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module
public import RandomSystems.Distance.Transcript
public import RandomSystems.Converter.ConverterAttachment
/-!
# Decision probabilities
A deterministic distinguisher is compatible with a domain when, on every resource on the
domain, it queries only admitted inputs and replies along every possible transcript; with
its finite bound it then produces a decision. Its decision probability on a resource is the
probability of the decision `1` in the completed transcript law. An environment followed by
an event test decides `1` with the probability of the event, so decision gaps and the
statistical distance of transcript laws bound one another. On a presentation of a resource
by deterministic resources, the decision probability is the probability of deciding `1` on
a sample.
## Main definitions
* `Domain.Compatible`: environments compatible with every resource on a domain
* `Domain.DecisionCompatible`: deterministic distinguishers compatible with a domain
* `RandomSystem.decisionProbability`: the probability of the decision `1`
* `RandomSystem.transcriptDistance`: the largest statistical distance of completed
transcript laws under compatible query-bounded environments
## Main results
* `RandomSystem.transcriptDistance_le`: a bound in `ℝ≥0` on the transcript laws under every
environment bounds the transcript distance
* `RandomSystem.transcriptDistance_eq_iSup_domainBound`: the supremum may range over the
compatible environments globally bounded by `𝒟.bound`, observed at `𝒟.bound`
* `RandomSystem.decisionProbability_envProbe`: an environment followed by an event test
decides `1` with the probability of the event
* `RandomSystem.decisionProbability_gap_le`: decision gaps are at most the transcript
distance
* `RandomSystem.decisionProbability_of_presents`: the decision probability on a
presentation
* `Domain.decisionCompatible_iff_deterministic`: compatibility is checked on the
deterministic resources of the domain
## Observing at the domain bound
For compatible `E` with `QueryBounded n E`, and `E' = DDE.limitQueries E 𝒟.bound`, every
term of the defining supremum is a term at the domain bound, by exact law equalities:
```text
sLaw R E n = sLaw R E 𝒟.bound (sLaw_eq_domainBound: possible queries lie below 𝒟.bound)
= sLaw R E' 𝒟.bound (sLaw_limitQueries; E' is compatible and globally bounded)
```
Here `R` replies at the queried interface, as `Domain.Compatible` requires. `E'` stops after
`𝒟.bound` replies on every reply history, including impossible ones; compatibility alone does
not give this bound.
-/
@[expose] public section
namespace SystemAlgebra
open Probability
open scoped NNReal
lemma FollowsStrategy.queries_eq {A B : Type} {e : List B →. A} {h : List (A × B)}
(hc : FollowsStrategy e h) : h.map Prod.fst = qsOf e (h.map Prod.snd) := by
induction h using List.reverseRecOn with
| nil => rfl
| append_singleton h z ih =>
obtain ⟨hc, hz⟩ := FollowsStrategy.snoc_iff.mp hc
simp only [List.map_append, List.map_singleton]
rw [qsOf_snoc hz, ih hc]
lemma FollowsStrategy.fits {I : Type} {X Y : I → Type}
{e : List (Σ i, Y i) →. Σ i, X i}
{h : List ((Σ i, X i) × (Σ i, Y i))} (hc : FollowsStrategy e h)
