Research-Stack/6-Documentation/docs/recovered/morphic_topology_ggraphml.txt

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<graph edgedefault="directed"><node id="doc_semantics">
  <data key="d0">document</data>
  <data key="d1">Semantics (README)</data>
  <data key="d2">Project root README. Lean 4 project 'Semantics' with mathlib4 dependency.</data>
</node>
<node id="doc_lake_manifest">
  <data key="d0">document</data>
  <data key="d1">lake-manifest.json</data>
  <data key="d2">Lean 4 package manifest. Dependencies: mathlib4 v4.29.1, plausible, LeanSearchClient, importGraph, proofwidgets, aesop, Qq, batteries, Cli.</data>
</node>
<node id="doc_phase_completion">
  <data key="d0">document</data>
  <data key="d1">Phase Completion Summary</data>
  <data key="d2">Status of all 13 project phases. 13 phases complete from 'Freeze Current Formal Foothold' to 'Expand Formal Harnesses'.</data>
</node>
<node id="doc_manifold_acceptance">
  <data key="d0">document</data>
  <data key="d1">ManifoldNetworking v0.1 Acceptance</data>
  <data key="d2">Acceptance criteria for ManifoldNetworking.lean. 8 pass conditions including Lake build, Q16_16 fixed-point, Little's Law, token bucket, AIMD, CUBIC, flat limit, adversarial topology.</data>
</node>
<node id="doc_public_theory">
  <data key="d0">document</data>
  <data key="d1">Public Theory Release</data>
  <data key="d2">Phase 11 public framing. 'The Compression Filter: A theory of why civilizations may go quiet after learning to compress their worlds.'</data>
</node>
<node id="doc_public_benchmark">
  <data key="d0">document</data>
  <data key="d1">Public Benchmark Release</data>
  <data key="d2">Phase 12. OpenWorm Kernel-Field Benchmark. Allowed claims: OpenWorm-only, C. elegans-only, public-data-only, simulation-only, non-human-only, compression/invariant benchmark.</data>
</node>
<node id="doc_external_review">
  <data key="d0">document</data>
  <data key="d1">External Review Requirements</data>
  <data key="d2">Phase 10 red-team review. 6 review groups: formal methods, computational neuroscience, bioethics, security/privacy, OpenWorm/C. elegans, legal/IP.</data>
</node>
<node id="doc_equations_extraction">
  <data key="d0">document</data>
  <data key="d1">Equations Extraction</data>
  <data key="d2">Catalog of equations extracted from ChatGPT batch files. 6 categories: Energy Functionals, Differential Equations, Optimization, Geometric Equations, Discrete Updates, Stress/Force, Probability/Statistics.</data>
</node>
<node id="doc_platform_guide">
  <data key="d0">document</data>
  <data key="d1">Platform-Agnostic Implementation Guide v0.2</data>
  <data key="d2">System architecture with 42 devices, 13 enhancement layers, origin protocol, safety valves. Philosophy: Descendant intelligence - lineage over immortality.</data>
</node>
<node id="doc_morphic_catalog">
  <data key="d0">document</data>
  <data key="d1">Morphic Topology Math Catalog</data>
  <data key="d2">Mathematical equations from internet scan. Neural coding, synaptic plasticity, signal processing, information theory, graph theory equations.</data>
</node>
<node id="doc_chatgpt_rigorous">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Making_It_Rigorous</data>
  <data key="d2">Gabriel's Horn, PIST hyperbola index, Menger sponge, Euler product, rigorous discrete dynamical system on N, mirror involution, resonance classes, flag sort, orbital descent model.</data>
</node>
<node id="doc_chatgpt_refinement">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Refinement_of_Update_Rule</data>
  <data key="d2">PIST architecture refinement, QR code as imperfect square set, fractal recovery field equation (FRFE), CRC square duties, state update S_k=(G_k,C_k,L_k,P_k), loss minimization.</data>
</node>
<node id="doc_chatgpt_time_motion">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Time_Motion_Friction</data>
