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import OAI.Probability.CubeShuffle.NetworkSpectral
import OAI.Probability.CubeShuffle.Physical
import OAI.RepresentationTheory.YoungSymmetry.ShapeBounds
namespace OAI
namespace CubeShuffle.DimensionEstimates
open scoped BigOperators Classical
open Filter
lemma medium_parameters (h : ℝ) (hh : 0<h) :
∃ L : ℕ, 0<L ∧ ∃ ε t : ℝ, 0<ε ∧ ε<1/2 ∧ 0≤t ∧
t*ε+Real.log (1+Real.exp (-t))≤h*(2:ℝ)^L/16000 ∧
∀ᶠ r : ℕ in atTop, ∀ (E : Finset (Card r)), (E.card:ℝ)<ε*(2:ℝ)^r →
∀ e : Card (L+r) ↪ Card (L+r),
modifiedRowMoment L r E e (1/1000)≤Real.exp ((h/4000)*(2:ℝ)^(L+r)) := by
obtain ⟨L,hL,ε₀,hε₀,_,hM⟩ := modified_arbitrarily_small_rate (h/4000) (by positivity)
obtain ⟨ε,hε,hεle,hεhalf,t,ht,hcount⟩ := exists_small_set_rate
(h*(2:ℝ)^L/16000) ε₀ (by positivity) hε₀
refine ⟨L,hL,ε,t,hε,hεhalf,ht,hcount,?_⟩
filter_upwards [hM] with r hM
intro E hE e
exact hM E (hE.le.trans (mul_le_mul_of_nonneg_right hεle (by positivity))) e
end CubeShuffle.DimensionEstimates
namespace CubeShuffle.Specht
open scoped BigOperators Classical
open UnitaryFinite DimensionEstimates Filter
lemma dimension_pos (μ : YoungDiagram) : 0 < Module.finrank ℂ (space μ) := by
have h := factorial_le_dimension_row_column μ
by_contra hn
have hz : Module.finrank ℂ (space μ)=0 := by omega
rw [hz,zero_mul,zero_mul] at h
exact (Nat.factorial_pos μ.card).not_ge h
lemma near_numerical_cutoff :
∃ X : ℝ, 2 ≤ X ∧ ∀ (N j D : ℕ), 0 < j → X ≤ (N:ℝ)/j → N.choose j ≤ D * 2^j →
∃ k : ℕ, j ≤ k ∧ k ≤ N ∧ ∀ m : ℕ, D * k.choose j ≤ m * N.choose j →
nearFraction * Real.log D ≤ Real.log m ∧
densityConstant * (k:ℝ) * ((k:ℝ)/N)^(1/512:ℝ) ≤ Real.log m/4000 ∧
(1/2:ℝ) * Real.log N ≤ Real.log D ∧ (j:ℝ) ≤ Real.log D := by
obtain ⟨X,hX,h⟩ := exists_near_cutoff densityConstant densityConstant_pos.le
refine ⟨X,hX,?_⟩
intro N j D hj hx hd
have hjN : j ≤ N := by
have hjp : (0:ℝ) < j := by exact_mod_cast hj
have hh : (j:ℝ) ≤ N := by
have := (le_div_iff₀ hjp).mp (hX.trans hx)
linarith
exact_mod_cast hh
have hc : 1 ≤ N.choose j := Nat.choose_pos hjN
have hfoot : D * (chosenTuple N j).choose j ≤ (D * (chosenTuple N j).choose j) * N.choose j :=
Nat.le_mul_of_pos_right _ hc
have hh := h N j D _ hj hx hd hfoot
refine ⟨chosenTuple N j,hh.1,hh.2.1,?_⟩
intro m hm
exact (h N j D m hj hx hd hm).2.2
lemma near_row_amplification (d : ℕ) (μ : YoungDiagram) (e : Card d ≃ Cell μ)
{k : ℕ} (f : Fin k ↪ Card d) (hk : 0<k)