(hl : ∀ z ∈ h, z.2.1 = z.1.1) : EFits e (h.map Prod.snd) := by
induction h using List.reverseRecOn with
| nil => exact EFits.nil
| append_singleton h z ih =>
obtain ⟨hc, hz⟩ := FollowsStrategy.snoc_iff.mp hc
simp only [List.map_append, List.map_singleton]
exact (ih hc (fun a ha => hl a (by simp [ha]))).snoc hz (hl z (by simp))
/-- A probe is defined along precisely the environment's valid reply paths. -/
lemma envProbe_reach {I : Type} {X Y : I → Type}
{E : DDE (Σ i, X i) (Σ i, Y i)}
(A : List (Σ i, X i) × List (Σ i, Y i) → Prop)
{ys : List (Σ i, Y i)} (hv : EFits E.1 ys) : Reach (envProbe E A) (dHist ys) := by
induction ys using List.reverseRecOn with
| nil =>
change Reach (envProbe E A) ([] ++ [⟨.start, ()⟩])
apply reach_snoc_iff.mpr
refine ⟨reach_nil _, ?_⟩
rw [show ([] ++ [⟨.start, ()⟩] : List (Σ p, dIn Y p)) = dHist [] from rfl,
envProbe_dHist EFits.nil]
simp only [envReply]
split_ifs <;> exact Part.some_dom _
| append_singleton ys y ih =>
have he : dHist (ys ++ [y]) = dHist ys ++ [envIn y] := by simp [dHist]
rw [he, reach_snoc_iff]
refine ⟨ih hv.of_snoc.1, ?_⟩
rw [← he, envProbe_dHist hv]
simp only [envReply]
split_ifs <;> exact Part.some_dom _
lemma envOf_trim_envProbe {I : Type} {X Y : I → Type}
{E : DDE (Σ i, X i) (Σ i, Y i)}
{A : List (Σ i, X i) × List (Σ i, Y i) → Prop}
{ys} (hv : EFits E.1 ys) : envOf (trim (envProbe E A)) ys = E.1 ys := by
change ((trim (envProbe E A)) (dHist ys)).bind _ = _
rw [trim, ite_eq_left (envProbe_reach A hv)]
exact envOf_envProbe hv
namespace RandomSystem
variable {I : Type} {X Y : I → Type} [Fintype (Σ i, X i)] [Fintype (Σ i, Y i)]
{D : Domain (Σ i, X i) (Σ i, Y i)}
lemma RepliesAtQueriedInterface.history
{R : RandomSystem (Σ i, X i) (Σ i, Y i) D} (hr : R.RepliesAtQueriedInterface)
{h} (hm : R h ≠ 0) : ∀ z ∈ h, z.2.1 = z.1.1 := by
induction h using List.reverseRecOn with
| nil => simp
| append_singleton h z ih =>
have hp : R h ≠ 0 := fun hz => hm (R.mass_eq_zero_of_prefix ⟨[z], rfl⟩ hz)
intro w hw
rcases List.mem_append.mp hw with hw | hw
· exact ih hp w hw
· obtain rfl := List.mem_singleton.mp hw
exact Classical.byContradiction (fun hn => hm (hr h w.1 w.2 hn))
/-- Canonicalizing the probe leaves exactly the original query strategy on
all possible responding-resource transcripts. -/
lemma followsStrategy_trim_envProbe_iff
{R : RandomSystem (Σ i, X i) (Σ i, Y i) D} (hr : R.RepliesAtQueriedInterface)
(E : DDE (Σ i, X i) (Σ i, Y i))
(A : List (Σ i, X i) × List (Σ i, Y i) → Prop)
{h} (hm : R h ≠ 0) :
FollowsStrategy (envOf (trim (envProbe E A))) h ↔ FollowsStrategy E.1 h := by
induction h using List.reverseRecOn with
| nil => exact iff_of_true FollowsStrategy.nil FollowsStrategy.nil
| append_singleton h z ih =>
have hp : R h ≠ 0 := fun hz => hm (R.mass_eq_zero_of_prefix ⟨[z], rfl⟩ hz)
rw [FollowsStrategy.snoc_iff, FollowsStrategy.snoc_iff, ih hp]
exact and_congr_right fun hc => by
rw [envOf_trim_envProbe (hc.fits (hr.history hp))]
lemma sLaw_trim_envProbe
(R : RandomSystem (Σ i, X i) (Σ i, Y i) D) (hr : R.RepliesAtQueriedInterface)
(E : DDE (Σ i, X i) (Σ i, Y i))
(A : List (Σ i, X i) × List (Σ i, Y i) → Prop) (n : ℕ) :
