openAI-math-dataset / lean /OAI /Analysis /BernoulliCone /DominatedVariation.lean
roseking's picture
Add lean source and binary files (part 11)
110f4f3 verified
Raw History Blame Contribute Delete
2.96 kB
import OAI.Analysis.BernoulliCone.HalfspaceGroundstate
namespace OAI
section
noncomputable section
open MeasureTheory Set Filter Metric
open scoped Topology NNReal ENNReal ContDiff
namespace Bernoulli
open scoped _root_.Bernoulli
variable {d : ℕ} {D : Set (Space d)}
lemma dominatedVariation_of_comparison [IsFiniteMeasure (volume.restrict D)]
{u v : Space d → ℝ} {G V : Space d → Space d}
(hu : H1 D u G) (hv : H10 D v V)
(hn : ∀ᵐ x ∂volume.restrict D, 0≤u x)
{C : ℝ} (hC : 0<C) (hbound : ∀ᵐ x ∂volume.restrict D, |v x| ≤ C*u x)
(hmin : ∀ (w : Space d → ℝ) (W : Space d → Space d),
H1 D w W → (∀ᵐ x ∂volume.restrict D, 0≤w x) →
H10 D (fun x=>w x-u x) (fun x=>W x-G x) → energy D u G≤energy D w W) :
(∫ x in D, inner ℝ (G x) (V x))=0 := by
apply linear_coefficient_eq_zero _ (∫ x in D, ‖V x‖^2) (inv_pos.mpr hC)
intro t ht
have htC : |t| * C<1 := by
calc |t| * C < C⁻¹*C := mul_lt_mul_of_pos_right ht hC
_ = 1 := inv_mul_cancel₀ hC.ne'
have hcontrol : ∀ᵐ x ∂volume.restrict D,
0≤u x+t*v x ∧ ((0<u x+t*v x) ↔ 0<u x) := by
filter_upwards [hn,hbound] with x hx hbx
have hb : |t*v x| ≤ (|t| * C)*u x := by
rw [abs_mul,mul_assoc]
exact mul_le_mul_of_nonneg_left hbx (abs_nonneg t)
by_cases hup : 0<u x
· have hp : 0<u x+t*v x := by
have := neg_abs_le (t*v x)
nlinarith
exact ⟨hp.le,iff_of_true hp hup⟩
· have hz : u x=0 := le_antisymm (not_lt.mp hup) hx
have hvz : v x=0 := abs_eq_zero.mp (le_antisymm (by simpa only [hz,mul_zero] using hbx) (abs_nonneg _))
simp only [hz,hvz,mul_zero,add_zero,le_refl,lt_self_iff_false,iff_self,and_self]
have hc := hmin (fun x=>u x+t*v x) (fun x=>G x+t • V x)
(hu.add (hv.1.const_smul t)) (hcontrol.mono fun _ hx=>hx.1)
(by simpa only [add_sub_cancel_left] using hv.const_smul t)
rw [energy_affine hu.1 hu.2.1 hv.1.2.1 t (hcontrol.mono fun _ hx=>hx.2)] at hc
linarith
lemma GlobalMinimizer.dominatedVariation {u v : Space d → ℝ} {L : ℝ≥0}
(hm : GlobalMinimizer u) (hL : LipschitzWith L u)
{a : Space d} {R C : ℝ} (hR : 0<R)
{V : Space d → Space d} (hv : H10 (ball a R) v V)
(hC : 0<C) (hbound : ∀ᵐ x ∂volume.restrict (ball a R), |v x| ≤ C*u x) :
(∫ x in ball a R, inner ℝ (gradient u x) (V x))=0 := by
let : IsFiniteMeasure (volume.restrict (ball a R)) :=
isFiniteMeasure_restrict.mpr measure_ball_lt_top.ne
obtain ⟨_,G,hG,hn,hmin⟩ := hm
have hu := hG a R hR (subset_univ _)
have he := hu.gradient_unique isOpen_ball (LipschitzSobolev.h1_ball hL a R)
have hh := dominatedVariation_of_comparison hu hv
(ae_restrict_of_ae (by simpa only [Measure.restrict_univ] using hn)) hC hbound
(hmin a R hR (subset_univ _))
rw [←hh]
apply integral_congr_ae
filter_upwards [he] with x hx
rw [hx]
end Bernoulli
end
end
end OAI