The finite-axis case of prop:aniso:small fails #
Closing argument of Step 2 of the zoom-in of Section sec:aniso:zoom
(eq:aniso:zoom:finite:endpoint and the paragraph after it). In the variables
eq:aniso:zoom:finite:variables the selected point (x_n, t_n) has coordinates
(R, Z, τ) = (r_n/λ_n, 0, -1), and (r_n/λ_n, 0) lies in the compact set [0, A] × {0}. By
eq:aniso:zoom:fields and the chain rule the selected quantity
(-t_n)(|∂_r u_r| + |u_r/r| + |∂_z u_z|)(x_n, t_n) equals
(|∂_R V_n| + |V_n/R| + |∂_Z W_n|)(r_n/λ_n, 0, -1), both quotients extended continuously to the
axis.
The bounds eq:aniso:zoom:derivatives make V_n(·,-1) and W_n(·,-1) bounded in C² on every
compact subset of the closed half-plane with one constant, so along a subsequence they converge
in C¹ on those compact sets. The limits obey ∂_R V⁰ + V⁰/R + ∂_Z W⁰ = 0 and ∂_R W⁰ = 0,
and the endpoint argument CIV.endpoint_tendstoUniformlyOn_triple turns this into the uniform
vanishing eq:aniso:zoom:finite:endpoint on [0, A] × {0}. The selected quantity therefore
tends to zero along the subsequence, contradicting its lower bound c₀ > 0 in
eq:aniso:zoom:selected; that last step is CIV.false_of_finite_contradiction_data, whose nine
limit and convergence hypotheses are supplied here by the extraction rather than assumed.
Everything here happens at the single time τ = -1: the compactness used is the spatial C¹
compactness CIV.exists_subseq_tendstoUniformlyOn_c1_halfPlane on a fixed time slice, and no
equicontinuity in τ is claimed or needed. The two inputs that carry information from the
equation — the divergence identity of eq:aniso:zoom:finite:identities and the vanishing of
∂_R W_n off the axis, which comes from Ω_n → 0 through the
potential-vorticity identity CIV.zoomOmega_eq — enter as hypotheses on the sequence itself.
The factor 2 in the lower bound is the one produced by
CIV.lt_of_neg_t_mul_meridionalQuantity_selection_lt, which absorbs the axis value of the
quotient u_r/r into the radial derivative; it costs nothing, since all three terms are shown to
vanish.
Evaluation of a convergent sequence of continuous linear maps #
Evaluation at a fixed vector is continuous, so a convergent sequence of continuous linear maps converges at every vector.
The endpoint data extracted from the C² bounds #
The endpoint data of eq:aniso:zoom:finite:endpoint, extracted rather than assumed: a
sequence of smooth meridional fields (V_n, W_n) on the plane which is C²-bounded by one
constant L on every square [0, j+1] × [-(j+1), j+1] for all large n, satisfies the
divergence identity of eq:aniso:zoom:finite:identities off the axis for all large n, and
whose radial derivative ∂_R W_n tends to zero off the axis, has a subsequence along which
(V_n, W_n) converges in C¹ on every such square to a pair (V⁰, W⁰) that is bounded by L
on the open half-plane, divergence free there, and independent of R in its axial component.
The nine conclusions are exactly the nine hypotheses hV, hW, hbdd, hdiv, hWr,
hDVcont, hDWcont, hDVconv, hDWconv of CIV.false_of_finite_contradiction_data, in that
order, with M = L, Vn n = V_{φ n}, DVn n = ∇V_{φ n} and DWn n = ∇W_{φ n}.
The endpoint vanishing on the axis segment #
eq:aniso:zoom:finite:endpoint on the segment [0, A] × {0}: along the subsequence of
CIV.exists_subseq_finite_endpoint_data, the radial derivative ∂_R V_n, the axial derivative
∂_Z W_n and the quotient V_n/R all tend to zero uniformly there, the axis included.
The contradiction #
Step 2 of prop:aniso:small closes: a sequence of meridional fields (V_n, W_n) with the
endpoint data of CIV.exists_subseq_finite_endpoint_data cannot satisfy the selection bound
eq:aniso:zoom:selected at radii R_n ∈ [0, A]. The extraction supplies exactly the nine
convergence and limit hypotheses of CIV.false_of_finite_contradiction_data, which then
produces the contradiction.
The form produced by the selection bound #
The same contradiction, with the selected quantity written through the repository's dr,
dz of the space-time fields at the selected time τ = -1: this is the form in which
CIV.lt_of_neg_t_mul_meridionalQuantity_selection_lt delivers the lower bound
eq:aniso:zoom:selected, with Vfield n = zoomV λ_n h z_n u and Wfield n = zoomW λ_n h z_n u
and their τ = -1 slices as Vseq, Wseq.