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Books.ConvexAnalysis_Rockafellar_1970.Chap07.section34_part3

noncomputable def classicalDecidablePredPart3 {α : Type u_1} (p : αProp) :

Predicates on coordinate spaces in this section are treated classically when needed in piecewise definitions.

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      theorem helperForText_34_1_4_openBall_reverseMinimax_of_localConcaveConvexOn_of_saddlePointOn {m n : } (K : SaddleFunction m n) (u : Fin m) (xStar : Fin n) (ε δ : { δ : // 0 < δ }) (hLocal : IsConcaveConvexOn {w : Fin m | w - u < ε} {z : Fin n | z - xStar < δ} K) (w0 : Fin m) (hw0 : w0 - u < ε) (z0 : Fin n) (hz0 : z0 - xStar < δ) (hS : IsSaddlePointOn {z : Fin n | z - xStar < δ} {w : Fin m | w - u < ε} (fun (z : Fin n) (w : Fin m) => K w z) z0 w0) :
      ⨅ (z : { z : Fin n // z - xStar < δ }), ⨆ (w : { w : Fin m // w - u < ε }), K w z ⨆ (w : { w : Fin m // w - u < ε }), ⨅ (z : { z : Fin n // z - xStar < δ }), K w z

      Helper for Text 34.1.4: reverse-minimax inequality on a pair of open balls, derived from local concave-convexity on those balls.

      This lemma is the true upstream minimax/duality input required by the current proof route. Once it is available, helperForText_34_1_4_reverseMinimax_closedBallRadiusEnvelope follows by deterministic rewriting to the closed-ball-radius envelope form.

      Helper for Text 34.1.4: a one-dimensional coordinate kernel used to exhibit that Jensen-style concave-convexity on open balls does not force existence of a saddle point.

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          theorem helperForText_34_1_4_coordKernel_concaveConvexOn_openBalls (u xStar : Fin 1) (ε δ : { δ : // 0 < δ }) :

          Helper for Text 34.1.4: the coordinate kernel is concave-convex on every pair of open balls.

          The first-variable Jensen inequality holds by equality for the linear map w ↦ w 0, while the second-variable inequality holds because the kernel is constant in the second variable.

          Helper for Text 34.1.4: the one-dimensional coordinate kernel is globally concave-convex.

          Helper for Text 34.1.4: the first-variable closure of the coordinate kernel vanishes at the origin of the first variable.

          Helper for Text 34.1.4: the mixed lower closure of the coordinate kernel also vanishes at the origin of the first variable.

          Helper for Text 34.1.4: a one-dimensional coordinate kernel in the second variable, used to test the right closed-ball bridge.

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              Helper for Text 34.1.4: the second-coordinate kernel is globally concave-convex.

              Helper for Text 34.1.4: the first closure of the second-coordinate kernel is trivial because the kernel is constant in the first variable.

              Helper for Text 34.1.4: the second closure of the second-coordinate kernel vanishes at the origin of the second variable.

              Helper for Text 34.1.4: the mixed lower closure of the second-coordinate kernel also vanishes at the origin of the second variable.

              theorem helperForText_34_1_4_exists_mem_openBall_gt_coord_fin1 (u : Fin 1) (ε : ) (w0 : Fin 1) (hw0 : w0 - u < ε) :
              ∃ (w : Fin 1), w - u < ε w0 0 < w 0

              Helper for Text 34.1.4: any point in a nontrivial open ball in Fin 1 → ℝ can be moved to a nearby point in the same ball with strictly larger 0-th coordinate.

              theorem helperForText_34_1_4_coordKernel_no_saddlePointOn_openBalls (u xStar : Fin 1) (ε δ : { δ : // 0 < δ }) :
              ¬∃ (w0 : Fin 1), w0 - u < ε ∃ (z0 : Fin 1), z0 - xStar < δ IsSaddlePointOn {z : Fin 1 | z - xStar < δ} {w : Fin 1 | w - u < ε} (fun (z w : Fin 1) => helperForText_34_1_4_coordKernel w z) z0 w0

              Helper for Text 34.1.4: the coordinate kernel admits no saddle point on open balls.

              This gives a concrete counterexample to the naive implication IsConcaveConvexOn (openBall u ε) (openBall xStar δ) K → ∃ saddle point, so the corresponding step in the proof pipeline must be replaced by a genuine minimax/duality theorem with additional hypotheses (compactness/attainment, semicontinuity, etc.).

              theorem helperForText_34_1_4_counterexample_openBall_exists_saddlePointOn_false (u xStar : Fin 1) (ε δ : { δ : // 0 < δ }) :
              IsConcaveConvexOn {w : Fin 1 | w - u < ε} {z : Fin 1 | z - xStar < δ} helperForText_34_1_4_coordKernel ¬∃ (w0 : Fin 1), w0 - u < ε ∃ (z0 : Fin 1), z0 - xStar < δ IsSaddlePointOn {z : Fin 1 | z - xStar < δ} {w : Fin 1 | w - u < ε} (fun (z w : Fin 1) => helperForText_34_1_4_coordKernel w z) z0 w0

              Helper for Text 34.1.4: counterexample showing that the open-ball saddle-point existence step cannot be proved from IsConcaveConvexOn alone.

              theorem helperForText_34_1_4_no_uniform_openBall_saddlePointExistence_in_dim1 :
              ¬∀ (K : SaddleFunction 1 1) (u xStar : Fin 1) (ε δ : { δ : // 0 < δ }), IsConcaveConvexOn {w : Fin 1 | w - u < ε} {z : Fin 1 | z - xStar < δ} K∃ (w0 : Fin 1), w0 - u < ε ∃ (z0 : Fin 1), z0 - xStar < δ IsSaddlePointOn {z : Fin 1 | z - xStar < δ} {w : Fin 1 | w - u < ε} (fun (z w : Fin 1) => K w z) z0 w0

              Helper for Text 34.1.4: the abandoned open-ball route is already false in dimension 1.

