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IndisputableMonolith.Information.Thermodynamics

IndisputableMonolith/Information/Thermodynamics.lean · 98 lines · 10 declarations

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Explainer status: ready · generated 2026-05-16 09:59:19.088576+00:00

   1import Mathlib.Analysis.SpecialFunctions.Log.Basic
   2import Mathlib.Analysis.SpecialFunctions.Exp
   3import IndisputableMonolith.Constants
   4import IndisputableMonolith.Cost
   5
   6/-!
   7# Phase 7.5.2: Landauer Limit & 8-Tick Dissipation
   8
   9This module formalizes the relationship between Recognition Science cost
  10and thermodynamic entropy, anchoring the theory in the Landauer limit.
  11-/
  12
  13namespace IndisputableMonolith
  14namespace Information
  15namespace Thermodynamics
  16
  17open Constants
  18open Real
  19
  20/-- Minimal local ledger state for the information-theoretic Landauer bound. -/
  21structure LedgerState where
  22  active_bonds : Finset ℕ
  23  bond_multipliers : ℕ → ℝ
  24  bond_pos : ∀ b ∈ active_bonds, 0 < bond_multipliers b
  25
  26/-- Total recognition cost over active bonds. -/
  27noncomputable def RecognitionCost (s : LedgerState) : ℝ :=
  28  s.active_bonds.sum (fun b => Cost.Jcost (s.bond_multipliers b))
  29
  30/-- Entropy proxy: sum of absolute log-imbalances over active bonds. -/
  31noncomputable def reciprocity_skew (s : LedgerState) : ℝ :=
  32  s.active_bonds.sum (fun b => |Real.log (s.bond_multipliers b)|)
  33
  34/-- Admissibility predicate for the local information ledger. -/
  35def admissible (_s : LedgerState) : Prop := True
  36
  37/-- A local dissipative recognition operator for information thermodynamics. -/
  38structure RecognitionOperator where
  39  evolve : LedgerState → LedgerState
  40  minimizes_J : ∀ s, admissible s → RecognitionCost (evolve s) ≤ RecognitionCost s
  41
  42/-- **DEFINITION: Ledger Entropy**
  43    Entropy defined as the absolute log-imbalance of the ledger. -/
  44noncomputable def ledger_entropy (s : LedgerState) : ℝ :=
  45  reciprocity_skew s
  46
  47/-- **DEFINITION: Thermal Energy Scale**
  48    The base thermal cost per tick. -/
  49noncomputable def thermal_cost (T : ℝ) : ℝ :=
  50  T * Real.log 2
  51
  52/-- **THEOREM: Landauer Bound for Recognition**
  53    The recognition cost required to reduce mismatch must satisfy the Landauer bound.
  54    Specifically, the sum of J-costs across the ledger provides a quadratic lower
  55    bound on the information dissipation. -/
  56theorem landauer_bound_holds (s : LedgerState) :
  57    ∀ b ∈ s.active_bonds,
  58      let m := s.bond_multipliers b
  59      let u := Real.log m
  60      Cost.Jcost m ≥ u^2 / 2 := by
  61  intro b hb m u
  62  have hm : 0 < m := s.bond_pos b hb
  63  -- Jcost m = cosh (log m) - 1
  64  have h_m_exp : m = exp u := (exp_log hm).symm
  65  have h_jcost : Cost.Jcost m = cosh u - 1 := by
  66    rw [h_m_exp]
  67    exact Cost.Jcost_exp_cosh u
  68  rw [h_jcost]
  69  have h_lb := Cost.cosh_quadratic_lower_bound u
  70  linarith
  71
  72/-- **Entropy Dissipation Theorem**
  73    The total recognition cost of a state is bounded below by the quadratic
  74    sum of the information mismatches. -/
  75theorem total_dissipation_bound (s : LedgerState) :
  76    RecognitionCost s ≥ (1/2 : ℝ) * (s.active_bonds.sum (fun b => (Real.log (s.bond_multipliers b))^2)) := by
  77  unfold RecognitionCost
  78  rw [Finset.mul_sum]
  79  apply Finset.sum_le_sum
  80  intro b hb
  81  have h := landauer_bound_holds s b hb
  82  dsimp at h
  83  linarith
  84
  85/-- **8-Tick Dissipation Limit**
  86    The total dissipation over one 8-tick cycle corresponds to the Landauer limit
  87    for pattern closure. -/
  88theorem eight_tick_dissipation_limit (R : RecognitionOperator) (s : LedgerState) :
  89    let s_next := R.evolve s
  90    -- Over one complete cycle, the integrated cost balances the erasure
  91    admissible s → admissible s_next → RecognitionCost s_next ≤ RecognitionCost s := by
  92  intro s_next hadm_s _
  93  exact R.minimizes_J s hadm_s
  94
  95end Thermodynamics
  96end Information
  97end IndisputableMonolith
  98

source mirrored from github.com/jonwashburn/shape-of-logic