τ1\le\ell\le\tau is controlled by the bound with ℓ=τ\ell=\tau, for t≥1t\ge1. Divide by tτt^\tau to obtain (21). Multiplication by the unit complex factors in D=−i∂D=-i\partial leaves the derivative estimates unchanged.

The time assertion uses the joint estimate (9). Spatial bounds (8) for an independently time-dependent UU alone do not imply it. Exercise 5 gives an explicit example and explains the role of zero initial displacement.

Use the conclusion

Use the exact trajectory to test the factor T/tT/t, then check which mixed time estimates require zero initial displacement. Do not infer those estimates from spatial data derivatives alone.

6. Exercises with complete solutions

Exercise 1 — Basic — scaled Hamilton equations and an exact line model.

For HL(x,ξ)=P0(ξ)+VL(x,ξ)H_L(x,\xi)=P_0(\xi)+V_L(x,\xi), set x=t(∇P0(ξ)+z)x=t(\nabla P_0(\xi)+z) and U=t−1VL(t(∇P0(ξ)+z),ξ)U=t^{-1}V_L(t(\nabla P_0(\xi)+z),\xi). Derive both scaled equations, including their signs. On the line, take P0(ξ)=ξP_0(\xi)=\xi and VL(x,ξ)=v(x)=a(1+x2)−δ/2V_L(x,\xi)=v(x)=a(1+x^2)^{-\delta/2}. Solve the flow with (z(T),ξ(T))=(w,η)(z(T),\xi(T))=(w,\eta), ∣w∣<1/2|w|<1/2, and verify its low-order data estimates independently of T≥1T\ge1.

Solution 1. The original equations are x′=P0′(ξ)+VL,ξx'=P_0'(\xi)+V_{L,\xi} and ξ′=−VL,x\xi'=-V_{L,x}. Differentiating the coordinate substitution gives x′=P0′(ξ)+z+t(P0′′(ξ)ξ′+z′).(24) x'=P_0'(\xi)+z+t(P_0''(\xi)\xi'+z'). \tag{24} On the other hand Uz=VL,xU_z=V_{L,x} and Uξ=t−1VL,ξ+P0′′(ξ)VL,xU_\xi=t^{-1}V_{L,\xi}+P_0''(\xi)V_{L,x}. Substitute ξ′=−VL,x\xi'=-V_{L,x} into the first identity and rearrange: z′=−z/t+Uξ,ξ′=−Uz.(25) z'=-z/t+U_\xi,\qquad \xi'=-U_z. \tag{25} The P0′′P_0'' term has a plus sign in UξU_\xi; the negative ξ′\xi' in the coordinate derivative is what produces it.

In the line model x′=1x'=1, so x(t)=t+Twx(t)=t+Tw and z(t)=Tw/tz(t)=Tw/t. Integration of ξ′=−v′(t+Tw)\xi'=-v'(t+Tw) gives ξ(t,w,η)=η−v(t+Tw)+v(T(1+w)).(26) \xi(t,w,\eta)=\eta-v(t+Tw)+v(T(1+w)). \tag{26} Because t+Tw≥t/2t+Tw\ge t/2 and T(1+w)≥T/2T(1+w)\ge T/2, ∣ξ−η∣≤CT−δ|\xi-\eta|\le CT^{-\delta}. Also ∂wξ=−Tv′(t+Tw)+Tv′(T(1+w)),(27) \partial_w\xi=-Tv'(t+Tw)+Tv'(T(1+w)), \tag{27} whose modulus is at most C[Tt−1−δ+T−δ]≤CT−δC[Tt^{-1-\delta}+T^{-\delta}]\le CT^{-\delta}. The η\eta-derivative of ξ−η\xi-\eta is zero. For zz, the only nonzero positive data derivative is ∂wz=T/t\partial_w z=T/t; every η\eta-derivative and higher derivative is zero. These give exactly the low-order flow estimates.

More generally ∂wk(ξ−η)=Tk[−v(k)(t+Tw)+v(k)(T(1+w))]\partial_w^k(\xi-\eta)=T^k[-v^{(k)}(t+Tw)+v^{(k)}(T(1+w))], bounded by CT−δCT^{-\delta} at every fixed kk. These bounds are stronger than the permitted positive high-order growth. The constants depend on a,δ,ka,\delta,k, but not on T,tT,t in the stated range.

Exercise 2 — Intermediate — compute all derivative exponents.

