Ported for Lean Pool: imports relocated and code adapted to Lean/Mathlib v4.34.0.
Line subgradient lift interfaces #
A scalar subgradient of a line restriction is represented by an ambient subgradient.
Equations
- AleksandrovDifferentiability.LineSubgradientLiftsToAmbient s u x z t q = ∃ (p : E), AleksandrovDifferentiability.SubgradientOn s u (x + t • z) p ∧ q = inner ℝ p z
Instances For
Functional form of LineSubgradientLiftsToAmbient.
This is the form naturally produced by a geometric Hahn-Banach/separation argument: a continuous
linear functional supports the epigraph of u at x + t • z and has value q on the line
direction z. In complete real inner-product spaces, Fréchet-Riesz converts this functional
form into the vector-valued subgradient form used elsewhere in the project.
Equations
Instances For
An ambient subgradient at a point on the line gives a vector-valued lift of its directional pairing.
An ambient subgradient at a point on the line gives a functional lift of its directional pairing.
If a scalar slope is attained by an ambient subgradient in direction z, then it has a
functional lift.
If a scalar slope is attained by an ambient subgradient in direction z, then it has a
vector-valued lift.
Right-derivative endpoint attainment by an ambient subgradient gives the corresponding functional lift.
Right-derivative endpoint attainment by an ambient subgradient gives the corresponding vector-valued lift.
Left-derivative endpoint attainment by an ambient subgradient gives the corresponding functional lift.
Left-derivative endpoint attainment by an ambient subgradient gives the corresponding vector-valued lift.
A one-dimensional subgradient of a line restriction is exactly an affine minorant along that line. This is the line datum that the Hahn-Banach/separation step must extend to the ambient domain.
If an ambient supporting functional has the prescribed value on the line direction, it extends the line affine minorant determined by a line subgradient. This records the compatibility between the line-subgradient datum and the functional lift target.
A vector-valued ambient subgradient lift gives the functional lift by the Riesz embedding
p ↦ (y ↦ p · y). The reverse implication uses Fréchet-Riesz and therefore requires
completeness; see LineSubgradientLiftsToAmbientFunctional.to_lineSubgradientLiftsToAmbient.
Convex combinations of vector-valued line-subgradient lifts are again vector-valued lifts. This records the interval-convexity of directional values of ambient subgradients.
Convex combinations of functional line-subgradient lifts are again functional lifts.
If the left and right derivatives of a convex line restriction have functional ambient lifts, then every one-dimensional subgradient slope has a functional ambient lift.
Vector-valued version of
ConvexOn.lineSubgradient_liftsToAmbientFunctional_of_leftRightDeriv_lift.
Eventual functional lift of all line subgradients from eventual lifts of the left and right derivatives.
Eventual vector-valued lift of all line subgradients from eventual lifts of the left and right derivatives.
Eventual functional lift of all line subgradients from endpoint attainment of the left and right derivatives by ambient subgradients. This is the form expected from the endpoint support-function/Hahn-Banach step.
Eventual vector-valued lift of all line subgradients from endpoint attainment of the left and right derivatives by ambient subgradients.
A functional lift gives the vector-valued ambient subgradient lift by Fréchet-Riesz.
Eventual version of the Fréchet-Riesz conversion from functional line-subgradient lifts to vector-valued ambient subgradient lifts.
Eventual conversion from vector-valued line-subgradient lifts to functional lifts.
Pointwise functional lift of the left derivative, once all line subgradients are known to lift. Convexity supplies the fact that the left derivative is itself a one-dimensional subgradient.
Pointwise vector-valued lift of the left derivative, once all line subgradients are known to lift.
Pointwise functional lift of the right derivative, once all line subgradients are known to lift. Convexity supplies the fact that the right derivative is itself a one-dimensional subgradient.
Pointwise vector-valued lift of the right derivative, once all line subgradients are known to lift.
Eventual functional lift of the left derivative along short segments.
Eventual vector-valued lift of the left derivative along short segments.
Eventual functional lift of the right derivative along short segments. This is the
separation-facing analogue of
ConvexOn.eventually_lineRightDeriv_realized_by_subgradient_of_lineSubgradientLift.
Eventual vector-valued lift of the right derivative along short segments.
If every one-dimensional subgradient along short segments lifts to an ambient subgradient, then the right derivative of the line restriction is realized by an ambient subgradient.
This packages the already-formalized one-dimensional fact
ConvexOn.lineRestriction_rightDeriv_subgradientOn_at: at interior line parameters the right
derivative is itself a line subgradient.