Iterated gradients of a scalar function #
The gradient of a scalar function on a real inner product space E is an E-valued field; its
Fréchet derivative is an E →L[ℝ] E-valued field, and each further derivative adds one
continuous-linear direction on the left. This file names these basis-free target spaces and the
classical chain of derivative fields that lands in them.
TauCeti.IteratedGradient E j is the target after j derivatives of the gradient: E at
j = 0 and E →L[ℝ] IteratedGradient E j at j + 1, with the operator norm.
TauCeti.iteratedGradientChain f j is the corresponding field of f: the gradient at j = 0
and the Fréchet derivative of the previous field at j + 1. Its order-one member is the
derivative of the gradient, which is the Hessian of f represented as an endomorphism of E.
Implementation notes #
The target spaces are produced by the reducible recursion TauCeti.iteratedGradientModel, which
bundles each space with its normed structure in a TauCeti.IteratedGradientModel. Both are public
because TauCeti.IteratedGradient is indexed by them: at a concrete order the space and its
normed, complete structures are recovered by unfolding the recursion rather than by transport.
Main declarations #
TauCeti.IteratedGradient: the basis-free target of an iterated gradient.TauCeti.iteratedGradientChain: the classical derivative fields of a scalar function.TauCeti.contDiffAt_iteratedGradientChain: thejth field of aCⁿfunction isCᵐwhenm + j + 1 ≤ n.TauCeti.hasCompactSupport_iteratedGradientChain: every field of a compactly supported function is compactly supported.
The normed-space data underlying an iterated gradient.
- Space : Type u
The carrier space for the iterated gradient.
- normedAddCommGroup : NormedAddCommGroup self.Space
The normed additive commutative group structure on
Space. - normedSpace : NormedSpace ℝ self.Space
The normed
ℝ-space structure onSpace.
Instances For
The recursively bundled target of an iterated gradient.
Equations
- One or more equations did not get rendered due to their size.
- TauCeti.iteratedGradientModel E 0 = { Space := E, normedAddCommGroup := inst✝¹, normedSpace := inst✝ }
Instances For
The target of an iterated gradient, indexed by the number of derivative directions added
beyond the gradient. At j = 0 this is the gradient vector E; each successor adds one
continuous-linear derivative direction on the left.
Equations
Instances For
The classical derivative fields of a scalar function, in the basis-free nested-linear-map
types TauCeti.IteratedGradient. Index zero is the gradient and each successor is the Fréchet
derivative of the preceding field.
Equations
- TauCeti.iteratedGradientChain f 0 = fun (x : F) => gradient f x
- TauCeti.iteratedGradientChain f j.succ = fderiv ℝ (TauCeti.iteratedGradientChain f j)
Instances For
The jth iterated-gradient field is C^m at a point whenever the scalar function
is C^n there with m + j + 1 ≤ n.
Iterated gradients do not enlarge the topological support of a scalar function. No differentiability assumption is needed.
Every field in the iterated-gradient chain of a compactly supported function has compact support.