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import Mathlib
import OAI.Probability.LogConcave.Dynamics.Truncated
namespace OAI
section
section
noncomputable section
namespace LogConcaveSampling.GlobalODE
open Set Function Filter Metric
open scoped Topology NNReal
def variationalField {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
(f : E → E) (p : E × (E →L[ℝ] E)) : E × (E →L[ℝ] E) :=
(f p.1,(fderiv ℝ f p.1).comp p.2)
lemma variationalField_smooth {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
{f : E → E} {n : ℕ} (hf : ContDiff ℝ ((n:WithTop ℕ∞)+1) f) :
ContDiff ℝ (n:WithTop ℕ∞) (variationalField f) :=
((hf.of_le (by exact_mod_cast Nat.le_succ n)).comp contDiff_fst).prodMk
(((hf.fderiv_right le_rfl).comp contDiff_fst).clm_comp contDiff_snd)
lemma truncated_contDiff {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[FiniteDimensional ℝ E] {f : E → E} {k : ℕ} (hf : ContDiff ℝ (k:WithTop ℕ∞) f) (n : ℕ) :
ContDiff ℝ (k:WithTop ℕ∞) (LinearGrowthODE.truncated f n) :=
(((PoincareCutoff.bump (E:=E)).contDiff).comp (contDiff_id.const_smul _)).smul hf
theorem autonomous_flow_contDiff (n : ℕ) :
∀ {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [FiniteDimensional ℝ E]
{f : E → E} (hf : ContDiff ℝ (n:WithTop ℕ∞) f) {K : ℝ≥0}
(hL : LipschitzWith K f) {a b : ℝ} (hab : a≤b) (t : Icc a b),
ContDiff ℝ (n:WithTop ℕ∞) (fun x => flow (fun _ _ => hL)
(hf.continuous.comp continuous_snd) ⟨a,le_rfl,hab⟩ x t) := by
induction n with
| zero =>
intro E _ _ _ f hf K hL a b hab t
exact contDiff_zero.mpr (flow_lipschitz (fun _ _ => hL)
(hf.continuous.comp continuous_snd) ⟨a,le_rfl,hab⟩ t).continuous
| succ n ih =>
intro E _ _ _ f hf K hL a b hab t
have hf1 : ContDiff ℝ 1 f := hf.of_le (by exact_mod_cast Nat.succ_pos n)
let hc : Continuous (uncurry (fun (_ : ℝ) => f)) := hf.continuous.comp continuous_snd
let hD : Continuous (uncurry (fun (_ : ℝ) => fderiv ℝ f)) :=
(hf1.continuous_fderiv (by norm_num)).comp continuous_snd
let hd : ∀ (u : ℝ) (z : E),HasFDerivAt f (fderiv ℝ f z) z :=
fun _ z => (hf1.differentiable (by norm_num) z).hasFDerivAt
cases n with
| zero =>
exact flow_contDiff_one_left hab hc (fun _ _ => hL) hD hd t
| succ m =>
let J := flowLinearization hab hc (fun _ _ => hL) hD hd
let X := fun x => flow (fun _ _ => hL) hc ⟨a,le_rfl,hab⟩ x
have hXd (x : E) : HasFDerivAt (fun z => X z t) (J x t) x :=
flow_hasFDerivAt_left hab hc (fun _ _ => hL) hD hd x t
change ContDiff ℝ (((m+1:ℕ):WithTop ℕ∞)+1) (fun x => X x t)
apply contDiff_succ_iff_hasFDerivAt.mpr
refine ⟨fun x => J x t,?_,hXd⟩
apply contDiff_iff_contDiffAt.mpr
intro x₀
let V := variationalField f
have hV : ContDiff ℝ ((m+1:ℕ):WithTop ℕ∞) V := variationalField_smooth (by simpa using hf)
have hV1 : ContDiff ℝ 1 V := hV.of_le (by exact_mod_cast Nat.succ_pos m)
obtain ⟨A,hA⟩ := isCompact_Icc.exists_bound_of_continuousOn
(flow_continuous (fun _ _ => hL) hc ⟨a,le_rfl,hab⟩ (0:E)).continuousOn
let C := Real.exp ((K:ℝ)*(b-a))
have hC : 0<C := Real.exp_pos _
obtain ⟨N,hN⟩ := exists_nat_gt (max (A+C*(‖x₀‖+1)) C)
let W := LinearGrowthODE.truncated V N