R.sLaw (envOf (trim (envProbe E A))) n = R.sLaw E.1 n := by
classical
ext h
rw [sLaw_apply, sLaw_apply]
by_cases hm : R h = 0
· simp [hm]
· have hc := followsStrategy_trim_envProbe_iff hr E A hm
by_cases hh : FollowsStrategy E.1 h
· simp only [Good, hc, hh, true_and, Done,
envOf_trim_envProbe (hh.fits (hr.history hm))]
· simp only [Good, hc, hh, false_and, ite_false]
/-- A completed transcript leaves a query-bounded environment without a next query. -/
lemma sLaw_complete {E : DDE (Σ i, X i) (Σ i, Y i)} {n : ℕ} (hn : QueryBounded n E)
(R : RandomSystem (Σ i, X i) (Σ i, Y i) D) {h} (hh : h ∈ (R.sLaw E.1 n).support) :
¬ (E.1 (h.map Prod.snd)).Dom := by
have hp := Finsupp.mem_support_iff.mp hh
have hg : Good E.1 n h := by
by_contra hg
exact hp (by simp [sLaw_apply, hg])
rcases hg.2 with he | ⟨_, hs⟩
· intro hd
have hb := hn _ hd
simp only [List.length_map, he] at hb
exact Nat.lt_irrefl n hb
· exact hs
end RandomSystem
variable {I : Type} [Fintype I] {X Y : I → Type} [∀ i, Fintype (X i)] [∀ i, Fintype (Y i)]
namespace Domain
/-- An environment is compatible with a domain when it is compatible with every resource on
the domain. -/
def Compatible (𝒟 : Domain (Σ i, X i) (Σ i, Y i)) (E : DDE (Σ i, X i) (Σ i, Y i)) : Prop :=
∀ R : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟, R.RepliesAtQueriedInterface → R.Compatible E.1
/-- A deterministic distinguisher is compatible with a domain when, on every resource on the
domain, it queries only admitted inputs and replies along every possible transcript.
Together with its finite bound this gives an actual decision. -/
def DecisionCompatible (𝒟 : Domain (Σ i, X i) (Σ i, Y i)) (D : DDD I X Y) : Prop :=
∀ R : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟, R.RepliesAtQueriedInterface →
∀ h, FollowsStrategy (envOf (trim D)) h → R h ≠ 0 →
((trim D) (dHist (h.map Prod.snd))).Dom ∧
∀ x, x ∈ envOf (trim D) (h.map Prod.snd) → 𝒟 h x
variable {𝒟 : Domain (Σ i, X i) (Σ i, Y i)}
lemma DecisionCompatible.environment {D : DDD I X Y}
(hc : 𝒟.DecisionCompatible D) (hD : IsDDD D) : 𝒟.Compatible (ddeOf hD) :=
fun R hR h x ht hp hx => (hc R hR h ht hp).2 x hx
/-- Every completed possible transcript ends in a defined decision. -/
lemma DecisionCompatible.producesDecision {D : DDD I X Y}
(hc : 𝒟.DecisionCompatible D) (hD : IsDDD D) {R : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟}
(hR : R.RepliesAtQueriedInterface) {h}
(hh : h ∈ (R.sLaw (ddeOf hD).1 hD.2.1.choose).support) :
∃ b : Bool, ⟨.dec, b⟩ ∈ (trim D) (dHist (h.map Prod.snd)) := by
have hstop := R.sLaw_complete (ddeOf_bounded hD) hh
have hp : R h ≠ 0 := by
intro hz
exact Finsupp.mem_support_iff.mp hh (by simp [RandomSystem.sLaw_apply, hz])
have ht : FollowsStrategy (envOf (trim D)) h := by
by_contra hn
exact Finsupp.mem_support_iff.mp hh
(by simp [RandomSystem.sLaw_apply, Good, ddeOf, hn])
obtain ⟨o, ho⟩ := Part.dom_iff_mem.mp (hc R hR h ht hp).1
rcases o with ⟨_ | _ | i, v⟩
· exact v.elim
· exact ⟨v, ho⟩
· exact False.elim (hstop (Part.dom_iff_mem.mpr ⟨⟨i, v⟩, mem_envOf.mpr ho⟩))
/-- An environment followed by an event test is compatible with the domain of the
environment. -/
lemma envProbe_decisionCompatible {E : DDE (Σ i, X i) (Σ i, Y i)} (hc : 𝒟.Compatible E)
