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/-
Copyright (c) 2024 Damien Thomine. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damien Thomine, Pietro Monticone
-/
import Mathlib.Dynamics.TopologicalEntropy.CoverEntropy
/-!
# Topological entropy via nets
We implement Bowen-Dinaburg's definitions of the topological entropy, via nets.
The major design decisions are the same as in `Mathlib.Dynamics.TopologicalEntropy.CoverEntropy`,
and are explained in detail there: use of uniform spaces, definition of the topological entropy of
a subset, and values taken in `EReal`.
Given a map `T : X → X` and a subset `F ⊆ X`, the topological entropy is loosely defined using
nets as the exponential growth (in `n`) of the number of distinguishable orbits of length `n`
starting from `F`. More precisely, given an entourage `U`, two orbits of length `n` can be
distinguished if there exists some index `k < n` such that `T^[k] x` and `T^[k] y` are far enough
(i.e. `(T^[k] x, T^[k] y)` is not in `U`). The maximal number of distinguishable orbits of
length `n` is `netMaxcard T F U n`, and its exponential growth `netEntropyEntourage T F U`. This
quantity increases when `U` decreases, and a definition of the topological entropy is
`⨆ U ∈ 𝓤 X, netEntropyInfEntourage T F U`.
The definition of topological entropy using nets coincides with the definition using covers.
Instead of defining a new notion of topological entropy, we prove that
`coverEntropy` coincides with `⨆ U ∈ 𝓤 X, netEntropyEntourage T F U`.
## Main definitions
- `IsDynNetIn`: property that dynamical balls centered on a subset `s` of `F` are disjoint.
- `netMaxcard`: maximal cardinality of a dynamical net. Takes values in `ℕ∞`.
- `netEntropyInfEntourage`/`netEntropyEntourage`: exponential growth of `netMaxcard`. The former is
defined with a `liminf`, the latter with a `limsup`. Take values in `EReal`.
## Implementation notes
As when using covers, there are two competing definitions `netEntropyInfEntourage` and
`netEntropyEntourage` in this file: one uses a `liminf`, the other a `limsup`. When using covers,
we chose the `limsup` definition as the default.
## Main results
- `coverEntropy_eq_iSup_netEntropyEntourage`: equality between the notions of topological entropy
defined with covers and with nets. Has a variant for `coverEntropyInf`.
## Tags
net, entropy
## TODO
Get versions of the topological entropy on (pseudo-e)metric spaces.
-/
namespace Dynamics
open Set Uniformity UniformSpace
variable {X : Type*}
/-! ### Dynamical nets -/
/-- Given a subset `F`, an entourage `U` and an integer `n`, a subset `s` of `F` is a
`(U, n)`-dynamical net of `F` if no two orbits of length `n` of points in `s` shadow each other. -/
def IsDynNetIn (T : X → X) (F : Set X) (U : Set (X × X)) (n : ℕ) (s : Set X) : Prop :=
s ⊆ F ∧ s.PairwiseDisjoint (fun x : X ↦ ball x (dynEntourage T U n))
lemma IsDynNetIn.of_le {T : X → X} {F : Set X} {U : Set (X × X)} {m n : ℕ} (m_n : m ≤ n) {s : Set X}
(h : IsDynNetIn T F U m s) :