have hW : ContDiff ℝ ((m+1:ℕ):WithTop ℕ∞) W := truncated_contDiff hV N
obtain ⟨L,hWL⟩ := LinearGrowthODE.truncated_lipschitz hV1 N
have hWc : Continuous (uncurry (fun (_ : ℝ) => W)) := hW.continuous.comp continuous_snd
let Z (p : E × (E →L[ℝ] E)) := flow (fun _ _ => hWL) hWc ⟨a,le_rfl,hab⟩ p t
have hZ : ContDiff ℝ ((m+1:ℕ):WithTop ℕ∞) Z := ih hW hWL hab t
have hloc : (fun x => J x t) =ᶠ[𝓝 x₀]
(fun x => (Z (x,ContinuousLinearMap.id ℝ E)).2) := by
filter_upwards [Metric.ball_mem_nhds x₀ zero_lt_one] with x hx
have hxn : ‖x‖≤‖x₀‖+1 := by
have hh := norm_le_norm_add_norm_sub x₀ x
rw [←dist_eq_norm, dist_comm] at hh
linarith [Metric.mem_ball.mp hx]
have hb (u : Icc a b) : ‖(X x u,J x u)‖≤(N:ℝ)+1 := by
have hu : |(u:ℝ)-a|≤b-a := by
rw [abs_of_nonneg (sub_nonneg.mpr u.2.1)]; linarith [u.2.2]
have hex : Real.exp ((K:ℝ)*|(u:ℝ)-a|)≤C :=
Real.exp_le_exp.mpr (mul_le_mul_of_nonneg_left hu K.coe_nonneg)
have hX : ‖X x u‖≤A+C*(‖x₀‖+1) := by
have hs := (flow_lipschitz (fun _ _ => hL) hc ⟨a,le_rfl,hab⟩ u).dist_le_mul x 0
simp only [dist_zero_right] at hs
have hn : ‖X x u‖≤‖X 0 u‖+dist (X x u) (X 0 u) := by
simpa only [dist_eq_norm, norm_sub_rev] using
(norm_le_norm_add_norm_sub (X 0 u) (X x u))
exact hn.trans (add_le_add (hA u u.2) (hs.trans
(mul_le_mul hex hxn (norm_nonneg _) hC.le)))
have hJ : ‖J x u‖≤C :=
(fundamental_norm_bound ⟨a,le_rfl,hab⟩
(flowSpatialCoefficient_continuous hab hc (fun _ _ => hL) hD x)
(flowSpatialCoefficient_bound hab hc (fun _ _ => hL) hd x) u).trans hex
rw [Prod.norm_def]
exact (max_le_max hX hJ).trans (by linarith)
have he (u : ℝ) (hu : u∈Icc a b) : W (X x u,J x u)=V (X x u,J x u) :=
LinearGrowthODE.truncated_eq (hb ⟨u,hu⟩)
have hcP : Continuous (fun u => (X x u,J x u)) :=
(flow_continuous (fun _ _ => hL) hc _ x).prodMk
(fundamental_continuous ⟨a,le_rfl,hab⟩
(flowSpatialCoefficient_continuous hab hc (fun _ _ => hL) hD x)
(flowSpatialCoefficient_bound hab hc (fun _ _ => hL) hd x))
have hdP (u : ℝ) (hu : u∈Icc a b) :
HasDerivWithinAt (fun u => (X x u,J x u)) (W (X x u,J x u)) (Icc a b) u := by
rw [he u hu]
exact (flow_deriv (fun _ _ => hL) hc _ x u hu).prodMk
(fundamental_deriv ⟨a,le_rfl,hab⟩
(flowSpatialCoefficient_continuous hab hc (fun _ _ => hL) hD x)
(flowSpatialCoefficient_bound hab hc (fun _ _ => hL) hd x) u hu)
have hs := trajectory_dist (fun (_ : ℝ) _ => hWL) hcP.continuousOn hdP
(flow_continuous (fun _ _ => hWL) hWc ⟨a,le_rfl,hab⟩ (x,ContinuousLinearMap.id ℝ E)).continuousOn
(flow_deriv (fun _ _ => hWL) hWc ⟨a,le_rfl,hab⟩ (x,ContinuousLinearMap.id ℝ E))
⟨a,le_rfl,hab⟩ t
have hi : (X x a,J x a)=(x,ContinuousLinearMap.id ℝ E) := by
apply Prod.ext
· exact flow_initial (fun _ _ => hL) hc ⟨a,le_rfl,hab⟩ x
· exact fundamental_initial ⟨a,le_rfl,hab⟩
(flowSpatialCoefficient_continuous hab hc (fun _ _ => hL) hD x)
(flowSpatialCoefficient_bound hab hc (fun _ _ => hL) hd x)
rw [show (⟨a,le_rfl,hab⟩ : Icc a b).val=a from rfl,hi,flow_initial,
dist_self,zero_mul,dist_le_zero] at hs
exact congrArg Prod.snd hs
exact (hZ.comp (contDiff_id.prodMk contDiff_const)).snd.contDiffAt.congr_of_eventuallyEq hloc