(T : List (Σ i, X i) × List (Σ i, Y i) → Prop) :
𝒟.DecisionCompatible (envProbe E T) := by
intro R hR h ht hp
have he := (RandomSystem.followsStrategy_trim_envProbe_iff hR E T hp).mp ht
have hv := he.fits (hR.history hp)
constructor
· rw [trim, ite_eq_left (envProbe_reach T hv), envProbe_dHist hv]
simp only [envReply]
split_ifs <;> exact Part.some_dom _
· intro x hx
rw [envOf_trim_envProbe hv] at hx
exact hc R hR h x he hp hx
end Domain
namespace RandomSystem
variable {𝒟 : Domain (Σ i, X i) (Σ i, Y i)}
/-- The transcript distance of two random systems on a domain: the largest statistical
distance of their completed-transcript laws under a query-bounded environment compatible
with the domain. -/
noncomputable def transcriptDistance (R S : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟) :
ENNReal :=
⨆ (E : DDE (Σ i, X i) (Σ i, Y i)) (n : ℕ) (_ : QueryBounded n E) (_ : 𝒟.Compatible E),
ENNReal.ofReal (statDist (R.sLaw E.1 n) (S.sLaw E.1 n))
lemma statDist_le_transcriptDistance {E : DDE (Σ i, X i) (Σ i, Y i)} {n : ℕ}
(hn : QueryBounded n E) (hc : 𝒟.Compatible E) (R S : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟) :
ENNReal.ofReal (statDist (R.sLaw E.1 n) (S.sLaw E.1 n)) ≤ R.transcriptDistance S :=
le_iSup_of_le E (le_iSup_of_le n (le_iSup_of_le hn (le_iSup_of_le hc le_rfl)))
/-- The supremum defining the transcript distance may use the domain bound for both the
observation horizon and the environments' global query bound: with `N = 𝒟.bound`,
`Δ(R, S) = ⨆ {E | QueryBounded N E, 𝒟.Compatible E}, d(R.sLaw E N, S.sLaw E N)`.
The systems must reply at the queried interface, as required by `Domain.Compatible`.
Lanzenberger–Maurer, Definition 11, printed p. 15: “the supremum is over all compatible
(Y, X)-DDE.” -/
lemma transcriptDistance_eq_iSup_domainBound
{R S : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟}
(hr : R.RepliesAtQueriedInterface) (hs : S.RepliesAtQueriedInterface) :
R.transcriptDistance S =
⨆ (E : DDE (Σ i, X i) (Σ i, Y i)) (_ : QueryBounded 𝒟.bound E)
(_ : 𝒟.Compatible E),
ENNReal.ofReal (statDist (R.sLaw E.1 𝒟.bound) (S.sLaw E.1 𝒟.bound)) := by
apply le_antisymm
-- `≤`: each term `(E, n)` equals the term of `E' = limitQueries E 𝒟.bound`.
· refine iSup_le fun E => iSup_le fun n => iSup_le fun hn => iSup_le fun hc => ?_
-- Move the horizon from `n` to `𝒟.bound`; compatibility uses the interface replies.
rw [sLaw_eq_domainBound R hn (hc R hr), sLaw_eq_domainBound S hn (hc S hs)]
-- Truncation keeps compatibility with every resource on the domain.
have hlim : 𝒟.Compatible (DDE.limitQueries E 𝒟.bound) :=
fun T hT => (hc T hT).limitQueries _
refine le_iSup_of_le (DDE.limitQueries E 𝒟.bound)
(le_iSup_of_le (DDE.limitQueries_queryBounded E 𝒟.bound) (le_iSup_of_le hlim ?_))
-- On the raw cutoff `limitQueries E.1`, truncation at the horizon keeps both laws.
change ENNReal.ofReal (statDist (R.sLaw E.1 𝒟.bound) (S.sLaw E.1 𝒟.bound)) ≤
ENNReal.ofReal (statDist (R.sLaw (limitQueries E.1 𝒟.bound) 𝒟.bound)
(S.sLaw (limitQueries E.1 𝒟.bound) 𝒟.bound))
rw [sLaw_limitQueries, sLaw_limitQueries]
-- `≥`: the right side is the restriction of the defining supremum to `n = 𝒟.bound`.