              Concretely, there is no uniform theorem saying that local concave-convexity on open balls forces existence of a saddle point on those balls.

              theorem helperForText_34_1_4_coordKernel_reverseMinimax_openBalls (u xStar : Fin 1) (ε δ : { δ : // 0 < δ }) :
              ⨅ (z : { z : Fin 1 // z - xStar < δ }), ⨆ (w : { w : Fin 1 // w - u < ε }), helperForText_34_1_4_coordKernel w z ⨆ (w : { w : Fin 1 // w - u < ε }), ⨅ (z : { z : Fin 1 // z - xStar < δ }), helperForText_34_1_4_coordKernel w z

              Helper for Text 34.1.4: the coordinate kernel satisfies the reverse-minimax inequality on open balls even though it has no saddle point there.

              This emphasizes that failure of saddle-point attainment does not by itself refute reverse minimax; what is missing for the general theorem is a genuine minimax/duality input, not the simple saddle-point existence step.

              Helper for Text 34.1.4: graph-function closedness upgrades a Rockafellar convex bifunction to a closed convex bifunction.

              Dimension-wide realization qualification for the converse direction of Corollary 33.3.1. The forward closure theorem does not construct a bifunction witness from an arbitrary closure pair, so the two canonical realization clauses are recorded explicitly.

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                Helper for Text 34.1.4: the qualified converse of Corollary 33.3.1 gives a closed convex witness for the canonical pair (underline(K), cl₁ underline(K)) once the primal side is assumed to avoid both and .

                Helper for Text 34.1.4: the corrected Corollary 33.3.1 likewise gives a closed convex witness for the canonical pair (cl₂ overline(K), overline(K)) once the lower partner is assumed to avoid both and .

                Helper for Text 34.1.4: a closed convex bifunction already has graph function fixed by the raw convex-closure operator.

                Helper for Text 34.1.4: the constant function is concave in the Jensen sense on ℝ^n.

                theorem helperForText_34_1_4_zeroDimensional_constBot_lowerClosure_eq_bot :
                let K := fun (x x_1 : Fin 0) => ; have h := ; lowerClosureConcaveConvex K h 0 0 =

                Route correction for Text 34.1.4: the zero-dimensional constant- kernel is concave-convex, and its mixed lower closure still equals at the unique point.

                Route correction for Text 34.1.4: the statement HasNoBotValuesBifunction (lowerClosureConcaveConvex K h) is false in general. The zero-dimensional constant- kernel already refutes it.

                theorem helperForText_34_1_4_lowerClosure_hasNoBot_of_closedConvexLowerRepresentation {m n : } (K : SaddleFunction m n) (h : IsConcaveConvex K) {F : (Fin m)(Fin n)EReal} (hRock : IsRockafellarConvexBifunction F) (hNoBot : HasNoBotValuesBifunction F) (hClosed : ClosedConvexBifunction F) (hLowerRep : lowerClosureConcaveConvex K h = convexBifunctionPairing F) (hFiniteSections : ∀ (u : Fin m), ∃ (x : Fin n), F u x < ) :

                Helper for Text 34.1.4: although underline(K) need not avoid in general, any actual closed-convex witness for underline(K) forces the represented mixed lower closure to have no values.

                theorem helperForText_34_1_4_lowerClosure_hasNoBot {m n : } (K : SaddleFunction m n) (h : IsConcaveConvex K) {F : (Fin m)(Fin n)EReal} (hRock : IsRockafellarConvexBifunction F) (hNoBot : HasNoBotValuesBifunction F) (hClosed : ClosedConvexBifunction F) (hLowerRep : lowerClosureConcaveConvex K h = convexBifunctionPairing F) (hFiniteSections : ∀ (u : Fin m), ∃ (x : Fin n), F u x < ) :

                Helper for Text 34.1.4: the usable no- statement for underline(K) is the witness-local one. The naive global version is false by the constant- counterexample above, so the remaining development only uses this corrected interface.

                theorem helperForText_34_1_4_witness_sections_notTop_of_lowerRepresentation {m n : } {K : SaddleFunction m n} {h : IsConcaveConvex K} {F : (Fin m)(Fin n)EReal} (hLowerNoBot : HasNoBotValuesBifunction (lowerClosureConcaveConvex K h)) (hLowerRep : lowerClosureConcaveConvex K h = convexBifunctionPairing F) (u : Fin m) :
                ∃ (x : Fin n), F u x

                Helper for Text 34.1.4: if a convex bifunction represents underline(K), then none of its parameter sections can be identically ; otherwise the pairing would force underline(K) to take the value .

                Helper for Text 34.1.4: any convex bifunction representing underline(K) already has full strict parameter domain, because underline(K) never takes the value .

                Helper for Text 34.1.4: any convex bifunction representing underline(K) has full Section 33 parameter domain, not just the strict < ⊤ variant.