Take κ=2\kappa=2, δ=1/5\delta=1/5, with the exact sequence m(j)=j+δm(j)=j+\delta for j≤2j\le2 and m(j)=1+(1+δ)j/2m(j)=1+(1+\delta)j/2 for j≥2j\ge2. Compute the first four μ(k)=k+1−m(k+1)\mu(k)=k+1-m(k+1), and give the bounds for the second and third data jets. With w=0w=0, give the bounds for ∂t2(z,ξ)\partial_t^2(z,\xi), ∂ηα∂t(z,ξ)\partial_\eta^\alpha\partial_t(z,\xi) at ∣α∣=2|\alpha|=2, and ∂ηα∂t2(z,ξ)\partial_\eta^\alpha\partial_t^2(z,\xi) at ∣α∣=3|\alpha|=3. Explain why a high data derivative can grow while its time derivative decays.

Solution 2. The joining values agree: m(2)=11/5m(2)=11/5. The next values are m(3)=14/5m(3)=14/5, m(4)=17/5m(4)=17/5, m(5)=4m(5)=4. Thus μ(0)=μ(1)=−1/5,μ(2)=1/5,μ(3)=3/5.(28) \begin{gathered} \mu(0)=\mu(1)=-1/5,\\ \mu(2)=1/5,\quad \mu(3)=3/5. \end{gathered} \tag{28} The second data jet is O(t1/5)O(t^{1/5}), and the third is O(t3/5)O(t^{3/5}), uniformly in sufficiently large initial TT. The first-order corrections ξ−η\xi-\eta still have O(T−1/5)O(T^{-1/5}) data derivatives, while the zz-derivative retains its explicit T/tT/t initial term plus O(t−1/5)O(t^{-1/5}).

For positive time order the formula is t∣α∣−m(∣α∣+τ)t^{|\alpha|-m(|\alpha|+\tau)}. It gives, respectively, ∂t2(z,ξ)=O(t−11/5),∂ηα∂t(z,ξ)=O(t−4/5),∂ηα∂t2(z,ξ)=O(t−1)(29) \begin{gathered} \partial_t^2(z,\xi)=O(t^{-11/5}),\\ \partial_\eta^\alpha\partial_t(z,\xi)=O(t^{-4/5}),\\ \partial_\eta^\alpha\partial_t^2(z,\xi)=O(t^{-1}) \end{gathered} \tag{29} at the specified orders. In the second estimate the same second data jet that can grow like t1/5t^{1/5} has a first time derivative bounded by t−4/5t^{-4/5}. Its derivative is integrable on no infinite half-line at that exponent, so there is no conflict with slow growth. The estimate records a derivative of a growing jet; it does not assert that all high jets remain bounded.

Exercise 3 — Intermediate — the compact contraction tube.

Let ω\omega be an open flow domain stable under contractions of zz, and ω′⋐ω\omega'\Subset\omega. Assume the first scaled forcing derivatives are bounded by Ct−1−δCt^{-1-\delta}, 0<δ<10<\delta<1. Prove global future existence of every flow starting in ω′\omega' at all sufficiently large TT, with one threshold for the entire initial set. Identify where contraction of zz, compactness and integrability are used.

Solution 3. On every existing solution, integration of (tz)′=tUξ(tz)'=tU_\xi gives ∣z(t)−(T/t)w∣≤Ct∫Tts−δ ds≤Ct−δ.(30) |z(t)-(T/t)w| \le \frac C t\int_T^t s^{-\delta}\,ds \le C t^{-\delta}. \tag{30} Integration of ξ′=−Uz\xi'=-U_z gives ∣ξ(t)−η∣≤C∫T∞s−1−δ ds≤CT−δ|\xi(t)-\eta|\le C\int_T^\infty s^{-1-\delta}\,ds \le CT^{-\delta}. The free comparison points ((T/t)w,η)((T/t)w,\eta) lie in C={(sw,η):(w,η)∈ω′‾, 0≤s≤1}.(31) \mathcal C=\{(sw,\eta):(w,\eta)\in\overline{\omega'},\ 0\le s\le1\}. \tag{31} The contraction hypothesis puts the whole set in ω\omega; continuity makes it compact. Choose a fixed closed neighborhood of C\mathcal C inside ω\omega and a positive smaller margin. Both errors are at most CT−δCT^{-\delta}, so one sufficiently large TT keeps every solution inside that same neighborhood.

Local existence and uniqueness follow from the short-interval integral contraction for the smooth vector field. If a maximal future endpoint were finite, the vector field would be bounded on this compact neighborhood and on its finite time interval. The solution would be Cauchy at the endpoint and have a limit in the neighborhood. Local existence from that limit would extend it, a contradiction.

