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Two declared linear models worked through: the harmonic flow has zero finite-time growth in every direction, while the repulsive linear model has exact rates ±1 and the positive Lyapunov exponent 1 at its equilibrium

Physical scope

A declared-data check of two physical one-label Cartesian force models with m0=1 kg, ell0=1 m and t0=1 s: F_1,phys=-(m0/t0^2)X and F_2,phys=(m0/t0^2)X, in newtons. The formulas use normalized q=X/ell0, v=t0 V/ell0 and t=T/t0, mass 1 and potentials U_1(q)=||q||^2/2 and U_2(q)=-||q||^2/2 with energy reference E0=m0 ell0^2/t0^2. In this numerical state metric the harmonic derivative is orthogonal, so all finite-time rates and Lyapunov exponents are zero; the repulsive derivative has exact rates plus and minus 1 along its eigendirections, with positive exponent 1 at equilibrium. The corresponding physical rates divide by t0. All data are declared, with no measurement and no claim of chaos.

Example

Declared model data and normalization. Take one label with Q:=R3 and declare physical reference data m0:=1 kg, ℓ0:=1 m, t0:=1 s. For σ1=−1, σ2=1 define physical force maps Fi,phys:R×Q×R3→R3 by Fi,phys(T,X,V)=σi(m0/t02)X, with T in seconds, X in metres, V in metres per second, and outputs in newtons. These are smooth globally state-Lipschitz force maps of Adopted force model: force maps, the equation of motion, additive composition of force contributions and frame covariance with physical mass m0. Put t=T/t0, q=X/ℓ0, v=t0V/ℓ0 and E0=m0ℓ02/t02. Then m0X¨=Fi,phys becomes q′′=σiq, with q′=v, since X¨=(ℓ0/t02)q′′. The normalized force maps are Fi(t,q,v)=Fi,phys(t0t,ℓ0q,(ℓ0/t0)v)/(m0ℓ0/t02)=σiq, with normalized mass m=1. The physical potentials are Ui,phys(X)=−σim0∥X∥22/(2t02); normalizing their energies by E0 gives, in the constant-metric chart Ω:=R3 with M:=I3, they have the potentials U1(q):=12∥q∥22 and U2(q):=−12∥q∥22 of The mechanical first-order field, Lagrangian and energy of a configuration-dependent kinetic metric in a chart. The associated fields and complete motion maps are listed below; e1,e2,e3 denote the coordinate basis, explicitly ej(k)=1 for k=j−1 and 0 otherwise, for k∈{0,1,2} and j∈{1,2,3}. All state and tangent norms below apply to the dimensionless numerical coordinates (q,v).

  1. The harmonic model has field G1(q,v)=(v,−q) and motion map Φt1(q0,v0)=(q0cos⁡t+v0sin⁡t, −q0sin⁡t+v0cos⁡t).
  2. The repulsive linear model has field G2(q,v)=(v,q) and motion map Φt2(q0,v0)=(12(q0+v0)et+12(q0−v0)e−t, 12(q0+v0)et−12(q0−v0)e−t).

For a state a and a nonzero tangent vector u with DaΦt(a)u≠0, the finite-time tangent growth rate is t−1log⁡(∥DaΦt(a)u∥2/∥u∥2); when the forward lifetime is unbounded and its finite limit as t→∞ exists, that limit is the Lyapunov exponent (Finite-time tangent growth rates and Lyapunov exponents of the model's flow: the rate per unit time of a transported deviation, with its existence convention and its limits clauses (i)-(ii)). Both displayed flows are complete, so this lifetime condition holds for each state.

Assertions to check. (i) Both displayed maps are the local flows of their fields; (ii) for the harmonic model DaΦt1(a) is the orthogonal block rotation (cos⁡t I3sin⁡t I3−sin⁡t I3cos⁡t I3), so every finite-time tangent growth rate vanishes and every existing Lyapunov exponent is 0; (iii) for the repulsive model the rates along the directions (e1,−e1) and (e1,e1) are −1 and +1, so the Lyapunov exponent of the equilibrium along the unstable eigenvector is 1.

Facts & Assumptions

Given: the two force maps and their equivalent chart data with M=I3, the displayed candidate flows and the finite-time growth-rate definition of Finite-time tangent growth rates and Lyapunov exponents of a C¹ flow as recorded in Finite-time tangent growth rates and Lyapunov exponents of the model's flow: the rate per unit time of a transported deviation, with its existence convention and its limits.