· exact iSup_le fun E => iSup_le fun hn => iSup_le fun hc =>
RandomSystem.statDist_le_transcriptDistance hn hc R S
/-- **A bound on the transcript laws bounds the transcript distance**: if under every compatible
query-bounded environment the statistical distance of the transcript laws is at most `b`, the
transcript distance is at most `b`. -/
lemma transcriptDistance_le {R S : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟} {b : ℝ≥0}
(h : ∀ (E : DDE (Σ i, X i) (Σ i, Y i)) (n : ℕ), QueryBounded n E → 𝒟.Compatible E →
statDist (R.sLaw E.1 n) (S.sLaw E.1 n) ≤ b) :
R.transcriptDistance S ≤ b :=
iSup_le fun E => iSup_le fun n => iSup_le fun hn => iSup_le fun hc => by
-- The real bound `b` read in `ℝ≥0∞` is `b` itself.
rw [← ENNReal.ofReal_coe_nnreal]
exact ENNReal.ofReal_le_ofReal (h E n hn hc)
lemma transcriptDistance_le_one {R S : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟}
(hR : R.RepliesAtQueriedInterface) (hS : S.RepliesAtQueriedInterface) :
R.transcriptDistance S ≤ 1 := by
rw [← ENNReal.coe_one]
refine transcriptDistance_le fun E n _ hc => ?_
have hr := R.sLaw_isProbDist (hc R hR) n
have hs := S.sLaw_isProbDist (hc S hS) n
exact (statDist_le_weight hr.1 hs.1).trans_eq hr.2
/-- The decision probability of a deterministic distinguisher on a random system: the
probability of the decision `1` in the completed transcript law. On a compatible
distinguisher the decision exists (`Domain.DecisionCompatible.producesDecision`). -/
noncomputable def decisionProbability (D : DDD I X Y) (hD : IsDDD D)
(R : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟) : ℝ :=
(R.sLaw (ddeOf hD).1 hD.2.1.choose).mass
fun h => ⟨.dec, true⟩ ∈ (trim D) (dHist (h.map Prod.snd))
/-- An environment followed by an event test decides `1` with exactly that event's
probability on its completed transcript. -/
lemma decisionProbability_envProbe {E : DDE (Σ i, X i) (Σ i, Y i)} {n : ℕ}
(hn : QueryBounded n E) (T : List (Σ i, X i) × List (Σ i, Y i) → Prop)
{R : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟} (hR : R.RepliesAtQueriedInterface) :
R.decisionProbability (envProbe E T) (envProbe_isDDD hn) =
(R.sLaw E.1 n).mass (fun h => T (h.map Prod.fst, h.map Prod.snd)) := by
let hD := envProbe_isDDD (A := T) hn
change (R.sLaw (envOf (trim (envProbe E T))) hD.2.1.choose).mass _ = _
rw [R.sLaw_trim_envProbe hR E T]
have hb : ∀ h, FollowsStrategy E.1 h → R h ≠ 0 → (E.1 (h.map Prod.snd)).Dom →
h.length < hD.2.1.choose := by
intro h ht hp hd
have hv := ht.fits (hR.history hp)
have hd' : ((ddeOf hD).1 (h.map Prod.snd)).Dom := by
change (envOf (trim (envProbe E T)) (h.map Prod.snd)).Dom
rwa [envOf_trim_envProbe hv]
simpa only [List.length_map] using ddeOf_bounded hD _ hd'
rw [R.sLaw_eq_of_query_bounds hb (fun h _ _ hd => by
simpa only [List.length_map] using hn _ hd)]
apply Distribution.mass_congr_of_support
intro h hh