end LogConcaveSampling.GlobalODE
end
end
section
noncomputable section
namespace LogConcaveSampling.GlobalODE
open Set Function Filter Metric
open scoped Topology NNReal
theorem smooth_flow_left {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[FiniteDimensional ℝ E] {n : ℕ} {f : ℝ → E → E}
(hf : ContDiff ℝ (n:WithTop ℕ∞) (uncurry f)) {K : ℝ≥0} {a b : ℝ}
(hL : ∀t∈Icc a b,LipschitzWith K (f t)) (hab : a≤b) (t : Icc a b) :
ContDiff ℝ (n:WithTop ℕ∞) (fun x => flow hL hf.continuous ⟨a,le_rfl,hab⟩ x t) := by
cases n with
| zero => exact contDiff_zero.mpr (flow_lipschitz hL hf.continuous _ t).continuous
| succ n =>
let V : ℝ × E → ℝ × E := fun p => (1,f p.1 p.2)
have hV : ContDiff ℝ ((n+1:ℕ):WithTop ℕ∞) V := contDiff_const.prodMk hf
have hV1 : ContDiff ℝ 1 V := hV.of_le (by exact_mod_cast Nat.succ_pos n)
let X := fun x => flow hL hf.continuous ⟨a,le_rfl,hab⟩ x
apply contDiff_iff_contDiffAt.mpr
intro x₀
obtain ⟨A,hA⟩ := isCompact_Icc.exists_bound_of_continuousOn
((flow_continuous hL hf.continuous ⟨a,le_rfl,hab⟩ (0:E)).continuousOn :
ContinuousOn (X 0) (Icc a b))
let C := Real.exp ((K:ℝ)*(b-a))
have hC : 0<C := Real.exp_pos _
obtain ⟨N,hN⟩ := exists_nat_gt (max (max |a| |b|) (A+C*(‖x₀‖+1)))
let W := LinearGrowthODE.truncated V N
have hW : ContDiff ℝ ((n+1:ℕ):WithTop ℕ∞) W := truncated_contDiff hV N
obtain ⟨L,hWL⟩ := LinearGrowthODE.truncated_lipschitz hV1 N
have hWc : Continuous (uncurry (fun (_ : ℝ) => W)) := hW.continuous.comp continuous_snd
let Z (p : ℝ × E) := flow (fun _ _ => hWL) hWc ⟨a,le_rfl,hab⟩ p t
have hZ : ContDiff ℝ ((n+1:ℕ):WithTop ℕ∞) Z := autonomous_flow_contDiff _ hW hWL hab t
have he : (fun x => X x t) =ᶠ[𝓝 x₀] (fun x => (Z (a,x)).2) := by
filter_upwards [ball_mem_nhds x₀ zero_lt_one] with x hx
have hxn : ‖x‖≤‖x₀‖+1 := by
have hh := norm_le_norm_add_norm_sub x₀ x
rw [←dist_eq_norm,dist_comm] at hh
linarith [mem_ball.mp hx]
have hb (u : Icc a b) : ‖((u:ℝ),X x u)‖≤(N:ℝ)+1 := by
have hu : |(u:ℝ)-a|≤b-a := by
rw [abs_of_nonneg (sub_nonneg.mpr u.2.1)]; linarith [u.2.2]
have hex : Real.exp ((K:ℝ)*|(u:ℝ)-a|)≤C :=
Real.exp_le_exp.mpr (mul_le_mul_of_nonneg_left hu K.coe_nonneg)
have hX : ‖X x u‖≤A+C*(‖x₀‖+1) := by
have hs := (flow_lipschitz hL hf.continuous ⟨a,le_rfl,hab⟩ u).dist_le_mul x 0
simp only [dist_zero_right] at hs
have hn : ‖X x u‖≤‖X 0 u‖+dist (X x u) (X 0 u) := by
simpa only [dist_eq_norm,norm_sub_rev] using (norm_le_norm_add_norm_sub (X 0 u) (X x u))
exact hn.trans (add_le_add (hA u u.2) (hs.trans
(mul_le_mul hex hxn (norm_nonneg _) hC.le)))
have hau : |(u:ℝ)| ≤ max |a| |b| := by
rw [abs_le]
exact ⟨by linarith [neg_abs_le a,le_max_left |a| |b|,u.2.1],
by linarith [le_abs_self b,le_max_right |a| |b|,u.2.2]⟩
rw [Prod.norm_def,Real.norm_eq_abs]
exact (max_le_max hau hX).trans (by linarith)
have heW (u : ℝ) (hu : u∈Icc a b) : W (u,X x u)=V (u,X x u) :=
LinearGrowthODE.truncated_eq (hb ⟨u,hu⟩)
have hcP : Continuous (fun u => (u,X x u)) :=
continuous_id.prodMk (flow_continuous hL hf.continuous _ x)
have hdP (u : ℝ) (hu : u∈Icc a b) :
HasDerivWithinAt (fun u => (u,X x u)) (W (u,X x u)) (Icc a b) u := by
