openAI-math-dataset / lean /OAI /Geometry /SmoothYau /Estimates /LinearProdSurjectiveMinor.lean
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Add lean source and binary files (part 75)
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import Mathlib
namespace OAI
noncomputable section
open Set Filter Function
open scoped Topology ContDiff
namespace YauCounterexamples
lemma linear_prod_surjective_of_minor {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
(L R : E →L[ℝ] ℝ) (v w : E) (h : L v*R w-L w*R v ≠ 0) :
Function.Surjective (L.prod R) := by
rintro ⟨a,b⟩
let D := L v*R w-L w*R v
refine ⟨((a*R w-b*L w)/D) • v+((b*L v-a*R v)/D) • w, ?_⟩
apply Prod.ext
· change L (_ • v+_ • w)=a
simp only [map_add,map_smul,smul_eq_mul]
calc
_ = a*D/D := by dsimp only [D]; ring
_ = a := mul_div_cancel_right₀ a h
· change R (_ • v+_ • w)=b
simp only [map_add,map_smul,smul_eq_mul]
calc
_ = b*D/D := by dsimp only [D]; ring
_ = b := mul_div_cancel_right₀ b h
lemma analytic_rank_dense {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
(f g : E → ℝ) (hf : ContDiff ℝ ω f) (hg : ContDiff ℝ ω g)
{x₀ : E} (hr : Function.Surjective (fderiv ℝ (fun x => (f x,g x)) x₀))
{O : Set E} (hO : IsOpen O) (hne : O.Nonempty) :
∃ y ∈ O, Function.Surjective (fderiv ℝ (fun x => (f x,g x)) y) := by
have hd (x : E) : fderiv ℝ (fun x => (f x,g x)) x = (fderiv ℝ f x).prod (fderiv ℝ g x) :=
(hf.differentiable (by simp) x).fderiv_prodMk (hg.differentiable (by simp) x)
obtain ⟨v,hv⟩ := hr (1,0)
obtain ⟨w,hw⟩ := hr (0,1)
rw [hd] at hv hw
have hv1 := congrArg Prod.fst hv
have hv2 := congrArg Prod.snd hv
have hw1 := congrArg Prod.fst hw
have hw2 := congrArg Prod.snd hw
simp only [ContinuousLinearMap.prod_apply] at hv1 hv2 hw1 hw2
let D : E → ℝ := fun x => fderiv ℝ f x v*fderiv ℝ g x w-fderiv ℝ f x w*fderiv ℝ g x v
have hD : ContDiff ℝ ω D := by
have H (q : E → ℝ) (hq : ContDiff ℝ ω q) (z : E) :
ContDiff ℝ ω (fun x => fderiv ℝ q x z) :=
(hq.contDiff_fderiv_apply (by simp)).comp (contDiff_id.prodMk contDiff_const)
exact ((H f hf v).mul (H g hg w)).sub ((H f hf w).mul (H g hg v))
by_contra! hn
obtain ⟨z,hz⟩ := hne
have he : D =ᶠ[𝓝 z] (fun _ => (0:ℝ)) := by
filter_upwards [hO.mem_nhds hz] with x hx
by_contra hh
apply hn x hx
rw [hd]
exact linear_prod_surjective_of_minor _ _ v w hh
have hglo := hD.analyticOnNhd.eq_of_eventuallyEq contDiff_const.analyticOnNhd he
have := congrFun hglo x₀
simp only [D,hv1,hv2,hw1,hw2] at this
norm_num at this
end YauCounterexamples
end
end OAI