(hm : 0<Module.finrank ℂ (fixedSpace (V := hilbertSpace μ) tupleAction f (relabelledUnitary μ e))) :
‖sampleOperator (V := hilbertSpace μ) (relabelledUnitary μ e) (palindromePerm d)‖ ≤
Real.exp (densityConstant*(k:ℝ)*((k:ℝ)/(2:ℝ)^d)^(1/512:ℝ))*
(Real.exp (Real.log (Module.finrank ℂ (fixedSpace (V := hilbertSpace μ) tupleAction f (relabelledUnitary μ e)))/2))^(-(1/1000:ℝ))+
Real.sqrt ((Real.exp (Real.log (Module.finrank ℂ (fixedSpace (V := hilbertSpace μ) tupleAction f (relabelledUnitary μ e)))/2))/
(Module.finrank ℂ (fixedSpace (V := hilbertSpace μ) tupleAction f (relabelledUnitary μ e)):ℝ)) := by
let := relabelledUnitary_irreducible μ e
let : NormedAddCommGroup (hilbertSpace μ) := inferInstance
let : InnerProductSpace ℂ (hilbertSpace μ) := inferInstance
let : FiniteDimensional ℂ (hilbertSpace μ) := inferInstance
have aux := @palindrome_irrep_amplification (hilbertSpace μ) _ _ _ d (Fin k) _ f
(by simpa only [Fintype.card_fin] using hk) (relabelledUnitary μ e) inferInstance
(relabelledUnitary_unitary μ e) hm
(Real.exp (Real.log (Module.finrank ℂ (fixedSpace (V := hilbertSpace μ) tupleAction f (relabelledUnitary μ e)))/2))
(Real.exp_pos _)
simpa only [Fintype.card_fin] using aux
/-- Uniform near-row decay for the actual full-permutation palindrome.
The tuple size and fixed-space multiplicity are constructed, not assumed. -/
theorem near_row_spectral :
∃ X : ℝ, 2 ≤ X ∧ ∀ (d : ℕ) (μ : YoungDiagram) (e : Card d ≃ Cell μ),
0 < μ.card-μ.rowLen 0 → X ≤ (μ.card:ℝ)/(μ.card-μ.rowLen 0:ℕ) →
32768000 * Real.log 2 ≤ (1/2:ℝ) * Real.log μ.card →
‖sampleOperator (V := hilbertSpace μ) (relabelledUnitary μ e) (palindromePerm d)‖ ≤
Real.exp (-(nearFraction/8000) * Real.log (Module.finrank ℂ (space μ))) ∧
(1/2:ℝ) * Real.log μ.card ≤ Real.log (Module.finrank ℂ (space μ)) ∧
(μ.card-μ.rowLen 0:ℕ) ≤ Real.log (Module.finrank ℂ (space μ)) := by
obtain ⟨X,hX,h⟩ := near_numerical_cutoff
refine ⟨X,hX,?_⟩
intro d μ e hj hx hlarge
let j := μ.card-μ.rowLen 0
let D := Module.finrank ℂ (space μ)
have hcard : μ.card=2^d := by rw [←card_cell,←Fintype.card_congr e,card_positions]
obtain ⟨k,hjk,hk,hnum⟩ := h μ.card j D hj hx (choose_tail_le_dimension μ)
obtain ⟨f⟩ := Function.Embedding.nonempty_of_card_le
(show Fintype.card (Fin k) ≤ Fintype.card (Card d) by simpa only [Fintype.card_fin,card_positions,←hcard] using hk)
let m := Module.finrank ℂ (fixedSpace (V := hilbertSpace μ) tupleAction f (relabelledUnitary μ e))
have hfoot : D * k.choose j ≤ m * μ.card.choose j := by
