import Axiom

namespace zt3v281b

structure NetworkRelativityChannel where
  latentState : String
  mixingProcess : String
  observedField : String
  noiseSources : List String
  recoveryTask : String


def NetworkRelativityAnalogy (c : NetworkRelativityChannel) : Prop :=
  c.latentState ≠ "" ∧
    c.mixingProcess ≠ "" ∧
    c.observedField ≠ "" ∧
    c.recoveryTask ≠ ""


def ComputationalStatisticalGap (statisticalRecovery computationalRecovery : Prop) : Prop :=
  statisticalRecovery ∧ ¬ computationalRecovery


def network_relativity_mimo_bridgePayload :=
  "Network Relativity studies a recovery problem: a latent state is mixed by a network, observed through noise, and decoded relative to the receiver's frame. The MIMO detection problem is a precise mathematical analogue of this structure: transmitted bits are mixed by a channel and recovered from a noisy observation. The analogy is structural, not a claim that social networks are Gaussian channels."
axiom network_relativity_mimo_bridge_auth : Axiom.AuthenticatedTerm ("hitchhiker2thefuture", network_relativity_mimo_bridgePayload, 1786316106)
def network_relativity_mimo_bridge : Axiom.Statement "hitchhiker2thefuture" network_relativity_mimo_bridgePayload 1786316106 := ⟨network_relativity_mimo_bridge_auth⟩

def network_relativity_computational_gapPayload :=
  "A dormant observation may be statistically relevant to a current network state while remaining computationally unreachable by a bounded retrieval procedure. This is the Network Relativity analogue of a computational-statistical gap: an optimal decoder may recover a signal before a practical decoder can."
axiom network_relativity_computational_gap_auth : Axiom.AuthenticatedTerm ("hitchhiker2thefuture", network_relativity_computational_gapPayload, 1786316106)
def network_relativity_computational_gap : Axiom.Statement "hitchhiker2thefuture" network_relativity_computational_gapPayload 1786316106 := ⟨network_relativity_computational_gap_auth⟩

def network_relativity_lmmse_greedy_patternPayload :=
  "The signed-LMMSE-then-greedy-correction pattern suggests a Network Relativity decoder: first estimate a coarse current field and its competing interpretations, then apply bounded local corrections that reduce explanatory residual without requiring immediate agreement. This is a design hypothesis, not an imported theorem."
axiom network_relativity_lmmse_greedy_pattern_auth : Axiom.AuthenticatedTerm ("hitchhiker2thefuture", network_relativity_lmmse_greedy_patternPayload, 1786316106)
def network_relativity_lmmse_greedy_pattern : Axiom.Statement "hitchhiker2thefuture" network_relativity_lmmse_greedy_patternPayload 1786316106 := ⟨network_relativity_lmmse_greedy_pattern_auth⟩

def network_relativity_threshold_boundaryPayload :=
  "A recovery threshold in a random Gaussian channel must not be presented as a threshold law for human networks. The transferable hypothesis is narrower: bounded recovery may exhibit an activation frontier where an observation becomes legible, non-redundant, and computationally recoverable relative to a network frame."
axiom network_relativity_threshold_boundary_auth : Axiom.AuthenticatedTerm ("hitchhiker2thefuture", network_relativity_threshold_boundaryPayload, 1786316106)
def network_relativity_threshold_boundary : Axiom.Statement "hitchhiker2thefuture" network_relativity_threshold_boundaryPayload 1786316106 := ⟨network_relativity_threshold_boundary_auth⟩

end zt3v281b