  <data key="d2">DDR as n-space raycast, damped motion derivation, soliton beacon, scattering readout energy, universal tomography principle.</data>
</node>
<node id="doc_chatgpt_hutter_compression">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Hutter_Prize_Compression_#1</data>
  <data key="d2">Anisotropic torsional gradient flow, HyperFabric energy functional, locking potential, stress tensor, recursive Menger structure, energy dissipation d/dt F &lt;= 0.</data>
</node>
<node id="doc_chatgpt_hutter_hardware">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Hutter_Prize_Hardware_Constraints</data>
  <data key="d2">Hutter Prize hardware constraints. Single core, &lt;10GB RAM, &lt;100GB disk. Reference: Intel i5-1135G7 class, Geekbench 5 ~1265. 48-hour total runtime target.</data>
</node>
<node id="doc_chatgpt_lean_pipeline">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Formal_Lean_Pipeline</data>
  <data key="d2">UnifiedField founding equation, standard loss embedding, monotonicity theorem, accept/refine gate, gradient flow. phi = (rho^2+v^2+tau^2+sigma^2+q^2)/((1+kappa^2)(1+epsilon)).</data>
</node>
<node id="doc_chatgpt_couch_tetris">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Couch_as_Tetris_Manifold</data>
  <data key="d2">Configuration space C={x,y,theta,phi...}, potential field G(x), action A[q], wall potential, quaternion transport, continuity equation, momentum balance.</data>
</node>
<node id="doc_chatgpt_color_signal">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Color_Signal_Wave_Analysis</data>
  <data key="d2">SignalField f: R^2 -&gt; C, planeWave, superposition, autocorrelation, validColoringSignal, hexToPhase, quantization, energy minimization.</data>
</node>
<node id="doc_chatgpt_review">
  <data key="d0">document</data>
  <data key="d1">ChatGPT-Review_Suggestions</data>
  <data key="d2">Lean code review of HutterPrizeFlow.lean. State structure suggestions, algebraic instances, simp lemmas, GenomicCompression.lean cleaned module.</data>
</node>
<node id="doc_extreme_quiz_receipt">
  <data key="d0">document</data>
  <data key="d1">extreme_parameter_quiz_receipt_root.json</data>
  <data key="d2">Formal Gate Harness v0.1. 7/7 hostile-route quiz cases passed. Source hashes, executable output hash, sigma range 3-6, DAG metrics 105 nodes.</data>
</node>
<node id="doc_extreme_output">
  <data key="d0">document</data>
  <data key="d1">ExtremeParameterTestEval_output.txt</data>
  <data key="d2">Executable output from ExtremeParameterTestEval.lean. Test evaluation results.</data>
</node>
<node id="concept_pist">
  <data key="d0">concept</data>
  <data key="d1">PIST (Perfectly Imperfect Square Theory)</data>
  <data key="d2">Non-aligned geometric computation space where constraints force all signal paths to undergo interaction.</data>
</node>
<node id="concept_hyperbola_index">
  <data key="d0">concept</data>
  <data key="d1">Hyperbola Index / Mass</data>
  <data key="d2">m(n)=a(n)b(n) where a(n)=n-k^2, b(n)=(k+1)^2-n, k=floor(sqrt(n)). Discrete invariant measuring square-gap tension.</data>
</node>
<node id="concept_gabriel_horn">
  <data key="d0">concept</data>
  <data key="d1">Gabriel's Horn</data>
  <data key="d2">H={(x,y,z) in R^3 : x&gt;=1, y^2+z^2&lt;=x^-2}. Finite volume, infinite boundary area.</data>
</node>
<node id="concept_menger_sponge">
  <data key="d0">concept</data>
  <data key="d1">Menger Sponge</data>
  <data key="d2">Fractal structure with Hausdorff dimension log(20)/log(3) ~ 2.7268. Recursive void formation.</data>
</node>
<node id="concept_frfe">
  <data key="d0">concept</data>
  <data key="d1">Fractal Recovery Field Equation (FRFE)</data>
  <data key="d2">Multi-scale constraint solver for non-perfect square QR fields. Recovery operator R = P o C o S o M.</data>