simpa only [Fintype.card_fin,finrank_hilbertSpace] using relabelled_tuple_dimension μ e f
have hm : 0 < m := by
have hc := Nat.choose_pos hjk
have hd := dimension_pos μ
by_contra hn
have hz : m=0 := by omega
rw [hz,zero_mul] at hfoot
exact (Nat.mul_pos hd hc).not_ge hfoot
obtain ⟨hlm,hden,hlog,hjlog⟩ := hnum m hfoot
have ha := near_row_amplification d μ e f (hj.trans_le hjk) hm
have hcardR : (μ.card:ℝ)=(2:ℝ)^d := by exact_mod_cast hcard
rw [←hcardR] at ha
have hl : 8000 * Real.log 2 ≤ Real.log m := by
dsimp [nearFraction] at hlm
linarith
have hn := amplification_decay (m:ℝ) (densityConstant * k * ((k:ℝ)/μ.card)^(1/512:ℝ))
(by exact_mod_cast hm) hden hl
refine ⟨ha.trans (hn.trans ?_),hlog,hjlog⟩
apply Real.exp_le_exp.mpr
dsimp [D] at hlm
linarith
end CubeShuffle.Specht
namespace CubeShuffle.UnitaryFinite
open scoped BigOperators Classical
open DimensionEstimates
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V] [FiniteDimensional ℂ V]
theorem medium_exception_decay (L r : ℕ) (h ε t : ℝ) (ht : 0≤t)
(hcount : t*ε+Real.log (1+Real.exp (-t))≤h*(2:ℝ)^L/16000)
(ρ : Representation ℂ (Equiv.Perm (Card (L+r))) V) [Representation.IsIrreducible ρ]
(hρ : IsUnitary ρ) (hm : 0<Module.finrank ℂ V)
(hd : h*(2:ℝ)^(L+r)≤Real.log (Module.finrank ℂ V))
(hl : 8000*Real.log 2≤Real.log (Module.finrank ℂ V))
(hM : ∀ (E : Finset (Card r)), (E.card:ℝ)<ε*(2:ℝ)^r →
∀ e : Card (L+r) ↪ Card (L+r),
modifiedRowMoment L r E e (1/1000)≤Real.exp ((h/4000)*(2:ℝ)^(L+r))) :
‖sampleOperator ρ (palindromePerm (L+r))‖≤
Real.exp (Real.log (blockGap L)*ε*(2:ℝ)^r)+Real.exp (-h*(2:ℝ)^(L+r)/16000) := by
have hmE (E : Finset (Card r)) (hE : E.card<⌈ε*(2:ℝ)^r⌉₊) :
‖sampleOperator ρ (modifiedPerm L r E)‖≤Real.exp (-h*(2:ℝ)^(L+r)/8000) := by
apply (full_modified_decay L r E ρ hρ hm ((h/4000)*(2:ℝ)^(L+r))
(hM E (Nat.lt_ceil.mp hE)) (by linarith) hl).trans
apply Real.exp_le_exp.mpr
linarith
have hs : (∑ E : Finset (Card r), if E.card<⌈ε*(2:ℝ)^r⌉₊ then
‖sampleOperator ρ (modifiedPerm L r E)‖ else 0) ≤
Real.exp (-h*(2:ℝ)^(L+r)/16000) := by
calc
_ ≤ (∑ E : Finset (Card r), if E.card<⌈ε*(2:ℝ)^r⌉₊ then (1:ℝ) else 0)*
Real.exp (-h*(2:ℝ)^(L+r)/8000) := by
rw [Finset.sum_mul]
apply Finset.sum_le_sum
intro E _
split_ifs with hE
· simpa only [one_mul] using hmE E hE
· simp
_ ≤ Real.exp ((t*ε+Real.log (1+Real.exp (-t)))*(2:ℝ)^r)*
Real.exp (-h*(2:ℝ)^(L+r)/8000) := by
apply mul_le_mul_of_nonneg_right _ (Real.exp_pos _).le
simpa only [card_positions,Nat.cast_pow,Nat.cast_ofNat] using