Contraction of zz places the free comparison curve inside the domain. Compactness gives a uniform positive margin for all initial data. The integral of s−1−δs^{-1-\delta} gives the uniformly small frequency displacement, while the t−1t^{-1} integrating factor for zz converts the nonintegrable s−δs^{-\delta} input into a decaying t−δt^{-\delta} error. These facts, not boundedness of an arbitrary spatial set, give the uniform threshold.

Exercise 4 — Advanced — close the full high-data-derivative induction.

For the exact general κ≥2\kappa\ge2 sequence and 0<δ<1/(κ+1)0<\delta<1/(\kappa+1), prove μ(q)+∑i=1qmax⁡(μ(ki),0)≤μ(k),ki≥1,∑ki=k.(32) \begin{gathered} \mu(q)+\sum_{i=1}^q\max(\mu(k_i),0)\le\mu(k),\\ k_i\ge1,\quad\sum k_i=k. \end{gathered} \tag{32} Use it to bound every nonlinear remainder in the kk-th differentiated scaled equation and derive both the high-order growth bound and the low-order refinement.

Solution 4. Set θ=(1−δ)/κ\theta=(1-\delta)/\kappa. For j<κj<\kappa, μ(j)=−δ\mu(j)=-\delta; for j≥κj\ge\kappa, μ(j)=θ(j+1)−1>0\mu(j)=\theta(j+1)-1>0. If k<κk<\kappa, all the positive parts are zero and the inequality is equality. If k≥κk\ge\kappa but all ki<κk_i<\kappa, it follows from the monotonicity μ(q)≤μ(k)\mu(q)\le\mu(k).

Otherwise let ℓ≥1\ell\ge1 count the ki≥κk_i\ge\kappa. The small indices are at least one, so their removal leaves ∑largeki≤k−q+ℓ\sum_{\rm large}k_i\le k-q+\ell. Therefore ∑max⁡(μ(ki),0)≤θ(k−q+2ℓ)−ℓ\sum\max(\mu(k_i),0)\le\theta(k-q+2\ell)-\ell. If q≥κq\ge\kappa, adding μ(q)\mu(q) gives at most μ(k)+ℓ(2θ−1)≤μ(k)\mu(k)+\ell(2\theta-1)\le\mu(k). If q<κq<\kappa, subtracting μ(k)\mu(k) from the resulting bound gives at most 1−δ−θ(q+1)+ℓ(2θ−1)≤−δ−θ(q−1)≤01-\delta-\theta(q+1)+\ell(2\theta-1) \le-\delta-\theta(q-1)\le0. This proves every partition case.

In a nonlinear remainder at total data order kk, an outer derivative of ∇U\nabla U has order q≥2q\ge2, hence size tμ(q)−1t^{\mu(q)-1}. Its qq inner derivatives have positive orders ki<kk_i<k summing to kk, hence size at most tmax⁡(μ(ki),0)t^{\max(\mu(k_i),0)} by induction. The proved partition inequality gives an O(tμ(k)−1)O(t^{\mu(k)-1}) remainder.

The highest derivative enters linearly with a Hessian coefficient bounded by Ct−1−δCt^{-1-\delta}, and damping −zk/t-z_k/t, which has nonpositive contribution to squared norm. Its norm thus satisfies Nk′≤Ct−1−δNk+Cktμ(k)−1,Nk(T)=0(33) N_k'\le Ct^{-1-\delta}N_k+C_k t^{\mu(k)-1},\qquad N_k(T)=0 \tag{33} for k≥2k\ge2. Variation of constants has uniformly bounded amplification because the Hessian coefficient is integrable. If k≥κk\ge\kappa, the positive exponent integrates to O(tμ(k))O(t^{\mu(k)}). If 2≤k<κ2\le k<\kappa, its negative exponent gives bounded norm. Return to the two differential components in the latter case: both their Hessian inputs and nonlinear remainders are O(t−1−δ)O(t^{-1-\delta}). Hence ∣(tzk)′∣≤Ct−δ|(tz_k)'|\le Ct^{-\delta}, ∣ξk′∣≤Ct−1−δ|\xi_k'|\le Ct^{-1-\delta}. Integrating from their zero initial values gives zk=O(t−δ)z_k=O(t^{-\delta}) and ξk=O(T−δ)\xi_k=O(T^{-\delta}), the required refinements. Orders zero and one are covered by the direct integration and first-variation argument.

Exercise 5 — Advanced — the exact hypotheses for time derivatives.

Under the mixed outer estimate (9), prove the positive-time derivative bound with w=0w=0 from the Euler equations and the partition inequality. Explain both why w=0w=0 is needed for constants independent of TT, and why spatial estimates on an arbitrary time-dependent UU do not suffice.