rw [heW u hu]
exact (hasDerivWithinAt_id u (Icc a b)).prodMk (flow_deriv hL hf.continuous _ x u hu)
have hs := trajectory_dist (fun (_ : ℝ) _ => hWL) hcP.continuousOn hdP
(flow_continuous (fun _ _ => hWL) hWc ⟨a,le_rfl,hab⟩ (a,x)).continuousOn
(flow_deriv (fun _ _ => hWL) hWc ⟨a,le_rfl,hab⟩ (a,x)) ⟨a,le_rfl,hab⟩ t
have hi : (a,X x a)=(a,x) := by rw [show X x a=x from flow_initial hL hf.continuous _ x]
rw [show (⟨a,le_rfl,hab⟩ : Icc a b).val=a from rfl,hi,flow_initial,
dist_self,zero_mul,dist_le_zero] at hs
exact congrArg Prod.snd hs
exact (hZ.comp (contDiff_const.prodMk contDiff_id)).snd.contDiffAt.congr_of_eventuallyEq he
lemma flow_congr {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [CompleteSpace E]
{a b : ℝ} {f g : ℝ → E → E} {K L : ℝ≥0}
(hf : Continuous (uncurry f)) (hg : Continuous (uncurry g))
(hL : ∀t∈Icc a b,LipschitzWith K (f t))
(hJ : ∀t∈Icc a b,LipschitzWith L (g t))
(he : ∀t∈Icc a b,∀x,f t x=g t x) (s t : Icc a b) (x : E) :
flow hL hf s x t=flow hJ hg s x t := by
have hd (u : ℝ) (hu : u∈Icc a b) := flow_deriv hJ hg s x u hu
have hh := trajectory_dist hL (flow_continuous hL hf s x).continuousOn
(flow_deriv hL hf s x) (flow_continuous hJ hg s x).continuousOn
(fun u hu => (he u hu _) ▸ flow_deriv hJ hg s x u hu) s t
simpa only [flow_initial,dist_self,zero_mul,dist_le_zero] using hh
end LogConcaveSampling.GlobalODE
namespace LogConcaveSampling.GlobalODE
open Set Function
open scoped Topology NNReal
theorem smooth_flow {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[FiniteDimensional ℝ E] {n : ℕ} {f : ℝ → E → E}
(hf : ContDiff ℝ (n:WithTop ℕ∞) (uncurry f)) {K : ℝ≥0} {a b : ℝ}
(hL : ∀t∈Icc a b,LipschitzWith K (f t)) (hab : a≤b) (s t : Icc a b) :
ContDiff ℝ (n:WithTop ℕ∞) (fun x => flow hL hf.continuous s x t) := by
cases n with
| zero => exact contDiff_zero.mpr (flow_lipschitz hL hf.continuous s t).continuous
| succ n =>
have hf1 : ContDiff ℝ 1 (uncurry f) := hf.of_le (by exact_mod_cast Nat.succ_pos n)
let D : ℝ → E → E →L[ℝ] E := fun u x =>
(fderiv ℝ (uncurry f) (u,x)).comp (ContinuousLinearMap.inr ℝ ℝ E)
have hD : Continuous (uncurry D) :=
(hf1.continuous_fderiv (by norm_num)).clm_comp continuous_const
have hd (u : ℝ) (z : E) : HasFDerivAt (f u) (D u z) z := by
exact ((hf1.differentiable (by norm_num) (u,z)).hasFDerivAt).comp z
((hasFDerivAt_const u z).prodMk (hasFDerivAt_id z))
have hi (u : Icc a b) : ContDiff ℝ ((n+1:ℕ):WithTop ℕ∞)
(fun x => flow hL hf.continuous u x a) := by
let H := flowHomeomorph hL hf.continuous ⟨a,le_rfl,hab⟩ u
let J (x : E) := fundamentalEquiv
(flowSpatialCoefficient_continuous hab hf.continuous hL hD x)
(flowSpatialCoefficient_bound hab hf.continuous hL hd x) ⟨a,le_rfl,hab⟩ u
have hJ (x : E) : HasFDerivAt H (J x : E →L[ℝ] E) x :=
flow_hasFDerivAt_left hab hf.continuous hL hD hd x u
exact H.contDiff_symm hJ (smooth_flow_left hf hL hab u)
have hh := (smooth_flow_left hf hL hab t).comp (hi s)
convert! hh using 1
funext x
exact (flow_cocycle hL hf.continuous s ⟨a,le_rfl,hab⟩ t x).symm
end LogConcaveSampling.GlobalODE
end
end
end
end OAI