[L1]

Uniqueness of force-model motions (Local existence and uniqueness for the Newtonian initial-value problem, with the quantitative Picard-Lindelöf cylinder): for the adopted physical force maps, every initial datum has a unique maximal model motion; consequently a globally defined curve that solves the equation with the given initial data is the model's maximal motion. The invertible state and time normalization transfers this uniqueness and maximality to the numerical systems.

[L3]

Pythagorean identity (Parity and the Pythagorean identity for sine and cosine): for every real t, sin⁡2t+cos⁡2t=1.

Verification

technique · direct
1.1givenalgebra

The two fields: for the constant metric M=I3 the mechanical field of The mechanical first-order field, Lagrangian and energy of a configuration-dependent kinetic metric in a chart is G(q,v)=(v,−∇U(q)), giving G1(q,v)=(v,−q) and G2(q,v)=(v,q). These are also the normalized force-model fields of the declared physical F1,phys,F2,phys.

2.1givenstep 1.1L1L2algebra

Harmonic flow: differentiating the displayed Φt1 with respect to t by [L2] gives (q˙,v˙)=(v,−q); at t=0 the map is the identity. By [L1] the displayed map is the force model's maximal flow.

2.2givenstep 1.1L1L2algebra

Repulsive flow: differentiating the displayed Φt2 gives q˙=v(t) and v˙=q(t); at t=0 the map is the identity, so by [L1] it is the force model's maximal flow of G2.

3.1step 2.1givenL2L3algebra

Harmonic growth rates: Φt1 is linear in a=(q0,v0), with derivative DaΦt1(a)=(cos⁡t I3sin⁡t I3−sin⁡t I3cos⁡t I3); writing c=cos⁡t, s=sin⁡t, its transpose times itself has diagonal blocks (c2+s2)I3=I3 by [L3] and off-diagonal blocks csI3−scI3=0, so it is orthogonal, whence ∥DaΦt1(a)u∥2=∥u∥2 for every u≠0. The explicit flow exists for every real time, so the forward lifetime is unbounded, as required by the exponent definition. Therefore r(t,a,u)=t−1log⁡1=0 for every t>0, and the limit defining the Lyapunov exponent exists and equals 0; the variational equation of Linearisation along a motion of the mechanical model: the flow derivative solves the variational equation, with Lipschitz dependence, the constant-metric second-order form, and the conditional finite-time error bound of the linear approximation is satisfied by this derivative matrix, whose columns solve Y˙=DG1Y by step 2.1.

3.2step 2.2givenL2algebra

Repulsive growth rates: for an initial tangent vector (δq,δv) put u:=δq+δv and w:=δq−δv. The derivative flow satisfies δq(t)+δv(t)=etu and δq(t)−δv(t)=e−tw. For each j∈{1,2,3}, input (ej,ej) gives output et(ej,ej) and rate +1, while input (ej,−ej) gives output e−t(ej,−ej) and rate −1. The explicit flow exists for every real time, so the lifetime hypothesis holds and these Lyapunov exponents exist. At the equilibrium a=(0,0) this gives a positive exponent along each unstable coordinate eigenvector.

4.1step 3.1step 3.2givenL1L2algebra∎

Scope check: the chain rule transfers each numerical motion to X(T)=ℓ0q(T/t0) satisfying its physical Newton equation. A rate r per numerical time t becomes r/t0 per physical time T; thus the physical rates are 0 and ±1/t0, and the positive physical exponent is 1/t0. All steps substitute declared normalized data into the chart formulas and the finite-time-rate definition; no step produces a chaotic invariant set, a mixing property or a measurement, and the positive exponent of step 3.2 concerns the linear model at its equilibrium, as the page's counterexample discusses.

Remarks

  • What is genuinely checked. The example verifies that the variational equation holds with the displayed derivative matrices and that the growth rate is invariant under multiplication of the deviation by nonzero scalars (the logarithm of a positive factor cancels against the norm ratio), so the rate is a function of the direction, not of the length of u. Both flows are complete on the declared chart; no domain-escape phenomenon occurs.

  • The unstable direction. For the repulsive model the directions (ej,ej) and (ej,−ej) are exactly the eigendirections of A=DG2(0,0)=(0I3I30), with eigenvalues +1 and −1, respectively, so the rates ±1 are the eigenvalues of the linearisation, in agreement with Hyperbolic linearisation of an equilibrium of the model: exponential dichotomy of the linearised flow, local exponential asymptotic stability in the stable case, and instability in the saddle case clause 1 with c=1.

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