IsDynNetIn T F U n s :=
⟨h.1, PairwiseDisjoint.mono h.2 (fun x ↦ ball_mono (dynEntourage_antitone T U m_n) x)⟩
lemma IsDynNetIn.of_entourage_subset {T : X → X} {F : Set X} {U V : Set (X × X)} (U_V : U ⊆ V)
{n : ℕ} {s : Set X} (h : IsDynNetIn T F V n s) :
IsDynNetIn T F U n s :=
⟨h.1, PairwiseDisjoint.mono h.2 (fun x ↦ ball_mono (dynEntourage_monotone T n U_V) x)⟩
lemma isDynNetIn_empty {T : X → X} {F : Set X} {U : Set (X × X)} {n : ℕ} :
IsDynNetIn T F U n ∅ :=
⟨empty_subset F, pairwise_empty _⟩
lemma isDynNetIn_singleton (T : X → X) {F : Set X} (U : Set (X × X)) (n : ℕ) {x : X} (h : x ∈ F) :
IsDynNetIn T F U n {x} :=
⟨singleton_subset_iff.2 h, pairwise_singleton x _⟩
/-- Given an entourage `U` and a time `n`, a dynamical net has a smaller cardinality than
a dynamical cover. This lemma is the first of two key results to compare two versions of
topological entropy: with cover and with nets, the second being `coverMincard_le_netMaxcard`. -/
lemma IsDynNetIn.card_le_card_of_isDynCoverOf {T : X → X} {F : Set X} {U : Set (X × X)}
(U_symm : IsSymmetricRel U) {n : ℕ} {s t : Finset X} (hs : IsDynNetIn T F U n s)
(ht : IsDynCoverOf T F U n t) :
s.card ≤ t.card := by
have (x : X) (x_s : x ∈ s) : ∃ z ∈ t, x ∈ ball z (dynEntourage T U n) := by
specialize ht (hs.1 x_s)
simp only [Finset.coe_sort_coe, mem_iUnion, Subtype.exists, exists_prop] at ht
exact ht
choose! F s_t using this
simp only [mem_ball_symmetry (U_symm.dynEntourage T n)] at s_t
apply Finset.card_le_card_of_injOn F (fun x x_s ↦ (s_t x x_s).1)
exact fun x x_s y y_s Fx_Fy ↦
PairwiseDisjoint.elim_set hs.2 x_s y_s (F x) (s_t x x_s).2 (Fx_Fy ▸ (s_t y y_s).2)
/-! ### Maximal cardinality of dynamical nets -/
/-- The largest cardinality of a `(U, n)`-dynamical net of `F`. Takes values in `ℕ∞`, and is
infinite if and only if `F` admits nets of arbitrarily large size. -/
noncomputable def netMaxcard (T : X → X) (F : Set X) (U : Set (X × X)) (n : ℕ) : ℕ∞ :=
⨆ (s : Finset X) (_ : IsDynNetIn T F U n s), (s.card : ℕ∞)
lemma IsDynNetIn.card_le_netMaxcard {T : X → X} {F : Set X} {U : Set (X × X)} {n : ℕ} {s : Finset X}
(h : IsDynNetIn T F U n s) :
s.card ≤ netMaxcard T F U n :=
le_iSup₂ (α := ℕ∞) s h
lemma netMaxcard_monotone_time (T : X → X) (F : Set X) (U : Set (X × X)) :
Monotone (fun n : ℕ ↦ netMaxcard T F U n) :=
fun _ _ m_n ↦ biSup_mono (fun _ h ↦ h.of_le m_n)
lemma netMaxcard_antitone (T : X → X) (F : Set X) (n : ℕ) :
Antitone (fun U : Set (X × X) ↦ netMaxcard T F U n) :=
fun _ _ U_V ↦ biSup_mono (fun _ h ↦ h.of_entourage_subset U_V)
lemma netMaxcard_finite_iff (T : X → X) (F : Set X) (U : Set (X × X)) (n : ℕ) :
netMaxcard T F U n < ⊤ ↔
∃ s : Finset X, IsDynNetIn T F U n s ∧ (s.card : ℕ∞) = netMaxcard T F U n := by
apply Iff.intro <;> intro h
· rcases WithTop.ne_top_iff_exists.1 h.ne with ⟨k, k_max⟩
rw [← k_max]
simp only [ENat.some_eq_coe, Nat.cast_inj]
-- The criterion we want to use is `Nat.sSup_mem`. We rewrite `netMaxcard` with an `sSup`,
-- then check its `BddAbove` and `Nonempty` hypotheses.