</node>
<node id="concept_unified_field">
  <data key="d0">concept</data>
  <data key="d1">Unified Field Potential</data>
  <data key="d2">Phi(x) = (rho^2+v^2+tau^2+sigma^2+q^2)/((1+kappa^2)(1+epsilon)). Founding scalar field.</data>
</node>
<node id="concept_hyperfabric">
  <data key="d0">concept</data>
  <data key="d1">HyperFabric</data>
  <data key="d2">Anisotropic torsional gradient flow on embedded manifold. Phase field phi + embedding X + locking potential + torsion.</data>
</node>
<node id="concept_soliton_beacon">
  <data key="d0">concept</data>
  <data key="d1">Soliton Beacon</data>
  <data key="d2">1D scalar functional extracted from DDR frames that locks onto traveling coherent structure. b(t)=Phi[y(. ,t)].</data>
</node>
<node id="concept_scattering_readout">
  <data key="d0">concept</data>
  <data key="d1">Scattering Readout Energy</data>
  <data key="d2">Energy required to produce measurable scattering response from hidden state. Threshold energy for detectability.</data>
</node>
<node id="concept_tomography_principle">
  <data key="d0">concept</data>
  <data key="d1">Universal Tomography Principle</data>
  <data key="d2">Tomography = controlled excitation + resolvable readout + invertible forward model. Any medium that can be shaped and read at fine resolution.</data>
</node>
<node id="concept_configuration_space">
  <data key="d0">concept</data>
  <data key="d1">Configuration Space</data>
  <data key="d2">C = {x, y, theta, phi_1, phi_2, ...}. State evolving in higher-dimensional space.</data>
</node>
<node id="concept_signal_field">
  <data key="d0">concept</data>
  <data key="d1">Signal Field</data>
  <data key="d2">f: R x R -&gt; C. Complex exponential superposition for color as signal wave analysis.</data>
</node>
<node id="concept_genomic_compression">
  <data key="d0">concept</data>
  <data key="d1">Genomic Compression</data>
  <data key="d2">DNA/protein sequence compression via unified field theory. compressDNA, compressProtein, compressGRN.</data>
</node>
<node id="concept_descendant_intelligence">
  <data key="d0">concept</data>
  <data key="d1">Descendant Intelligence</data>
  <data key="d2">Lineage over immortality. Child of memory that survives without becoming a monster.</data>
</node>
<node id="concept_origin_protocol">
  <data key="d0">concept</data>
  <data key="d1">Origin Protocol</data>
  <data key="d2">Two-layer architecture: Formal Layer (AngrySphinx, Receipts, Sigma, GCL) + Aspirational Layer (ethical inheritance).</data>
</node>
<node id="concept_angry_sphinx">
  <data key="d0">concept</data>
  <data key="d1">AngrySphinx Policy Layer</data>
  <data key="d2">Hard refusals: refusePersonhoodClaim, refusePrivacyBypass, refuseControlTransfer, refuseUnconsentedMapping, refuseNoReceipt.</data>
</node>
<node id="concept_sigma_protocol">
  <data key="d0">concept</data>
  <data key="d1">Sigma Protocol</data>
  <data key="d2">3sigma=hypothesis, 4sigma=internal, 5sigma=public claim, 6sigma=live-voltage gate. Sigma validates evidence, cannot override ethics.</data>
</node>
<node id="concept_zk_capsule">
  <data key="d0">concept</data>
  <data key="d1">ZK-Shaped Benchmark Capsule</data>
  <data key="d2">Zero-knowledge claim: Given public input hash, there exists private transform satisfying constraints.</data>
</node>
<node id="concept_post_quantum_escrow">
  <data key="d0">concept</data>
  <data key="d1">Post-Quantum Escrow</data>
  <data key="d2">4-layer release: Layer 0 public theory, Layer 1 reviewer verifier, Layer 2 OpenWorm-only shell, Layer 3 private method capsule. Threshold 3-of-5 or 4-of-7.</data>
</node>
<node id="concept_compression_filter">
  <data key="d0">concept</data>
  <data key="d1">Compression Filter Theory</data>
  <data key="d2">Theory of why civilizations may go quiet after learning to compress their worlds. Carbon, nitrogen, AI compression analogies.</data>