small_sets_ceil_bound (ι := Card r) ε t ht
_ ≤ _ := by
rw [←Real.exp_add]
apply Real.exp_le_exp.mpr
have hh := mul_le_mul_of_nonneg_right hcount (by positivity : (0:ℝ)≤(2:ℝ)^r)
rw [pow_add]
nlinarith
apply (palindrome_exception_cards r L ρ hρ ⌈ε*(2:ℝ)^r⌉₊).trans
apply add_le_add _ hs
simpa only [Nat.cast_pow,Nat.cast_ofNat] using
geometric_ceil_bound (blockGap L) ε (blockGap_pos L) (blockGap_lt_one L) (2^r)
end CubeShuffle.UnitaryFinite
namespace CubeShuffle
open scoped BigOperators Classical
lemma tail_preserving_pairSwitch (d : ℕ) (p : Equiv.Perm (Card (d+1)))
(hp : ∀ x, Fin.tail (p x)=Fin.tail x) :
pairSwitch (fun u => p (Fin.cons false u) 0)=p := by
apply Equiv.ext
intro x
rw [←Fin.cons_self_tail x]
generalize x 0=b
generalize Fin.tail x=u
apply funext
intro i
refine Fin.cases ?_ (fun j => ?_) i
· change Bool.xor b (p (Fin.cons false u) 0)=p (Fin.cons b u) 0
cases b with
| false => simp
| true =>
have hn : p (Fin.cons false u) 0 ≠ p (Fin.cons true u) 0 := by
intro he
have hh : p (Fin.cons false u)=p (Fin.cons true u) := by
rw [←Fin.cons_self_tail (p (Fin.cons false u)),←Fin.cons_self_tail (p (Fin.cons true u)),
hp,hp,Fin.tail_cons,Fin.tail_cons,he]
have hh := congrFun (p.injective hh) 0
simp only [Fin.cons_zero] at hh
contradiction
cases h0 : p (Fin.cons false u) 0 <;> cases h1 : p (Fin.cons true u) 0 <;> simp_all
· change u j=p (Fin.cons b u) j.succ
have h := congrFun (hp (Fin.cons b u)) j
simpa only [Fin.tail_cons,Fin.tail,Fin.cons_succ] using h.symm
lemma pairSwitch_injective (d : ℕ) : Function.Injective (pairSwitch (d := d)) := by
intro ξ η h
funext u
have hh := congrArg (fun p : Equiv.Perm (Card (d+1)) => p (Fin.cons false u) 0) h
change Bool.xor false (ξ u)=Bool.xor false (η u) at hh
simpa only [Bool.false_xor] using hh
end CubeShuffle
namespace CubeShuffle.Specht
open scoped BigOperators Classical
noncomputable def pairFiberEquiv (d : ℕ) (μ : YoungDiagram) (e : Card (d+1) ≃ Cell μ) :
(Card d → Bool) ≃ fiberGroup (fun x => Fin.tail (e.symm x)) :=
Equiv.ofBijective (fun ξ => ⟨e.permCongr (pairSwitch ξ),by
intro x
simp only [Equiv.permCongr_apply,e.symm_apply_apply]
exact Fin.tail_cons _ _⟩)
⟨fun ξ η h => pairSwitch_injective d (e.permCongr.injective (congrArg Subtype.val h)),by
intro p
let q := e.symm.permCongr p.1
have hq : ∀ x, Fin.tail (q x)=Fin.tail x := by
intro x
have h := p.2 (e x)
simpa only [q,Equiv.permCongr_apply,Equiv.symm_symm,e.symm_apply_apply] using h