have : netMaxcard T F U n
= sSup (WithTop.some '' (Finset.card '' {s : Finset X | IsDynNetIn T F U n s})) := by
rw [netMaxcard, ← image_comp, sSup_image]
simp only [mem_setOf_eq, ENat.some_eq_coe, Function.comp_apply]
rw [this] at k_max
have h_bdda : BddAbove (Finset.card '' {s : Finset X | IsDynNetIn T F U n s}) := by
refine ⟨k, mem_upperBounds.2 ?_⟩
simp only [mem_image, mem_setOf_eq, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂]
intro s h
rw [← WithTop.coe_le_coe, k_max]
apply le_sSup
simp only [ENat.some_eq_coe, mem_image, mem_setOf_eq, Nat.cast_inj, exists_eq_right]
exact Filter.frequently_principal.mp fun a ↦ a h rfl
have h_nemp : (Finset.card '' {s : Finset X | IsDynNetIn T F U n s}).Nonempty := by
refine ⟨0, ?_⟩
simp only [mem_image, mem_setOf_eq, Finset.card_eq_zero, exists_eq_right, Finset.coe_empty]
exact isDynNetIn_empty
rw [← WithTop.coe_sSup' h_bdda, ENat.some_eq_coe, Nat.cast_inj] at k_max
have key := Nat.sSup_mem h_nemp h_bdda
rw [← k_max, mem_image] at key
simp only [mem_setOf_eq] at key
exact key
· rcases h with ⟨s, _, s_netMaxcard⟩
rw [← s_netMaxcard]
exact WithTop.coe_lt_top s.card
@[simp]
lemma netMaxcard_empty {T : X → X} {U : Set (X × X)} {n : ℕ} : netMaxcard T ∅ U n = 0 := by
rw [netMaxcard, ← bot_eq_zero, iSup₂_eq_bot]
intro s s_net
replace s_net := subset_empty_iff.1 s_net.1
norm_cast at s_net
rw [s_net, Finset.card_empty, CharP.cast_eq_zero, bot_eq_zero']
lemma netMaxcard_eq_zero_iff (T : X → X) (F : Set X) (U : Set (X × X)) (n : ℕ) :
netMaxcard T F U n = 0 ↔ F = ∅ := by
refine Iff.intro (fun h ↦ ?_) (fun h ↦ by rw [h, netMaxcard_empty])
rw [eq_empty_iff_forall_not_mem]
intro x x_F
have key := isDynNetIn_singleton T U n x_F
rw [← Finset.coe_singleton] at key
replace key := key.card_le_netMaxcard
rw [Finset.card_singleton, Nat.cast_one, h] at key
exact key.not_lt zero_lt_one
lemma one_le_netMaxcard_iff (T : X → X) (F : Set X) (U : Set (X × X)) (n : ℕ) :
1 ≤ netMaxcard T F U n ↔ F.Nonempty := by
rw [ENat.one_le_iff_ne_zero, nonempty_iff_ne_empty]
exact not_iff_not.2 (netMaxcard_eq_zero_iff T F U n)
lemma netMaxcard_zero (T : X → X) {F : Set X} (h : F.Nonempty) (U : Set (X × X)) :
netMaxcard T F U 0 = 1 := by
apply (iSup₂_le _).antisymm ((one_le_netMaxcard_iff T F U 0).2 h)
intro s ⟨_, s_net⟩
simp only [ball, dynEntourage_zero, preimage_univ] at s_net
norm_cast
refine Finset.card_le_one.2 (fun x x_s y y_s ↦ ?_)
exact PairwiseDisjoint.elim_set s_net x_s y_s x (mem_univ x) (mem_univ x)
lemma netMaxcard_univ (T : X → X) {F : Set X} (h : F.Nonempty) (n : ℕ) :
netMaxcard T F univ n = 1 := by
apply (iSup₂_le _).antisymm ((one_le_netMaxcard_iff T F univ n).2 h)
intro s ⟨_, s_net⟩
simp only [ball, dynEntourage_univ, preimage_univ] at s_net
norm_cast
refine Finset.card_le_one.2 (fun x x_s y y_s ↦ ?_)
exact PairwiseDisjoint.elim_set s_net x_s y_s x (mem_univ x) (mem_univ x)