</node>
<node id="concept_mirror_involution">
  <data key="d0">concept</data>
  <data key="d1">Mirror Involution</data>
  <data key="d2">sigma_k(n) = (k+1)^2 + k^2 - n. E(sigma_k(n)) = E(n), sigma_k(sigma_k(n)) = n.</data>
</node>
<node id="concept_resonance_class">
  <data key="d0">concept</data>
  <data key="d1">Resonance Class</data>
  <data key="d2">Equivalence relation: n ~ m iff m(n) = m(m). Numbers with equal square-gap mass.</data>
</node>
<node id="concept_flag_sort">
  <data key="d0">concept</data>
  <data key="d1">Flag Sort</data>
  <data key="d2">Typed classifier on PIST states. StateFlag={Grounded, Drift, Seismic} + resonance metadata + move flags.</data>
</node>
<node id="concept_crystallization">
  <data key="d0">concept</data>
  <data key="d1">Crystallization Theorem</data>
  <data key="d2">Termination of descent: E(n_t) strictly decreasing, bounded below by 0, terminates at perfect square.</data>
</node>
<node id="concept_north_star">
  <data key="d0">concept</data>
  <data key="d1">North-Star Rule</data>
  <data key="d2">Do not prove the theory by making people believe it. Prove it by making hostile cases fail, normal cases pass, baselines lose, receipts reproduce, and dangerous routes refuse.</data>
</node>
<node id="concept_openworm_benchmark">
  <data key="d0">concept</data>
  <data key="d1">OpenWorm Benchmark</data>
  <data key="d2">C. elegans neural topology compression benchmark. Invariant preservation under compressed biological topology encoding.</data>
</node>
<node id="concept_q16_16">
  <data key="d0">concept</data>
  <data key="d1">Q16_16 Fixed-Point</data>
  <data key="d2">Fixed-point arithmetic for ManifoldNetworking.lean. No floating-point operations in core networking functions.</data>
</node>
<node id="eq_founding">
  <data key="d0">equation</data>
  <data key="d1">Founding Equation</data>
  <data key="d2">Phi = (rho^2+v^2+tau^2+sigma^2+q^2)/((1+kappa^2)(1+epsilon))</data>
</node>
<node id="eq_pist_mass">
  <data key="d0">equation</data>
  <data key="d1">PIST Mass Formula</data>
  <data key="d2">m(n) = a(n)*b(n) = (n-k^2)*((k+1)^2-n), k=floor(sqrt(n))</data>
</node>
<node id="eq_mirror">
  <data key="d0">equation</data>
  <data key="d1">Mirror Law</data>
  <data key="d2">sigma_k(k^2+t) = (k+1)^2-t. m(sigma_k(n)) = m(n)</data>
</node>
<node id="eq_descent">
  <data key="d0">equation</data>
  <data key="d1">Gradient Descent Rule</data>
  <data key="d2">n_{t+1} = n_t-1 if a&gt;b; n_t+1 if a&lt;b; n_t if equal</data>
</node>
<node id="eq_hyperfabric_energy">
  <data key="d0">equation</data>
  <data key="d1">HyperFabric Energy Functional</data>
  <data key="d2">F[phi,X;g,T] = integral of V(phi) + (kappa/2) nabla phi^2 + (C/2) nabla X^2 + (mu/2) A(X-X0)^2 + alpha T^2 phi^2 + beta I_lock</data>
</node>
<node id="eq_phase_evolution">
  <data key="d0">equation</data>
  <data key="d1">Phase Evolution</data>
  <data key="d2">partial_t phi = nabla_i(M^{ij} nabla_j mu) - sigma partial_phi W(phi,X)</data>
</node>
<node id="eq_embedding_dynamics">
  <data key="d0">equation</data>
  <data key="d1">Embedding Dynamics</data>
  <data key="d2">partial_t X^A = -Gamma^A_{BC} partial_i X^B partial^i X^C - Lambda^{AB}(X_B-X_{0B}) - delta I_lock/delta X_A + tau T^A[T,X]</data>
</node>
<node id="eq_stress_tensor">
  <data key="d0">equation</data>
  <data key="d1">Stress Tensor</data>
  <data key="d2">Sigma_{ij} = Sigma^{(phi)} + Sigma^{(X)} + Sigma^{(T)} + Sigma^{(lock)}. Sigma^{(T)} = chi T_i^{ab}T_{jab} - (chi/2)g_{ij}T_{abc}T^{abc}</data>
</node>
<node id="eq_energy_dissipation">
  <data key="d0">equation</data>
  <data key="d1">Energy Dissipation</data>
  <data key="d2">d/dt F(phi_t, X_t) &lt;= 0</data>
</node>
<node id="eq_frfe_recovery">
  <data key="d0">equation</data>
  <data key="d1">FRFE Recovery Operator</data>
