Rockafellar, §11: Separation Theorems #
The three notions of separation, the fundamental separation construction, and supporting
hyperplanes. All 16 numbered results of §11 are formalized, in the book's own vocabulary: a
hyperplane is {x | ⟨x, b⟩ = β} with b ≠ 0, and separation is an inclusion of the two sets in
the opposing closed half-spaces.
The section's definitions #
SeparatesRn b β C₁ C₂,SeparatesProperlyRn,SeparatesStrictlyRn,SeparatesStronglyRn— the section's four notions, each carryingb ≠ 0so that{x | ⟨x, b⟩ = β}really is a hyperplane (Theorem 1.3).SeparatesStronglyRnis written as the book writes it, withCᵢ + εBinside the open half-spaces;separatesStronglyRn_iffis the bridge to the backbone's gap definition, and is the substance of Theorem 11.1(c).SeparableProperly,SeparableStrongly— "there exists a hyperplane separatingC₁andC₂properly / strongly", which is what every numbered result of the section is about.IsSupportingHalfSpace b β C— the supporting half-space, bridged to the backbone'sIsSupportingbyisSupportingHalfSpace_iff.
The book quantifies over vectors where the backbone quantifies over continuous linear functionals;
TdafSurface.exists_linFn says the two are the same quantification in ℝⁿ, and every statement
below is over vectors.
Which set lies on which side. Rockafellar's Theorem 11.1 puts C₁ in the upper half-space
and C₂ in the lower one, where the backbone's Separates f c s t puts s below and t above.
The definitions here therefore read Separates (linFn b) β C₂ C₁, so that the inequalities in
every statement below are the book's.
corollary_11_5_2 and corollary_11_7_3 need C non-empty, where the book assumes only
C ≠ ℝⁿ: in ℝ⁰ the empty set is a convex set other than ℝ⁰ and there is no non-zero b at
all, so the conclusion fails. Every other §11 result carries the book's own non-emptiness
hypothesis anyway.
References #
- R. T. Rockafellar, Convex Analysis, Princeton University Press, 1970, §11.
Vectors as linear functions #
linFn and exists_linFn live in TdafSurface/Common/Euclidean.lean; §§13, 14 and 18 want them
too.
The four notions of separation (p. 95) #
Rockafellar, §11 (p. 95). The hyperplane H = {x | ⟨x, b⟩ = β}, b ≠ 0, separates C₁
and C₂: C₁ is contained in the closed half-space {x | ⟨x, b⟩ ≥ β} and C₂ in the opposite
one. Recorded through the backbone's Separates, whose two sets go in the other order.
Equations
- Rockafellar.SeparatesRn b β C₁ C₂ = (b ≠ 0 ∧ Tdaf.ConvexAnalysis.Separates (TdafSurface.linFn b) β C₂ C₁)
Instances For
Rockafellar, §11 (p. 95). H separates C₁ and C₂ properly: it separates them, and
they are not both actually contained in H itself.
Equations
- Rockafellar.SeparatesProperlyRn b β C₁ C₂ = (b ≠ 0 ∧ Tdaf.ConvexAnalysis.SeparatesProperly (TdafSurface.linFn b) β C₂ C₁)
Instances For
Rockafellar, §11 (p. 95). H separates C₁ and C₂ strictly: the two sets belong to
opposing open half-spaces. The book defines this notion and then numbers no result about it.
Equations
- Rockafellar.SeparatesStrictlyRn b β C₁ C₂ = (b ≠ 0 ∧ (∀ x ∈ C₂, ((TdafSurface.pairing n) x) b < β) ∧ ∀ x ∈ C₁, β < ((TdafSurface.pairing n) x) b)
Instances For
Rockafellar, §11 (p. 95). H separates C₁ and C₂ strongly: for some ε > 0,
C₁ + εB is contained in one of the open half-spaces associated with H and C₂ + εB in the
opposite one, where B is the closed Euclidean unit ball.