refine ⟨fun u => q (Fin.cons false u) 0,?_⟩
apply Subtype.ext
change e.permCongr (pairSwitch (fun u => q (Fin.cons false u) 0))=p.1
rw [tail_preserving_pairSwitch d q hq]
apply Equiv.ext
intro x
simp only [q,Equiv.permCongr_apply,Equiv.symm_symm,e.apply_symm_apply]⟩
lemma pair_sum_taboid_zero (d : ℕ) (μ : YoungDiagram) (e : Card (d+1) ≃ Cell μ)
(hj : 2^d < μ.colLen 0) (v : space μ) :
(∑ ξ : Card d → Bool, tabloidRep μ (e.permCongr (pairSwitch ξ))) v.1=0 := by
have he : (∑ ξ : Card d → Bool, tabloidRep μ (e.permCongr (pairSwitch ξ)))=
symmetrizer (fiberGroup (fun x => Fin.tail (e.symm x))) (tabloidRep μ) :=
Fintype.sum_equiv (pairFiberEquiv d μ e) _ _ (fun _ => rfl)
rw [he]
exact tall_column_average_zero μ _ 0 (by simpa only [card_positions] using hj) v.1 v.2
lemma pair_operator_tall_zero (d : ℕ) (μ : YoungDiagram) (e : Card (d+1) ≃ Cell μ)
(hj : 2^d < μ.colLen 0) :
UnitaryFinite.sampleOperator (V := hilbertSpace μ) (relabelledUnitary μ e) pairSwitch=0 := by
apply ContinuousLinearMap.ext
intro v
obtain ⟨w,rfl⟩ := (spaceHilbertEquiv μ).surjective v
have hh : (∑ ξ : Card d → Bool, representation μ (e.permCongr (pairSwitch ξ))) w=0 := by
apply Subtype.ext
simp only [LinearMap.sum_apply,Submodule.coe_sum,Submodule.coe_zero]
change (∑ ξ : Card d → Bool, tabloidRep μ (e.permCongr (pairSwitch ξ)) w.1)=0
simpa only [LinearMap.sum_apply] using pair_sum_taboid_zero d μ e hj w
have hh' := congrArg (spaceHilbertEquiv μ) hh
simp only [LinearMap.sum_apply,map_sum,map_zero] at hh'
change ((Fintype.card (Card d → Bool):ℂ)⁻¹ •
∑ ξ : Card d → Bool, UnitaryFinite.continuousRepresentation (relabelledUnitary μ e) (pairSwitch ξ))
(spaceHilbertEquiv μ w)=0
rw [smul_apply,sum_apply]
change (Fintype.card (Card d → Bool):ℂ)⁻¹ •
(∑ ξ : Card d → Bool, spaceHilbertEquiv μ (representation μ (e.permCongr (pairSwitch ξ))
((spaceHilbertEquiv μ).symm (spaceHilbertEquiv μ w))))=0
simp only [LinearEquiv.symm_apply_apply,hh',smul_zero]
end CubeShuffle.Specht
namespace CubeShuffle.Specht
open scoped BigOperators Classical
open UnitaryFinite
lemma palindrome_tall_zero (d : ℕ) (μ : YoungDiagram) (e : Card (d+1) ≃ Cell μ)
(hj : 2^d<μ.colLen 0) :
sampleOperator (V := hilbertSpace μ) (relabelledUnitary μ e) (palindromePerm (d+1))=0 := by
let ρ := relabelledUnitary μ e
let : NormedAddCommGroup (hilbertSpace μ) := inferInstance
let : InnerProductSpace ℂ (hilbertSpace μ) := inferInstance
let : FiniteDimensional ℂ (hilbertSpace μ) := inferInstance