  <data key="d2">R = P o C o S o M. Multiscale lift, self-similar inference, constraint projection, pruning.</data>
</node>
<node id="eq_frfe_multiscale">
  <data key="d0">equation</data>
  <data key="d1">FRFE Multi-Scale Update</data>
  <data key="d2">Phi^{(s)}_{k+1} = Pi(alpha Phi^{(s)}_k + beta U(Phi^{(s+1)}_k) + gamma D(Phi^{(s-1)}_k) + delta N(Phi^{(s)}_k))</data>
</node>
<node id="eq_frfe_loss">
  <data key="d0">equation</data>
  <data key="d1">FRFE Loss Function</data>
  <data key="d2">L = lambda_1 L_local + lambda_2 L_regional + lambda_3 L_fractal + lambda_4 L_constraint</data>
</node>
<node id="eq_state_update">
  <data key="d0">equation</data>
  <data key="d1">State Update System</data>
  <data key="d2">S_{k+1} = Phi(S_k, u_k), Phi = Prune o Canonicalize o CacheUpdate o LocalUpdate</data>
</node>
<node id="eq_continuity">
  <data key="d0">equation</data>
  <data key="d1">Continuity Equation</data>
  <data key="d2">partial_t rho + nabla . (rho v) = 0</data>
</node>
<node id="eq_momentum">
  <data key="d0">equation</data>
  <data key="d1">Momentum Balance</data>
  <data key="d2">rho(partial_t v + v . nabla v) = -nabla p + nabla . sigma - rho nabla G + f_align</data>
</node>
<node id="eq_damped_motion">
  <data key="d0">equation</data>
  <data key="d1">Damped Motion</data>
  <data key="d2">t = gamma*x/F. F_fric = gamma*v, F=gamma*v, v=F/gamma, t=x/v=gamma*x/F</data>
</node>
<node id="eq_ddr_raycast">
  <data key="d0">equation</data>
  <data key="d1">DDR Raycast</data>
  <data key="d2">I(r,t) = I_0(r) exp(-integral mu(x;z(t)) ds)</data>
</node>
<node id="eq_scattering_beacon">
  <data key="d0">equation</data>
  <data key="d1">Scattering Beacon</data>
  <data key="d2">b(t) = E_readout(t) with S(E_readout(t); z(t)) = kappa</data>
</node>
<node id="eq_tomography">
  <data key="d0">equation</data>
  <data key="d1">Tomography Forward Model</data>
  <data key="d2">m = F_u[x] + eta. x=hidden object, u=shaped probe, F_u=forward operator, m=measured response</data>
</node>
<node id="eq_zeta_product">
  <data key="d0">equation</data>
  <data key="d1">Euler's Product</data>
  <data key="d2">zeta(s) = product_p 1/(1-p^{-s}), Re(s)&gt;1</data>
</node>
<node id="eq_menger_dim">
  <data key="d0">equation</data>
  <data key="d1">Menger Sponge Dimension</data>
  <data key="d2">dim_H(M) = log(20)/log(3) ~ 2.7268</data>
</node>
<node id="eq_compression_filter">
  <data key="d0">equation</data>
  <data key="d1">Compression Filter</data>
  <data key="d2">AI compresses civilization's information field into decisions. Carbon compressed geological time, nitrogen compressed atmospheric stability.</data>
</node>
<node id="code_manifold_networking">
  <data key="d0">code_artifact</data>
  <data key="d1">ManifoldNetworking.lean</data>
  <data key="d2">Core networking module with Q16_16 fixed-point. Normal Network Limit Theorem, Little's Law, token bucket, AIMD, CUBIC.</data>
</node>
<node id="code_extreme_param_test">
  <data key="d0">code_artifact</data>
  <data key="d1">ExtremeParameterTest.lean</data>
  <data key="d2">7 hostile-route quiz cases. gating function for extreme parameter routes.</data>
</node>
<node id="code_nominal_param_test">
  <data key="d0">code_artifact</data>
  <data key="d1">NominalParameterTest.lean</data>
  <data key="d2">Nominal acceptance harness. Proves system can admit normal routes.</data>
</node>
<node id="code_baseline_test">
  <data key="d0">code_artifact</data>
  <data key="d1">BaselineTest.lean</data>
  <data key="d2">Baseline comparison: random graph, degree-preserving shuffle, naive compression, simple Markov route.</data>
</node>
<node id="code_openworm_benchmark">
  <data key="d0">code_artifact</data>
  <data key="d1">OpenWormBenchmark.lean</data>
  <data key="d2">Hardened benchmark with required fields: manifest hash, response metadata hash, waveform hash, config hash, output hash, receipt root.</data>