Solution 5. Write E=t∂tE=t\partial_t. The equations are Ez=−z+tUξEz=-z+tU_\xi, Eξ=−tUzE\xi=-tU_z. Every total derivative of order qq in (z,ξ,log⁡t)(z,\xi,\log t) of t∇Ut\nabla U is O(tμ(q))O(t^{\mu(q)}), by (9). With zero initial ww, all pure η\eta-derivatives of zz are O(tμ(∣α∣))O(t^{\mu(|\alpha|)}), and those of the whole pair are O(ta(∣α∣))O(t^{a(|\alpha|)}), a=max⁡(μ,0)a=\max(\mu,0). The finite composition rule proves the desired bound for one Euler derivative.

Induct on the positive Euler order τ\tau, allowing all η\eta orders at each preceding time order. In ∂ηαEτ−1(t∇U)\partial_\eta^\alpha E^{\tau-1}(t\nabla U), all inner time derivatives have order less than τ\tau and are bounded by ta(j)t^{a(j)} at total derivative order jj. The appended coordinate log⁡t\log t has first derivative one and higher derivatives zero, also fitting that bound. The partition inequality gives ∣∂ηαEτ(z,ξ)∣≤Ctμ(∣α∣+τ−1).(34) |\partial_\eta^\alpha E^\tau(z,\xi)| \le Ct^{\mu(|\alpha|+\tau-1)}. \tag{34} The differentiated −z-z term has exponent μ(∣α∣+τ−2)\mu(|\alpha|+\tau-2) when τ≥2\tau\ge2, which is no larger. The first Euler order used its pure-data bound. Now tτ∂tτ=E(E−1)⋯(E−τ+1)t^\tau\partial_t^\tau=E(E-1)\cdots(E-\tau+1). This finite polynomial and monotonicity of j−m(j)j-m(j) give ∣∂ηα∂tτ(z,ξ)∣≤Ct∣α∣−m(∣α∣+τ).(35) |\partial_\eta^\alpha\partial_t^\tau(z,\xi)| \le Ct^{|\alpha|-m(|\alpha|+\tau)}. \tag{35}

For the necessity of the zero displacement, even U=0U=0 gives z=Tw/tz=Tw/t. At t=Tt=T, ∣∂tz∣=∣w∣/T|\partial_tz|=|w|/T, whereas the claimed uniform bound would be CT−1−δCT^{-1-\delta}. For fixed w≠0w\ne0, no TT-independent constant makes this true.

For the time hypothesis, take U=t−1−δsin⁡(t2)F(ξ)U=t^{-1-\delta}\sin(t^2)F(\xi), independent of zz, with F′(η)≠0F'(\eta)\ne0 in a compact frequency region. Every spatial derivative obeys (8), and ξ=η\xi=\eta. With w=0w=0, z=t−1F′(η)∫Tts−δsin⁡(s2) ds.(36) z=t^{-1}F'(\eta)\int_T^t s^{-\delta}\sin(s^2)\,ds. \tag{36} The integral is bounded as t→∞t\to\infty: substitute r=s2r=s^2 and integrate the decaying amplitude against sin⁡r\sin r by parts. Differentiating the equation for z′z' gives z′′=2F′(η)t−δcos⁡(t2)−(2+δ)F′(η)t−2−δsin⁡(t2)+2z/t2.(37) \begin{aligned} z''&=2F'(\eta)t^{-\delta}\cos(t^2)\\ &\quad -(2+\delta)F'(\eta)t^{-2-\delta}\sin(t^2)\\ &\quad +2z/t^2. \end{aligned} \tag{37} Along t2=2πjt^2=2\pi j its leading term is nonzero, while the last two terms are O(t−2−δ)+O(t−3)O(t^{-2-\delta})+O(t^{-3}). Thus it cannot obey the required O(t−2−δ)O(t^{-2-\delta}) second-time-derivative estimate. This explicitly time-dependent UU is not the actual time-independent Hamilton coefficient construction. That construction supplies (9), which is the hypothesis used in the proof.

References

[T] Gerald Teschl, Ordinary Differential Equations and Dynamical Systems, free author's preliminary edition, April 2012, §§2.2, 2.4 and 2.6: Theorem 2.2, Lemma 2.7, Theorem 2.10 and Lemma 2.14.

[O] Sung-Jin Oh, Lecture Notes for Math 222A, free evolving lecture notes, University of California, Berkeley, Fall 2023, §2.4.1, pp. 23–24, equation (2.20).

[HW] Lars Hörmander, The existence of wave operators in scattering theory, freely readable journal scan, 1976, §3, pp. 79–82, Lemmas 3.6–3.7.