lemma netMaxcard_infinite_iff (T : X → X) (F : Set X) (U : Set (X × X)) (n : ℕ) :
netMaxcard T F U n = ⊤ ↔ ∀ k : ℕ, ∃ s : Finset X, IsDynNetIn T F U n s ∧ k ≤ s.card := by
apply Iff.intro <;> intro h
· intro k
rw [netMaxcard, iSup_subtype', iSup_eq_top] at h
specialize h k (ENat.coe_lt_top k)
simp only [Nat.cast_lt, Subtype.exists, exists_prop] at h
rcases h with ⟨s, s_net, s_k⟩
exact ⟨s, ⟨s_net, s_k.le⟩⟩
· refine WithTop.eq_top_iff_forall_gt.2 fun k ↦ ?_
specialize h (k + 1)
rcases h with ⟨s, s_net, s_card⟩
apply s_net.card_le_netMaxcard.trans_lt'
rw [ENat.some_eq_coe, Nat.cast_lt]
exact (lt_add_one k).trans_le s_card
lemma netMaxcard_le_coverMincard (T : X → X) (F : Set X) {U : Set (X × X)}
(U_symm : IsSymmetricRel U) (n : ℕ) :
netMaxcard T F U n ≤ coverMincard T F U n := by
rcases eq_top_or_lt_top (coverMincard T F U n) with h | h
· exact h ▸ le_top
· rcases ((coverMincard_finite_iff T F U n).1 h) with ⟨t, t_cover, t_mincard⟩
rw [← t_mincard]
exact iSup₂_le (fun s s_net ↦ Nat.cast_le.2 (s_net.card_le_card_of_isDynCoverOf U_symm t_cover))
/-- Given an entourage `U` and a time `n`, a minimal dynamical cover by `U ○ U` has a smaller
cardinality than a maximal dynamical net by `U`. This lemma is the second of two key results to
compare two versions topological entropy: with cover and with nets. -/
lemma coverMincard_le_netMaxcard (T : X → X) (F : Set X) {U : Set (X × X)} (U_rfl : idRel ⊆ U)
(U_symm : IsSymmetricRel U) (n : ℕ) :
coverMincard T F (U ○ U) n ≤ netMaxcard T F U n := by
classical
-- WLOG, there exists a maximal dynamical net `s`.
rcases (eq_top_or_lt_top (netMaxcard T F U n)) with h | h
· exact h ▸ le_top
rcases ((netMaxcard_finite_iff T F U n).1 h) with ⟨s, s_net, s_netMaxcard⟩
rw [← s_netMaxcard]
apply IsDynCoverOf.coverMincard_le_card
-- We have to check that `s` is a cover for `dynEntourage T F (U ○ U) n`.
-- If `s` is not a cover, then we can add to `s` a point `x` which is not covered
-- and get a new net. This contradicts the maximality of `s`.
by_contra h
rcases not_subset.1 h with ⟨x, x_F, x_uncov⟩
simp only [Finset.mem_coe, mem_iUnion, exists_prop, not_exists, not_and] at x_uncov
have larger_net : IsDynNetIn T F U n (insert x s) :=
And.intro (insert_subset x_F s_net.1) (pairwiseDisjoint_insert.2 (And.intro s_net.2
(fun y y_s _ ↦ (disjoint_left.2 (fun z z_x z_y ↦ x_uncov y y_s
(mem_ball_dynEntourage_comp T n U_symm x y (nonempty_of_mem ⟨z_x, z_y⟩)))))))
rw [← Finset.coe_insert x s] at larger_net
apply larger_net.card_le_netMaxcard.not_lt
rw [← s_netMaxcard, Nat.cast_lt]
refine (lt_add_one s.card).trans_eq (Finset.card_insert_of_not_mem fun x_s ↦ ?_).symm
apply x_uncov x x_s (ball_mono (dynEntourage_monotone T n (subset_comp_self U_rfl)) x
(ball_mono (idRel_subset_dynEntourage T U_rfl n) x _))
simp only [ball, mem_preimage, mem_idRel]
open ENNReal EReal
lemma log_netMaxcard_nonneg (T : X → X) {F : Set X} (h : F.Nonempty) (U : Set (X × X)) (n : ℕ) :
