Ported for Lean Pool: imports relocated and code adapted to Lean/Mathlib v4.34.0.
Convex jet Hessian estimates #
For a function convex on a closed ball, the Hessian component of an ordinary superjet at an interior point of that ball has nonnegative quadratic form in every direction.
In quantified mathematical form, if g is convex on closedBall x0 r,
x ∈ ball x0 r, (p, X) ∈ J^{2,+}_{R^n} g(x), and v ∈ R^n, then
0 ≤ ⟪Xv, v⟫.
For a function convex on a closed ball, a Hermitian Hessian component of an ordinary superjet at an interior point is nonnegative in the Loewner order.
For a convex function, the Hessian component of an ordinary superjet has nonnegative quadratic form in every direction.
In quantified mathematical form, if g : R^n -> R is convex, if (p, X)
belongs to J^{2,+}_{R^n} g(x), and if v ∈ R^n, then
0 ≤ ⟪Xv, v⟫.
For a convex function, a Hermitian Hessian component of an ordinary superjet is nonnegative in the Loewner order.
For a convex function, the Hessian component of a closed superjet has nonnegative quadratic form in every direction.
In quantified mathematical form, if g : R^n -> R is convex, if (p, X)
belongs to \overline J^{2,+}_{R^n} g(x), and if v ∈ R^n, then
0 ≤ ⟪Xv, v⟫.
For a convex function, a Hermitian Hessian component of a closed superjet is nonnegative in the Loewner order.