have hp : R h ≠ 0 := by
intro hz
exact Finsupp.mem_support_iff.mp hh (by simp [sLaw_apply, hz])
have ht : FollowsStrategy E.1 h := by
by_contra hn'
exact Finsupp.mem_support_iff.mp hh (by simp [sLaw_apply, Good, hn'])
have hv := ht.fits (hR.history hp)
have hstop := R.sLaw_complete hn hh
rw [trim, ite_eq_left (envProbe_reach T hv), envProbe_dHist hv, envReply, dite_eq_right hstop]
simp only [Part.mem_some_iff, Sigma.mk.inj_iff, heq_eq_eq, true_and]
rw [← ht.queries_eq]
simp
/-- Decision gaps of a compatible distinguisher are at most the transcript distance. -/
lemma decisionProbability_gap_le {D : DDD I X Y} (hD : IsDDD D)
(hc : 𝒟.DecisionCompatible D) {R S : RandomSystem (Σ i, X i) (Σ i, Y i) 𝒟}
(hR : R.RepliesAtQueriedInterface) (hS : S.RepliesAtQueriedInterface) :
|R.decisionProbability D hD - S.decisionProbability D hD| ≤
(R.transcriptDistance S).toReal := by
apply (ENNReal.ofReal_le_iff_le_toReal
(ne_top_of_le_ne_top ENNReal.one_ne_top (transcriptDistance_le_one hR hS))).mp
refine le_trans (ENNReal.ofReal_le_ofReal ?_)
(statDist_le_transcriptDistance (ddeOf_bounded hD) (hc.environment hD) R S)
exact abs_mass_sub_le_statDist
⟨_, R.sLaw_isProbDist (hc.environment hD R hR) _⟩
⟨_, S.sLaw_isProbDist (hc.environment hD S hS) _⟩ _
variable {E : List (Σ i, X i) → Prop} {m : ℕ} {hE : ∀ h, E h → h.length ≤ m}
/-- On a presentation by deterministic resources, the decision probability is the
probability of deciding `1` on a sample. -/
lemma decisionProbability_of_presents (D : DDD I X Y) (hD : IsDDD D)
(P : Distribution.ProbDist {s : InterfaceSystem I X Y //
IsDDS s ∧ SystemAlgebra.RepliesAtQueriedInterface s ∧ ∀ h, (s h).Dom ↔ E h})
{R : RandomSystem (Σ i, X i) (Σ i, Y i) (Domain.ofInputs E m hE)}
(hP : ∀ h, behaviorMass P.1 (h.map Prod.fst) (h.map Prod.snd) = R h) :
R.decisionProbability D hD = P.1.mass (fun s => decOut true ∈ close D s.1 [startIn]) := by
have stop {ys} (hy : (⟨.dec, true⟩ : Σ p, dOut X p) ∈ (trim D) (dHist ys)) :
¬ (envOf (trim D) ys).Dom := by
rw [envOf, Part.eq_some_iff.mpr hy]
simp [query]
change (R.sLaw (envOf (trim D)) hD.2.1.choose).mass _ = _
calc
_ = (R.sLaw (envOf (trim D)) hD.2.1.choose).mass
(fun h => ¬ (envOf (trim D) (h.map Prod.snd)).Dom ∧
⟨.dec, true⟩ ∈ (trim D) (dHist (h.map Prod.snd))) :=
Distribution.mass_congr _ (fun h => ⟨fun hy => ⟨stop hy, hy⟩, And.right⟩)
_ = P.1.mass (fun s => ∃ h : List ((Σ i, X i) × (Σ i, Y i)),
Transcript s.1 (envOf (trim D)) (h.map Prod.fst) (h.map Prod.snd) ∧
h.length ≤ hD.2.1.choose ∧ ¬ (envOf (trim D) (h.map Prod.snd)).Dom ∧
⟨.dec, true⟩ ∈ (trim D) (dHist (h.map Prod.snd))) :=
sLaw_completed_eq_mass _ P.1 P.2.1 (fun s => s.1) (fun h => (hP h).symm) _ _ _
_ = _ := by
apply Distribution.mass_congr
intro s
rw [← close_trim_start D s.1, close_decision]
constructor
· rintro ⟨h, ht, _, _, hd⟩
exact ⟨_, _, ht, hd⟩
· rintro ⟨xs, ys, ht, hd⟩