0 ≤ log (netMaxcard T F U n) := by
apply zero_le_log_iff.2
rw [← ENat.toENNReal_one, ENat.toENNReal_le]
exact (one_le_netMaxcard_iff T F U n).2 h
/-! ### Net entropy of entourages -/
open Filter
/-- The entropy of an entourage `U`, defined as the exponential rate of growth of the size of the
largest `(U, n)`-dynamical net of `F`. Takes values in the space of extended real numbers
`[-∞,+∞]`. This version uses a `limsup`, and is chosen as the default definition. -/
noncomputable def netEntropyEntourage (T : X → X) (F : Set X) (U : Set (X × X)) :=
atTop.limsup fun n : ℕ ↦ log (netMaxcard T F U n) / n
/-- The entropy of an entourage `U`, defined as the exponential rate of growth of the size of the
largest `(U, n)`-dynamical net of `F`. Takes values in the space of extended real numbers
`[-∞,+∞]`. This version uses a `liminf`, and is an alternative definition. -/
noncomputable def netEntropyInfEntourage (T : X → X) (F : Set X) (U : Set (X × X)) :=
atTop.liminf fun n : ℕ ↦ log (netMaxcard T F U n) / n
lemma netEntropyInfEntourage_antitone (T : X → X) (F : Set X) :
Antitone (fun U : Set (X × X) ↦ netEntropyInfEntourage T F U) :=
fun _ _ U_V ↦ (liminf_le_liminf) (Eventually.of_forall
fun n ↦ monotone_div_right_of_nonneg (Nat.cast_nonneg' n)
(log_monotone (ENat.toENNReal_mono (netMaxcard_antitone T F n U_V))))
lemma netEntropyEntourage_antitone (T : X → X) (F : Set X) :
Antitone (fun U : Set (X × X) ↦ netEntropyEntourage T F U) :=
fun _ _ U_V ↦ (limsup_le_limsup) (Eventually.of_forall
fun n ↦ (monotone_div_right_of_nonneg (Nat.cast_nonneg' n)
(log_monotone (ENat.toENNReal_mono (netMaxcard_antitone T F n U_V)))))
lemma netEntropyInfEntourage_le_netEntropyEntourage (T : X → X) (F : Set X) (U : Set (X × X)) :
netEntropyInfEntourage T F U ≤ netEntropyEntourage T F U := liminf_le_limsup
@[simp]
lemma netEntropyEntourage_empty {T : X → X} {U : Set (X × X)} : netEntropyEntourage T ∅ U = ⊥ := by
suffices h : ∀ᶠ n : ℕ in atTop, log (netMaxcard T ∅ U n) / n = ⊥ by
rw [netEntropyEntourage, limsup_congr h]
exact limsup_const ⊥
simp only [netMaxcard_empty, ENat.toENNReal_zero, log_zero, eventually_atTop]
exact ⟨1, fun n n_pos ↦ bot_div_of_pos_ne_top (Nat.cast_pos'.2 n_pos) (natCast_ne_top n)⟩
@[simp]
lemma netEntropyInfEntourage_empty {T : X → X} {U : Set (X × X)} :
netEntropyInfEntourage T ∅ U = ⊥ :=
eq_bot_mono (netEntropyInfEntourage_le_netEntropyEntourage T ∅ U) netEntropyEntourage_empty
lemma netEntropyInfEntourage_nonneg (T : X → X) {F : Set X} (h : F.Nonempty) (U : Set (X × X)) :
0 ≤ netEntropyInfEntourage T F U :=
(le_iInf fun n ↦ div_nonneg (log_netMaxcard_nonneg T h U n) (Nat.cast_nonneg' n)).trans
iInf_le_liminf
lemma netEntropyEntourage_nonneg (T : X → X) {F : Set X} (h : F.Nonempty) (U : Set (X × X)) :
0 ≤ netEntropyEntourage T F U :=
(netEntropyInfEntourage_nonneg T h U).trans (netEntropyInfEntourage_le_netEntropyEntourage T F U)