The book's definition verbatim; separatesStronglyRn_iff identifies it with the backbone's gap
definition, which is condition (c) of Theorem 11.1.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The bridge for SeparatesStronglyRn: the book's εB definition is the backbone's gap
⨆_{C₂} ⟨·, b⟩ < β < ⨅_{C₁} ⟨·, b⟩. Specialises separatesStrongly_iff_exists_closedBall.
Rockafellar, §11. C₁ and C₂ can be separated properly: some hyperplane does it.
Equations
- Rockafellar.SeparableProperly C₁ C₂ = ∃ (b : TdafSurface.Rn n) (β : ℝ), Rockafellar.SeparatesProperlyRn b β C₁ C₂
Instances For
Rockafellar, §11. C₁ and C₂ can be separated strongly: some hyperplane does it.
Equations
- Rockafellar.SeparableStrongly C₁ C₂ = ∃ (b : TdafSurface.Rn n) (β : ℝ), Rockafellar.SeparatesStronglyRn b β C₁ C₂
Instances For
The bridge to the backbone for proper separability. Rockafellar's "there exists a
hyperplane separating C₁ and C₂ properly" is the backbone's
∃ f c, SeparatesProperly f c C₁ C₂: the side-swap is SeparatesProperly.symm and b ≠ 0 is
SeparatesProperly.ne_zero.
The bridge to the backbone for strong separability, exactly as for proper separability.
Theorem 11.1 #
Theorem 11.1, conditions (a) and (b). Let C₁ and C₂ be non-empty sets in
ℝⁿ. There exists a hyperplane separating C₁ and C₂ properly if and only if there exists a
vector b such that
(a) inf {⟨x, b⟩ | x ∈ C₁} ≥ sup {⟨x, b⟩ | x ∈ C₂}, and
(b) sup {⟨x, b⟩ | x ∈ C₁} > inf {⟨x, b⟩ | x ∈ C₂}.
The extrema are taken in EReal, which removes the boundedness side conditions the book leaves
implicit.
Theorem 11.1, condition (c). There exists a hyperplane separating the
non-empty sets C₁ and C₂ strongly if and only if there exists a vector b such that
(c) inf {⟨x, b⟩ | x ∈ C₁} > sup {⟨x, b⟩ | x ∈ C₂}.
The passage from Rockafellar's εB definition to this gap is separatesStronglyRn_iff, which is
the substance of his proof.
Theorem 11.2, the fundamental construction #
Theorem 11.2. Let C be a non-empty relatively open convex set in ℝⁿ, and
let M be a non-empty affine set in ℝⁿ not meeting C. Then there exists a hyperplane H
containing M, such that one of the open half-spaces associated with H contains C.
Stated for relatively open C and a general affine M, where the backbone has the open case and
the single-point case.
Theorem 11.3, the main separation theorem #
Theorem 11.3. Let C₁ and C₂ be non-empty convex sets in ℝⁿ. In order
that there exist a hyperplane separating C₁ and C₂ properly, it is necessary and sufficient
that ri C₁ and ri C₂ have no point in common.
Theorem 11.4 and its corollaries #
Theorem 11.4, in the second of the two forms he gives it: strong separation of
two non-empty convex sets is possible exactly when 0 ∉ cl (C₁ - C₂).
Theorem 11.4. Let C₁ and C₂ be non-empty convex sets in ℝⁿ. In order
that there exist a hyperplane separating C₁ and C₂ strongly, it is necessary and sufficient
that inf {|x₁ - x₂| | x₁ ∈ C₁, x₂ ∈ C₂} > 0.
theorem_11_4_closure is the same statement written as 0 ∉ cl (C₁ - C₂), which is the form the
backbone proves; a positive infimum of |x₁ - x₂| is exactly a ball around the origin missing
C₁ - C₂.
Corollary 11.4.1. Let C₁ and C₂ be non-empty disjoint closed convex sets
in ℝⁿ having no common directions of recession. Then there exists a hyperplane separating C₁
and C₂ strongly.
Corollary 11.4.2. Let C₁ and C₂ be non-empty convex sets in ℝⁿ whose
closures are disjoint. If either set is bounded, there exists a hyperplane separating C₁ and C₂
strongly.
