القائمة
Lee Cronin's Assembly Theory for molecular complexity measurement and life detection via assembly index computation.
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Compressive Vasomotion Hypothesis (CVH) — vasomotion as a fast compression sweep that collapses ambivalent neural resonances (the Bayesian-blur problem) into a definite state. Use when modeling the ~100ms taṇhā 'grab', precision-weighting as compression forcefulness, or the generative collapse step of vasocomputational active inference.
Latched Hyperprior Hypothesis (LHH) — a sustained vascular contraction engages the smooth-muscle latch-bridge, durably freezing a circuit as a committed hyperprior isolated from global updating; unlatches when its prediction resolves. Use when modeling durable commitments, trauma/PTSD as cemented priors, latch spirals, or the cross-substrate latch (mechanical/bioelectric/immune/sheaf).
Synaptic substrate of biological active inference — long-term potentiation/depression (LTP/LTD) writes priors into synaptic weights = the learning landscape (Deep CANALs). A held vascular latch annealed long enough crystallizes into a neuron prior. Use when modeling consolidation, neuron priors, the inference→learning landscape write-path, or commit-to-disk of a held prediction.
| name | assembly-index |
| description | Lee Cronin's Assembly Theory for molecular complexity measurement and life detection via assembly index computation. |
| license | UNLICENSED |
| metadata | {"trit":1,"source":"local"} |
Status: ✅ Production Ready Trit: -1 (MINUS - validator/constraint) Color: #2626D8 (Blue) Principle: Complexity threshold → Life signature Frame: Assembly pathways with minimal step counting
Assembly Index measures molecular complexity by counting the minimum number of joining operations needed to construct a molecule from basic building blocks. Molecules with assembly index > 15 are biosignatures—too complex for random chemistry.
MA(molecule) = min |steps| to construct from primitives
Life threshold: MA > 15 with copy_number > 1
def assembly_index(molecule: Molecule) -> int:
"""Compute minimum assembly steps via dynamic programming."""
substructures = enumerate_substructures(molecule)
dag = build_assembly_dag(substructures)
return shortest_path_length(dag, source="primitives", target=molecule)
class AssemblyPathway:
def __init__(self, molecule):
self.mol = molecule
self.fragments = self.decompose()
def decompose(self) -> list[Fragment]:
"""Find all valid bond-breaking decompositions."""
return [split for split in self.mol.bonds
if split.yields_valid_fragments()]
def minimal_pathway(self) -> list[JoinOperation]:
"""DP over fragment DAG for minimum steps."""
memo = {}
return self._dp_assemble(self.mol, memo)
def is_biosignature(molecule, sample) -> bool:
ma = assembly_index(molecule)
copies = sample.count(molecule)
# Life creates copies of complex molecules
return ma > 15 and copies > 1
def ma_from_ms2(spectrum: MS2Spectrum) -> float:
"""Estimate assembly index from fragmentation pattern."""
fragments = spectrum.peaks
dag = reconstruct_assembly_dag(fragments)
return dag.longest_path()
# Compute assembly index
just assembly-index molecule.sdf
# Validate biosignature threshold
just assembly-validate sample.ms2
# Compare assembly pathways
just assembly-compare mol1.sdf mol2.sdf
assembly-index (-1) ⊗ turing-chemputer (0) ⊗ crn-topology (+1) = 0 ✓ [Molecular Complexity]
Skill Name: assembly-index Type: Complexity Validator Trit: -1 (MINUS) Color: #2626D8 (Blue)
Part of: alife-commons. Family: complexity-measurement. Canonical: assembly-index.