have hf : (xs.zip ys).map Prod.fst = xs := List.map_fst_zip (by rw [ht.length_eq])
have hs : (xs.zip ys).map Prod.snd = ys := List.map_snd_zip (by rw [ht.length_eq])
refine ⟨xs.zip ys, ?_, ?_, ?_, ?_⟩
· simpa only [hf, hs] using ht
· have hn := finite_trim hD.2.1.choose_spec _ hd.1
simp only [dHist, List.length_cons, List.length_map] at hn
have hl : (xs.zip ys).length = ys.length := by
rw [List.length_zip, ht.length_eq, Nat.min_self]
omega
· simpa only [hs] using stop hd
· simpa only [hs] using hd
end RandomSystem
namespace Domain
variable {E : List (Σ i, X i) → Prop} {m : ℕ} {hE : ∀ h, E h → h.length ≤ m}
/-- Compatibility with a domain of input histories is checked on its deterministic
resources: the distinguisher decides on each of them. -/
lemma decisionCompatible_iff_deterministic
(hE' : ¬ E [] ∧ ∀ {p h}, p <+: h → p ≠ [] → E h → E p) {D : DDD I X Y} (hD : IsDDD D) :
(Domain.ofInputs E m hE : Domain (Σ i, X i) (Σ i, Y i)).DecisionCompatible D ↔
∀ s : InterfaceSystem I X Y, IsDDS s → SystemAlgebra.RepliesAtQueriedInterface s →
(∀ h, (s h).Dom ↔ E h) → (close D s [startIn]).Dom := by
classical
constructor
· intro hc s hs hr he
rw [← close_trim_start D s]
apply (close_dom_iff_compatible (finite_trim hD.2.1.choose_spec)).mpr
intro xs ys ht
let Q : Distribution.ProbDist {s : InterfaceSystem I X Y //
IsDDS s ∧ SystemAlgebra.RepliesAtQueriedInterface s ∧ ∀ h, (s h).Dom ↔ E h} :=
⟨Finsupp.single ⟨s, hs, hr, he⟩ 1, Distribution.isProbDist_single _⟩
let R : RandomSystem (Σ i, X i) (Σ i, Y i) (Domain.ofInputs E m hE) :=
RandomSystem.ofPDS Q.1 Q.2 (fun s _ _ _ _ => s.2.2.2 _)
have hfst : (xs.zip ys).map Prod.fst = xs := List.map_fst_zip (by rw [ht.length_eq])
have hsnd : (xs.zip ys).map Prod.snd = ys := List.map_snd_zip (by rw [ht.length_eq])
have hm : R (xs.zip ys) =
if Replies s ((xs.zip ys).map Prod.fst) ((xs.zip ys).map Prod.snd) then 1 else 0 := by
simp [R, Q, RandomSystem.ofPDS, behaviorMass, Distribution.mass, Finsupp.sum]
have hp : R (xs.zip ys) ≠ 0 := by
rw [hm, hfst, hsnd, ite_eq_left ht.replies]
exact one_ne_zero
have hh := hc R (RandomSystem.ofPDS_repliesAtQueriedInterface Q) (xs.zip ys)
(Transcript.followsStrategy ht) hp
simp only [Domain.ofInputs_apply, hfst, hsnd] at hh
exact ⟨hh.1, fun x hx => (he _).mpr (hh.2 x hx)⟩
· intro hc R hR h ht hp
obtain ⟨s, ⟨hs, hr, he⟩, hsrep⟩ := R.2.isSubprobabilistic.exists_replies (n := m)
(fun h hl => R.mass_eq_zero_of_bound_lt hl)
(fun s => IsDDS s ∧ SystemAlgebra.RepliesAtQueriedInterface s ∧ ∀ h, (s h).Dom ↔ E h)
(fun _ hg => RandomSystem.isResource_realization hE' hR hg) hp
have hd := hc s hs hr he
rw [← close_trim_start D s] at hd
have hcompat := (close_dom_iff_compatible (finite_trim hD.2.1.choose_spec)).mp hd
obtain ⟨hdec, hquery⟩ := hcompat _ _ (FollowsStrategy.transcript ht hsrep)
exact ⟨hdec, fun x hx => (he _).mp (hquery x hx)⟩
end Domain
end SystemAlgebra