A bounded closed set in ℝⁿ is compact; the book instead deduces this from
Corollary 11.4.1.
Theorem 11.5 and its corollaries #
Theorem 11.5. A closed convex set C is the intersection of the closed
half-spaces which contain it.
Indexed over vectors. The degenerate index b = 0 is harmless: {x | ⟨x, 0⟩ ≤ β} is ℝⁿ
whenever β ≥ 0, the only case in which it contains a non-empty C.
Corollary 11.5.1. Let S be any subset of ℝⁿ. Then cl (conv S) is the
intersection of all the closed half-spaces containing S.
Corollary 11.5.2. Let C be a convex subset of ℝⁿ other than ℝⁿ itself.
Then there exists a closed half-space containing C; in other words, there exists some b ∈ ℝⁿ,
b ≠ 0, such that the linear function ⟨·, b⟩ is bounded above on C.
C.Nonempty is added to the book's hypotheses — see the module docstring.
Theorem 11.6, supporting hyperplanes #
Rockafellar, §11 (p. 99). A supporting half-space to C is a closed half-space
{x | ⟨x, b⟩ ≤ β}, b ≠ 0, which contains C and has a point of C in its boundary. The
boundary {x | ⟨x, b⟩ = β} is then a supporting hyperplane to C.
Equations
- Rockafellar.IsSupportingHalfSpace b β C = (b ≠ 0 ∧ (∀ x ∈ C, ((TdafSurface.pairing n) x) b ≤ β) ∧ ∃ x ∈ C, ((TdafSurface.pairing n) x) b = β)
Instances For
The bridge for IsSupportingHalfSpace: it is the backbone's IsSupporting for the
functional ⟨·, b⟩.
Theorem 11.6. Let C be a convex set, and let D be a non-empty convex
subset of C. In order that there exist a non-trivial supporting hyperplane to C containing D,
it is necessary and sufficient that D be disjoint from ri C.
Stated with ri C, where the backbone has the interior version; a non-trivial supporting
hyperplane to C through D is the same thing as a proper separation of D and C.
Corollary 11.6.1. A convex set has a non-zero normal at each of its boundary points.
Rockafellar's normal to C at x is the backbone's normalCone (pairing n) C x. Specialises
exists_ne_zero_isMaxOn_of_mem_frontier.
Corollary 11.6.2. Let C be a convex set. An x ∈ C is a relative boundary
point of C if and only if there exists a linear function h not constant on C such that h
achieves its maximum over C at x.
relbd is §6's relative boundary.
Theorem 11.7, cones and homogeneous half-spaces #
Theorem 11.7. Let C₁ and C₂ be non-empty subsets of ℝⁿ, at least one of
which is a cone. If there exists a hyperplane which separates C₁ and C₂ properly, then there
exists a hyperplane which separates C₁ and C₂ properly and passes through the origin.
Stated with the cone on the C₂ side; SeparatesProperlyRn b 0 C₁ C₂ says the separating
hyperplane is {x | ⟨x, b⟩ = 0}, which contains the origin.
Theorem 11.7, with the cone on the C₁ side.
Corollary 11.7.1. A non-empty closed convex cone in ℝⁿ is the intersection
of the homogeneous closed half-spaces which contain it, a homogeneous half-space being one with the
origin on its boundary.
Corollary 11.7.2. Let S be any subset of ℝⁿ, and let K be the closure of
the convex cone generated by S. Then K is the intersection of all the homogeneous closed
half-spaces containing S.
The cone generated by S is PointedCone.hull ℝ S, which contains the origin; the book's own
proof needs that, so no generality is lost.
Corollary 11.7.3. Let K be a convex cone in ℝⁿ other than ℝⁿ itself.
Then K is contained in some homogeneous closed half-space of ℝⁿ; in other words, there exists
some vector b ≠ 0 such that ⟨x, b⟩ ≤ 0 for every x ∈ K.
K.Nonempty is added to the book's hypotheses, exactly as in Corollary 11.5.2.