lemma netEntropyInfEntourage_univ (T : X → X) {F : Set X} (h : F.Nonempty) :
netEntropyInfEntourage T F univ = 0 := by simp [netEntropyInfEntourage, netMaxcard_univ T h]
lemma netEntropyEntourage_univ (T : X → X) {F : Set X} (h : F.Nonempty) :
netEntropyEntourage T F univ = 0 := by simp [netEntropyEntourage, netMaxcard_univ T h]
lemma netEntropyInfEntourage_le_coverEntropyInfEntourage (T : X → X) (F : Set X) {U : Set (X × X)}
(U_symm : IsSymmetricRel U) :
netEntropyInfEntourage T F U ≤ coverEntropyInfEntourage T F U :=
(liminf_le_liminf) (Eventually.of_forall fun n ↦ (div_le_div_right_of_nonneg (Nat.cast_nonneg' n)
(log_monotone (ENat.toENNReal_le.2 (netMaxcard_le_coverMincard T F U_symm n)))))
lemma coverEntropyInfEntourage_le_netEntropyInfEntourage (T : X → X) (F : Set X) {U : Set (X × X)}
(U_rfl : idRel ⊆ U) (U_symm : IsSymmetricRel U) :
coverEntropyInfEntourage T F (U ○ U) ≤ netEntropyInfEntourage T F U := by
refine (liminf_le_liminf) (Eventually.of_forall fun n ↦ ?_)
apply div_le_div_right_of_nonneg (Nat.cast_nonneg' n) (log_monotone _)
exact ENat.toENNReal_le.2 (coverMincard_le_netMaxcard T F U_rfl U_symm n)
lemma netEntropyEntourage_le_coverEntropyEntourage (T : X → X) (F : Set X) {U : Set (X × X)}
(U_symm : IsSymmetricRel U) :
netEntropyEntourage T F U ≤ coverEntropyEntourage T F U := by
refine (limsup_le_limsup) (Eventually.of_forall fun n ↦ ?_)
apply div_le_div_right_of_nonneg (Nat.cast_nonneg' n) (log_monotone _)
exact ENat.toENNReal_le.2 (netMaxcard_le_coverMincard T F U_symm n)
lemma coverEntropyEntourage_le_netEntropyEntourage (T : X → X) (F : Set X) {U : Set (X × X)}
(U_rfl : idRel ⊆ U) (U_symm : IsSymmetricRel U) :
coverEntropyEntourage T F (U ○ U) ≤ netEntropyEntourage T F U := by
refine (limsup_le_limsup) (Eventually.of_forall fun n ↦ ?_)
apply div_le_div_right_of_nonneg (Nat.cast_nonneg' n) (log_monotone _)
exact ENat.toENNReal_le.2 (coverMincard_le_netMaxcard T F U_rfl U_symm n)
/-! ### Relationship with entropy via covers -/
variable [UniformSpace X] (T : X → X) (F : Set X)
/-- Bowen-Dinaburg's definition of topological entropy using nets is
`⨆ U ∈ 𝓤 X, netEntropyEntourage T F U`. This quantity is the same as the topological entropy using
covers, so there is no need to define a new notion of topological entropy. This version of the
theorem relates the `liminf` versions of topological entropy. -/
theorem coverEntropyInf_eq_iSup_netEntropyInfEntourage :
coverEntropyInf T F = ⨆ U ∈ 𝓤 X, netEntropyInfEntourage T F U := by
apply le_antisymm <;> refine iSup₂_le fun U U_uni ↦ ?_
· rcases (comp_symm_mem_uniformity_sets U_uni) with ⟨V, V_uni, V_symm, V_comp_U⟩
apply (coverEntropyInfEntourage_antitone T F V_comp_U).trans (le_iSup₂_of_le V V_uni _)
exact coverEntropyInfEntourage_le_netEntropyInfEntourage T F (refl_le_uniformity V_uni) V_symm
· apply (netEntropyInfEntourage_antitone T F (symmetrizeRel_subset_self U)).trans