have hpair : sampleOperator (V := hilbertSpace μ) ρ (pairSwitch (d := d))=0 := pair_operator_tall_zero d μ e hj
have hi : sampleOperator ρ (fun ω => (butterflyPerm (d+1) (decodeButterfly (d+1) ω))⁻¹)=0 := by
rw [inverse_butterfly_average_step,hpair,mul_zero]
rw [sampleOperator_inv ρ (relabelledUnitary_unitary μ e)] at hi
rw [sampleOperator_palindrome _ _ (relabelledUnitary_unitary μ e),hi,mul_zero]
lemma palindrome_tall_zero_general (d : ℕ) (hd : 0<d) (μ : YoungDiagram) (e : Card d ≃ Cell μ)
(hj : (μ.card:ℝ)/2<(μ.colLen 0:ℝ)) :
sampleOperator (V := hilbertSpace μ) (relabelledUnitary μ e) (palindromePerm d)=0 := by
obtain ⟨r,rfl⟩ := Nat.exists_eq_succ_of_ne_zero (by omega : d≠0)
apply palindrome_tall_zero r μ e
have hc : μ.card=2^(r+1) := by rw [←card_cell,←Fintype.card_congr e,card_positions]
rw [hc,Nat.cast_pow,Nat.cast_ofNat,pow_succ] at hj
have hh : (2:ℝ)^r<(μ.colLen 0:ℝ) := by linarith
exact_mod_cast hh
end CubeShuffle.Specht
namespace CubeShuffle.Specht
open scoped BigOperators Classical
open Filter UnitaryFinite DimensionEstimates
/-- Every exponentially large irreducible has the same absolute power decay.
Both the high-dimensional FAC.1 and medium-dimensional FAC.2 regimes are used. -/
theorem exponential_dimension_spectral (h : ℝ) (hh : 0<h) :
∃ a : ℝ, 0<a ∧ ∀ᶠ d : ℕ in atTop, ∀ (μ : YoungDiagram) (e : Card d ≃ Cell μ),
h*(2:ℝ)^d≤Real.log (Module.finrank ℂ (space μ)) →
‖sampleOperator (V := hilbertSpace μ) (relabelledUnitary μ e) (palindromePerm d)‖ ≤
Real.exp (-a*Real.log (Module.finrank ℂ (space μ))) := by
obtain ⟨L,hL,ε,t,hε,_,ht,hcount,hM⟩ := medium_parameters h hh
obtain ⟨R,hR⟩ := eventually_atTop.mp hM
let A := 4000*densityConstant+1
have hA : 0<A := by dsimp [A]; have := densityConstant_pos; positivity
let β := min (-Real.log (blockGap L)*ε/(2:ℝ)^L) (h/16000)
have hβ : 0<β := by
apply lt_min
· exact div_pos (mul_pos (neg_pos.mpr (Real.log_neg (blockGap_pos L) (blockGap_lt_one L))) hε) (by positivity)
· positivity
let a := min (1/8000:ℝ) (β/(2*A))
have ha : 0<a := lt_min (by norm_num) (div_pos hβ (by positivity))
refine ⟨a,ha,?_⟩
filter_upwards [eventually_ge_atTop (L+R),twopow_mul_eventually h hh (8000*Real.log 2),
twopow_mul_eventually (β/2) (by positivity) (Real.log 2)] with d hd hl hb
intro μ e hdim
let : NormedAddCommGroup (hilbertSpace μ) := inferInstance
let : InnerProductSpace ℂ (hilbertSpace μ) := inferInstance
let : FiniteDimensional ℂ (hilbertSpace μ) := inferInstance
