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Mathlib.Analysis.Convex.Cone.InnerDual

Convex cones in inner product spaces #

We define Set.innerDualCone to be the cone consisting of all points y such that for all points x in a given set 0 ≤ ⟪ x, y ⟫.

Main statements #

We prove the following theorems:

The dual cone #

The dual cone is the cone consisting of all points y such that for all points x in a given set 0 ≤ ⟪ x, y ⟫.

Equations
Instances For
    @[simp]
    theorem mem_innerDualCone {H : Type u_1} [NormedAddCommGroup H] [InnerProductSpace H] (y : H) (s : Set H) :
    y s.innerDualCone xs, 0 inner x y
    @[simp]

    Dual cone of the convex cone {0} is the total space.

    @[simp]

    Dual cone of the total space is the convex cone {0}.

    The inner dual cone of a singleton is given by the preimage of the positive cone under the linear map fun y ↦ ⟪x, y⟫.

    theorem innerDualCone_iUnion {H : Type u_1} [NormedAddCommGroup H] [InnerProductSpace H] {ι : Sort u_2} (f : ιSet H) :
    (⋃ (i : ι), f i).innerDualCone = ⨅ (i : ι), (f i).innerDualCone

    The dual cone of s equals the intersection of dual cones of the points in s.

    The inner dual cone of a pointed cone is a pointed cone.

    Equations
    Instances For
      @[simp]
      theorem PointedCone.mem_dual {H : Type u_1} [NormedAddCommGroup H] [InnerProductSpace H] {C : PointedCone H} {y : H} :
      y C.dual ∀ ⦃x : H⦄, x C0 inner x y

      The inner dual cone of a proper cone is a proper cone.

      Equations
      • C.dual = { toSubmodule := (↑C).dual, isClosed' := }
      Instances For
        @[simp]
        @[simp]
        theorem ProperCone.mem_dual {H : Type u_1} [NormedAddCommGroup H] [InnerProductSpace H] {C : ProperCone H} {y : H} :
        y C.dual ∀ ⦃x : H⦄, x C0 inner x y
        theorem ConvexCone.hyperplane_separation_of_nonempty_of_isClosed_of_notMem {H : Type u_1} [NormedAddCommGroup H] [InnerProductSpace H] [CompleteSpace H] (K : ConvexCone H) (ne : (↑K).Nonempty) (hc : IsClosed K) {b : H} (disj : bK) :
        ∃ (y : H), (∀ xK, 0 inner x y) inner y b < 0

        This is a stronger version of the Hahn-Banach separation theorem for closed convex cones. This is also the geometric interpretation of Farkas' lemma.

        @[deprecated ConvexCone.hyperplane_separation_of_nonempty_of_isClosed_of_notMem (since := "2025-05-24")]
        theorem ConvexCone.hyperplane_separation_of_nonempty_of_isClosed_of_nmem {H : Type u_1} [NormedAddCommGroup H] [InnerProductSpace H] [CompleteSpace H] (K : ConvexCone H) (ne : (↑K).Nonempty) (hc : IsClosed K) {b : H} (disj : bK) :
        ∃ (y : H), (∀ xK, 0 inner x y) inner y b < 0

        Alias of ConvexCone.hyperplane_separation_of_nonempty_of_isClosed_of_notMem.


        This is a stronger version of the Hahn-Banach separation theorem for closed convex cones. This is also the geometric interpretation of Farkas' lemma.

        The inner dual of inner dual of a non-empty, closed convex cone is itself.

        @[simp]

        The dual of the dual of a proper cone is itself.

        This is a relative version of ConvexCone.hyperplane_separation_of_nonempty_of_isClosed_of_notMem, which we recover by setting f to be the identity map. This is also a geometric interpretation of the Farkas' lemma stated using proper cones.

        @[deprecated ProperCone.hyperplane_separation_of_notMem (since := "2025-05-24")]

        Alias of ProperCone.hyperplane_separation_of_notMem.