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Add lean source and binary files (part 60)
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import OAI.Computability.DepthThree.EntropyBits
import OAI.Computability.DepthThree.EntropyThreshold
import Mathlib.Algebra.Order.BigOperators.Group.Finset
import Mathlib.Analysis.SpecialFunctions.Pow.Real
import Mathlib.Tactic.Linarith
import Mathlib.Tactic.NormNum
import Mathlib.Tactic.Ring
namespace OAI
universe uDepth1
noncomputable section
namespace DepthThreeLowerBound
open scoped BigOperators
theorem finite_card_le_of_uniform_weight_lower_bound {α : Type uDepth1} [Fintype α]
(A : Finset α) (w : α → ℝ) {δ : ℝ} (hδ : 0 < δ)
(hw : ∀ a, 0 ≤ w a) (hsum : ∑ a, w a ≤ 1)
(hlower : ∀ a ∈ A, δ ≤ w a) : (A.card : ℝ) ≤ 1 / δ := by
classical
have hcard : (A.card : ℝ) * δ ≤ 1 := by
calc
(A.card : ℝ) * δ = ∑ _a ∈ A, δ := by simp
_ ≤ ∑ a ∈ A, w a := Finset.sum_le_sum hlower
_ ≤ ∑ a, w a := Finset.sum_le_sum_of_subset_of_nonneg
(Finset.subset_univ _) (fun a _ _ => hw a)
_ ≤ 1 := hsum
exact (le_div_iff₀ hδ).2 hcard
def bernoulliStringWeight {N : ℕ} (x : ℝ) (z : Fin N → Bool) : ℝ :=
∏ i, if z i = true then x else 1 - x
theorem bernoulliStringWeight_pos {N : ℕ} {x : ℝ} (hx : 0 < x)
(hx1 : x < 1) (z : Fin N → Bool) : 0 < bernoulliStringWeight x z := by
apply Finset.prod_pos
intro i _
split_ifs
· exact hx
· exact sub_pos.mpr hx1
theorem sum_bernoulliStringWeight (N : ℕ) (x : ℝ) :
∑ z : Fin N → Bool, bernoulliStringWeight x z = 1 := by
have hbit : (∑ b : Bool, if b = true then x else 1 - x) = 1 := by
simp [Fintype.univ_bool]
calc
(∑ z : Fin N → Bool, bernoulliStringWeight x z) =
∏ _i : Fin N, ∑ b : Bool, if b = true then x else 1 - x :=
(Fintype.prod_sum (fun (_i : Fin N) (b : Bool) =>
if b = true then x else 1 - x)).symm
_ = 1 := by simp only [hbit, Finset.prod_const_one]
theorem log_bernoulliStringWeight {N : ℕ} {x : ℝ} (hx : 0 < x)
(hx1 : x < 1) (z : Fin N → Bool) :
Real.log (bernoulliStringWeight x z) =
(N : ℝ) * Real.log (1 - x) +
(trueCount z : ℝ) * (Real.log x - Real.log (1 - x)) := by
have hne : ∀ i ∈ (Finset.univ : Finset (Fin N)),
(if z i = true then x else 1 - x) ≠ 0 := by
intro i _
split_ifs
· exact ne_of_gt hx
· exact ne_of_gt (sub_pos.mpr hx1)
rw [bernoulliStringWeight, Real.log_prod hne]
calc
(∑ i : Fin N, Real.log (if z i = true then x else 1 - x)) =
∑ i : Fin N, (Real.log (1 - x) +
(if z i = true then (1 : ℝ) else 0) *
(Real.log x - Real.log (1 - x))) := by
apply Finset.sum_congr rfl
intro i _
split_ifs <;> ring
_ = (N : ℝ) * Real.log (1 - x) +
(trueCount z : ℝ) * (Real.log x - Real.log (1 - x)) := by
rw [Finset.sum_add_distrib, ← Finset.sum_mul, ← trueCount_cast]
simp
theorem bernoulliStringWeight_lower_bound {N : ℕ} {x : ℝ}
(hx : 0 < x) (hxhalf : x ≤ 1 / 2) (z : Fin N → Bool)
(hz : (trueCount z : ℝ) ≤ (N : ℝ) * x) :
Real.exp (-((N : ℝ) * binaryEntropy x * Real.log 2)) ≤
bernoulliStringWeight x z := by
have hx1 : x < 1 := by linarith
have hc : Real.log x - Real.log (1 - x) ≤ 0 := by
apply sub_nonpos.mpr
apply Real.log_le_log hx
linarith
have hmul := mul_le_mul_of_nonpos_right hz hc
have hlog : -((N : ℝ) * binaryEntropy x * Real.log 2) ≤
Real.log (bernoulliStringWeight x z) := by
rw [log_bernoulliStringWeight hx hx1]
calc
-((N : ℝ) * binaryEntropy x * Real.log 2) =
(N : ℝ) * Real.log (1 - x) +
((N : ℝ) * x) * (Real.log x - Real.log (1 - x)) := by
rw [mul_assoc, binaryEntropy_mul_log_two]
ring
_ ≤ (N : ℝ) * Real.log (1 - x) +
(trueCount z : ℝ) * (Real.log x - Real.log (1 - x)) :=
add_le_add_right hmul _
calc
Real.exp (-((N : ℝ) * binaryEntropy x * Real.log 2)) ≤
Real.exp (Real.log (bernoulliStringWeight x z)) :=
Real.exp_le_exp.mpr hlog
_ = bernoulliStringWeight x z :=
Real.exp_log (bernoulliStringWeight_pos hx hx1 z)
def sparseBinaryStrings (N : ℕ) (x : ℝ) : Finset (Fin N → Bool) := by
classical
exact Finset.univ.filter fun z => (trueCount z : ℝ) ≤ (N : ℝ) * x
theorem card_sparse_binary_strings_le (N : ℕ) {x : ℝ}
(hx : 0 < x) (hxhalf : x ≤ 1 / 2) :
((sparseBinaryStrings N x).card : ℝ) ≤
(2 : ℝ) ^ ((N : ℝ) * binaryEntropy x) := by
classical
have hx1 : x < 1 := by linarith
have h := finite_card_le_of_uniform_weight_lower_bound
(sparseBinaryStrings N x) (bernoulliStringWeight x)
(Real.exp_pos (-((N : ℝ) * binaryEntropy x * Real.log 2)))
(fun z => (bernoulliStringWeight_pos hx hx1 z).le)
(sum_bernoulliStringWeight N x).le
(fun z hz => bernoulliStringWeight_lower_bound hx hxhalf z
(Finset.mem_filter.mp hz).2)
calc
((sparseBinaryStrings N x).card : ℝ) ≤
1 / Real.exp (-((N : ℝ) * binaryEntropy x * Real.log 2)) := h
_ = Real.exp ((N : ℝ) * binaryEntropy x * Real.log 2) := by
rw [one_div, Real.exp_neg, inv_inv]
_ = (2 : ℝ) ^ ((N : ℝ) * binaryEntropy x) := by
rw [Real.rpow_def_of_pos (show (0 : ℝ) < 2 by norm_num)]
congr 1
ring
end DepthThreeLowerBound
end
end OAI