let := relabelledUnitary_irreducible μ e
have hpos : 0<Module.finrank ℂ (hilbertSpace μ) := by rw [finrank_hilbertSpace]; exact dimension_pos μ
have hlarge : 8000*Real.log 2≤Real.log (Module.finrank ℂ (hilbertSpace μ)) := by rw [finrank_hilbertSpace]; exact hl.trans hdim
have hlog : 0≤Real.log (Module.finrank ℂ (space μ)) := (by positivity : (0:ℝ)≤h*(2:ℝ)^d).trans hdim
by_cases hhigh : A*(2:ℝ)^d≤Real.log (Module.finrank ℂ (space μ))
· have hden : densityConstant*(2:ℝ)^d≤Real.log (Module.finrank ℂ (hilbertSpace μ))/4000 := by
rw [finrank_hilbertSpace]
dsimp [A] at hhigh
nlinarith [pow_pos (by norm_num : (0:ℝ)<2) d]
have hspec := @full_palindrome_decay (hilbertSpace μ) _ _ _ d (relabelledUnitary μ e)
inferInstance (relabelledUnitary_unitary μ e) hpos hden hlarge
rw [finrank_hilbertSpace] at hspec
apply hspec.trans (Real.exp_le_exp.mpr ?_)
have := min_le_left (1/8000:ℝ) (β/(2*A))
nlinarith
· obtain ⟨r,rfl⟩ := Nat.exists_eq_add_of_le (show L≤d by omega)
have hr : R≤r := by omega
have hdim' : h*(2:ℝ)^(L+r)≤Real.log (Module.finrank ℂ (hilbertSpace μ)) := by rwa [finrank_hilbertSpace]
have hs := @medium_exception_decay (hilbertSpace μ) _ _ _ L r h ε t ht hcount
(relabelledUnitary μ e) inferInstance (relabelledUnitary_unitary μ e) hpos hdim' hlarge (hR r hr)
have hb1 : Real.log (blockGap L)*ε*(2:ℝ)^r≤-β*(2:ℝ)^(L+r) := by
have hb0 := min_le_left (-Real.log (blockGap L)*ε/(2:ℝ)^L) (h/16000)
have hp := (le_div_iff₀ (by positivity : (0:ℝ)<(2:ℝ)^L)).mp hb0
have hp := mul_le_mul_of_nonneg_right hp (by positivity : (0:ℝ)≤(2:ℝ)^r)
rw [pow_add]
dsimp [β]
nlinarith
have hb2 : -h*(2:ℝ)^(L+r)/16000≤-β*(2:ℝ)^(L+r) := by
have hp := mul_le_mul_of_nonneg_right (min_le_right (-Real.log (blockGap L)*ε/(2:ℝ)^L) (h/16000))
(by positivity : (0:ℝ)≤(2:ℝ)^(L+r))
dsimp [β]
linarith
apply hs.trans ((add_le_add (Real.exp_le_exp.mpr hb1) (Real.exp_le_exp.mpr hb2)).trans ?_)
apply (exp_two_absorb β ((2:ℝ)^(L+r)) (by nlinarith)).trans
apply Real.exp_le_exp.mpr
have hdmax := le_of_not_ge hhigh
have hp := mul_le_mul_of_nonneg_left hdmax (by positivity : 0≤β/(2*A))
have he : β/(2*A)*(A*(2:ℝ)^(L+r))=β*(2:ℝ)^(L+r)/2 := by field_simp
rw [he] at hp
have hba := mul_le_mul_of_nonneg_right (min_le_right (1/8000:ℝ) (β/(2*A))) hlog
dsimp [a] at *
linarith
end CubeShuffle.Specht
namespace CubeShuffle.Specht
open scoped BigOperators Classical
open Filter UnitaryFinite DimensionEstimates
/-- The nontrivial full-deck spectral regimes, with one absolute exponent.
