Operator-norm bounds on ℝ × ℝ from directional components #
ℝ × ℝ carries the sup norm ‖(a, b)‖ = max |a| |b| (Prod.norm_def), whose dual is the
ℓ¹ norm: a continuous linear functional on ℝ × ℝ is controlled by the sum of its two
directional values. This file records that fact, once for a functional into any normed
space, and derives the analogous bound for a bilinear form (a continuous linear map into a
space of continuous linear maps) by applying it twice. Neither theorem mentions any
zoomed field; both are used to convert the pointwise radial/axial derivative bounds of
eq:aniso:zoom:derivatives into the operator-norm bounds the finite-axis closures of
FiniteContradictionClosure.lean consume.
A continuous linear functional out of ℝ × ℝ (sup norm) is bounded by the sum of the
absolute values of its two directional values L (1, 0) and L (0, 1): every vector's
coordinates are each bounded by its sup norm.
The bilinear-form analogue, specialised to an iterated Fréchet derivative: the operator
norm of the second derivative of g : ℝ × ℝ → ℝ at y is bounded, by applying
norm_clm_le_norm_apply_add_norm_apply twice (once to the second derivative itself, valued
in the functionals (ℝ × ℝ) →L[ℝ] ℝ, and once to each of the two resulting functionals), by
the sum of the absolute values of its four directional entries. Stating the bound at
fderiv ℝ (fderiv ℝ g) y itself, rather than at a bare universally quantified continuous
linear map, keeps every instance on the operator-norm topology that fderiv itself installs;
a free variable of the bare bilinear type picks up a competing (defeq but not syntactically
equal) topology instance from the plain continuous-linear-map arrow and the two do not unify.