apply (le_iSup₂ (symmetrizeRel U) (symmetrize_mem_uniformity U_uni)).trans'
exact netEntropyInfEntourage_le_coverEntropyInfEntourage T F (symmetric_symmetrizeRel U)
/-- Bowen-Dinaburg's definition of topological entropy using nets is
`⨆ U ∈ 𝓤 X, netEntropyEntourage T F U`. This quantity is the same as the topological entropy using
covers, so there is no need to define a new notion of topological entropy. This version of the
theorem relates the `limsup` versions of topological entropy. -/
theorem coverEntropy_eq_iSup_netEntropyEntourage :
coverEntropy T F = ⨆ U ∈ 𝓤 X, netEntropyEntourage T F U := by
apply le_antisymm <;> refine iSup₂_le fun U U_uni ↦ ?_
· rcases (comp_symm_mem_uniformity_sets U_uni) with ⟨V, V_uni, V_symm, V_comp_U⟩
apply (coverEntropyEntourage_antitone T F V_comp_U).trans (le_iSup₂_of_le V V_uni _)
exact coverEntropyEntourage_le_netEntropyEntourage T F (refl_le_uniformity V_uni) V_symm
· apply (netEntropyEntourage_antitone T F (symmetrizeRel_subset_self U)).trans
apply (le_iSup₂ (symmetrizeRel U) (symmetrize_mem_uniformity U_uni)).trans'
exact netEntropyEntourage_le_coverEntropyEntourage T F (symmetric_symmetrizeRel U)
lemma coverEntropyInf_eq_iSup_basis_netEntropyInfEntourage {ι : Sort*} {p : ι → Prop}
{s : ι → Set (X × X)} (h : (𝓤 X).HasBasis p s) (T : X → X) (F : Set X) :
coverEntropyInf T F = ⨆ (i : ι) (_ : p i), netEntropyInfEntourage T F (s i) := by
rw [coverEntropyInf_eq_iSup_netEntropyInfEntourage T F]
apply (iSup₂_mono' fun i h_i ↦ ⟨s i, HasBasis.mem_of_mem h h_i, le_refl _⟩).antisymm'
refine iSup₂_le fun U U_uni ↦ ?_
rcases (HasBasis.mem_iff h).1 U_uni with ⟨i, h_i, si_U⟩
apply (netEntropyInfEntourage_antitone T F si_U).trans
exact le_iSup₂ (f := fun (i : ι) (_ : p i) ↦ netEntropyInfEntourage T F (s i)) i h_i
lemma coverEntropy_eq_iSup_basis_netEntropyEntourage {ι : Sort*} {p : ι → Prop}
{s : ι → Set (X × X)} (h : (𝓤 X).HasBasis p s) (T : X → X) (F : Set X) :
coverEntropy T F = ⨆ (i : ι) (_ : p i), netEntropyEntourage T F (s i) := by
rw [coverEntropy_eq_iSup_netEntropyEntourage T F]
apply (iSup₂_mono' fun i h_i ↦ ⟨s i, HasBasis.mem_of_mem h h_i, le_refl _⟩).antisymm'
refine iSup₂_le fun U U_uni ↦ ?_
rcases (HasBasis.mem_iff h).1 U_uni with ⟨i, h_i, si_U⟩
apply (netEntropyEntourage_antitone T F si_U).trans _
exact le_iSup₂ (f := fun (i : ι) (_ : p i) ↦ netEntropyEntourage T F (s i)) i h_i
lemma netEntropyInfEntourage_le_coverEntropyInf {U : Set (X × X)} (h : U ∈ 𝓤 X) :
netEntropyInfEntourage T F U ≤ coverEntropyInf T F :=
coverEntropyInf_eq_iSup_netEntropyInfEntourage T F ▸
le_iSup₂ (f := fun (U : Set (X × X)) (_ : U ∈ 𝓤 X) ↦ netEntropyInfEntourage T F U) U h
lemma netEntropyEntourage_le_coverEntropy {U : Set (X × X)} (h : U ∈ 𝓤 X) :
netEntropyEntourage T F U ≤ coverEntropy T F :=
coverEntropy_eq_iSup_netEntropyEntourage T F ▸
le_iSup₂ (f := fun (U : Set (X × X)) (_ : U ∈ 𝓤 X) ↦ netEntropyEntourage T F U) U h
end Dynamics