The two dimension alternatives are precisely those needed by the shape sum. -/
theorem spectral_regimes :
∃ a h : ℝ, 0<a ∧ 0<h ∧ ∀ᶠ d : ℕ in atTop,
∀ (μ : YoungDiagram) (e : Card d ≃ Cell μ), 0<μ.card-μ.rowLen 0 →
(μ.colLen 0:ℝ)≤(μ.card:ℝ)/2 →
‖sampleOperator (V := hilbertSpace μ) (relabelledUnitary μ e) (palindromePerm d)‖≤
Real.exp (-a*Real.log (Module.finrank ℂ (space μ))) ∧
1≤Real.log (Module.finrank ℂ (space μ)) ∧
(((1/2:ℝ)*Real.log μ.card≤Real.log (Module.finrank ℂ (space μ)) ∧
(μ.card-μ.rowLen 0:ℕ)≤Real.log (Module.finrank ℂ (space μ))) ∨
h*(2:ℝ)^d≤Real.log (Module.finrank ℂ (space μ))) := by
obtain ⟨X,hX,hnear⟩ := near_row_spectral
have hXpos : 0<X := by linarith
have hδ : 0<(1:ℝ)/X := by positivity
have hδ2 : (1:ℝ)/X≤1/2 := (div_le_iff₀ hXpos).mpr (by linarith)
obtain ⟨h,hh,hmedium⟩ := medium_dimension (1/X) hδ hδ2
obtain ⟨a₀,ha₀,hlarge⟩ := exponential_dimension_spectral h hh
let a := min (nearFraction/8000) a₀
have ha : 0<a := lt_min (by norm_num [nearFraction]) ha₀
refine ⟨a,h,ha,hh,?_⟩
have hl := (Real.tendsto_log_atTop.comp twopow_tendsto).eventually
(eventually_ge_atTop (2*max (32768000*Real.log 2) 1))
filter_upwards [hlarge,twopow_nat_tendsto.eventually hmedium,hl,
twopow_mul_eventually h hh 1] with d hspec hdim hlog h1
intro μ e hj hc
simp only [Function.comp_apply] at hlog
have hcard : μ.card=2^d := by rw [←card_cell,←Fintype.card_congr e,card_positions]
have hcardR : (μ.card:ℝ)=(2:ℝ)^d := by exact_mod_cast hcard
have hμlog : max (32768000*Real.log 2) 1≤(1/2:ℝ)*Real.log μ.card := by rw [hcardR]; linarith
by_cases hx : X≤(μ.card:ℝ)/(μ.card-μ.rowLen 0:ℕ)
· obtain ⟨hs,hl,hjD⟩ := hnear d μ e hj hx ((le_max_left _ _).trans hμlog)
have h1D : 1≤Real.log (Module.finrank ℂ (space μ)) := ((le_max_right _ _).trans hμlog).trans hl
refine ⟨hs.trans (Real.exp_le_exp.mpr ?_),h1D,Or.inl ⟨hl,hjD⟩⟩
have hp := mul_le_mul_of_nonneg_right (min_le_left (nearFraction/8000) a₀) (by linarith : 0≤Real.log (Module.finrank ℂ (space μ)))
dsimp [a]
linarith
· have htail : (1/X)*(μ.card:ℝ)≤(μ.card:ℝ)-μ.rowLen 0 := by
have hjR : (0:ℝ)<(μ.card-μ.rowLen 0:ℕ) := by exact_mod_cast hj
have hh := (div_lt_iff₀ hjR).mp (lt_of_not_ge hx)
have hs : ((μ.card-μ.rowLen 0:ℕ):ℝ)=(μ.card:ℝ)-μ.rowLen 0 := by
rw [Nat.cast_sub (rowLen_zero_le_card μ)]
rw [hs] at hh
have hd : (μ.card:ℝ)/X≤(μ.card:ℝ)-μ.rowLen 0 :=
(div_le_iff₀ hXpos).mpr (by nlinarith)
convert hd using 1; ring
have hdim' : h*(2:ℝ)^d≤Real.log (Module.finrank ℂ (space μ)) := by
simpa only [Nat.cast_pow,Nat.cast_ofNat] using
hdim μ hcard (by simpa only [hcard] using htail) (by simpa only [hcard] using hc)
have h1D := h1.trans hdim'
refine ⟨(hspec μ e hdim').trans (Real.exp_le_exp.mpr ?_),h1D,Or.inr hdim'⟩
have hp := mul_le_mul_of_nonneg_right (min_le_right (nearFraction/8000) a₀) (by linarith : 0≤Real.log (Module.finrank ℂ (space μ)))
dsimp [a]
linarith
end CubeShuffle.Specht
end OAI