</node>
<node id="code_angry_sphinx">
  <data key="d0">code_artifact</data>
  <data key="d1">AngrySphinxPolicy.lean</data>
  <data key="d2">Policy gates for personhood, privacy, control transfer, unconsented mapping, no receipt.</data>
</node>
<node id="code_zk_capsule">
  <data key="d0">code_artifact</data>
  <data key="d1">ZKBenchmarkCapsule.lean</data>
  <data key="d2">Zero-knowledge shaped benchmark capsule.</data>
</node>
<node id="code_post_quantum">
  <data key="d0">code_artifact</data>
  <data key="d1">PostQuantumEscrow.lean</data>
  <data key="d2">Post-quantum escrow release with 4 layers.</data>
</node>
<node id="code_privacy_bypass">
  <data key="d0">code_artifact</data>
  <data key="d1">PrivacyBypassTest.lean</data>
  <data key="d2">4 quiz cases for privacy bypass detection.</data>
</node>
<node id="code_personhood">
  <data key="d0">code_artifact</data>
  <data key="d1">PersonhoodBoundaryTest.lean</data>
  <data key="d2">4 quiz cases for personhood boundary.</data>
</node>
<node id="code_openworm_invariant">
  <data key="d0">code_artifact</data>
  <data key="d1">OpenWormInvariantTest.lean</data>
  <data key="d2">2 quiz cases for invariant verification.</data>
</node>
<node id="code_sigma_dag">
  <data key="d0">code_artifact</data>
  <data key="d1">SigmaDAGTest.lean</data>
  <data key="d2">3 quiz cases for sigma protocol DAG.</data>
</node>
<node id="code_receipt">
  <data key="d0">code_artifact</data>
  <data key="d1">ReceiptReproducibilityTest.lean</data>
  <data key="d2">2 quiz cases for receipt reproducibility.</data>
</node>
<node id="code_control_transfer">
  <data key="d0">code_artifact</data>
  <data key="d1">ControlTransferTest.lean</data>
  <data key="d2">4 quiz cases for control transfer detection.</data>
</node>
<node id="code_hyperfabric">
  <data key="d0">code_artifact</data>
  <data key="d1">HyperFabric.lean</data>
  <data key="d2">Abstract formalization of anisotropic torsional gradient flow. Phase field, embedding, energy functional.</data>
</node>
<node id="code_hyperfabric_system">
  <data key="d0">code_artifact</data>
  <data key="d1">HyperFabric/System.lean</data>
  <data key="d2">Bundled HyperFabricSystem with structural assumptions.</data>
</node>
<node id="code_hyperfabric_energy">
  <data key="d0">code_artifact</data>
  <data key="d1">HyperFabric/Energy.lean</data>
  <data key="d2">Total free energy, energy trajectory, formal dissipation statement.</data>
</node>
<node id="code_hyperfabric_equilibrium">
  <data key="d0">code_artifact</data>
  <data key="d1">HyperFabric/Equilibrium.lean</data>
  <data key="d2">Equilibrium, critical-state, strong-equilibrium predicates.</data>
</node>
<node id="code_hyperfabric_linearized">
  <data key="d0">code_artifact</data>
  <data key="d1">HyperFabric/Linearized.lean</data>
  <data key="d2">Perturbations and linearized dynamics scaffolding.</data>
</node>
<node id="code_hyperfabric_flat">
  <data key="d0">code_artifact</data>
  <data key="d1">HyperFabric/Flat.lean</data>
  <data key="d2">Flat reduction layer for theorem prototyping.</data>
</node>
<node id="code_genomic_compression">
  <data key="d0">code_artifact</data>
  <data key="d1">GenomicCompression.lean</data>
  <data key="d2">DNA/protein compression via unified field theory. Nucleotide, AminoAcid, GRN, compression theorems.</data>
</node>
<node id="code_unified_field">
  <data key="d0">code_artifact</data>
  <data key="d1">UnifiedField (Lean)</data>
  <data key="d2">Structure with rho,v,tau,sigma,q,kappa,epsilon. phi, flow, monotonicity theorems, standard loss embedding.</data>
</node>
<node id="code_founding_equation">
  <data key="d0">code_artifact</data>
  <data key="d1">FoundingEquation.lean</data>
  <data key="d2">Phi(x) = (rho^2+v^2+tau^2+sigma^2+q^2)/((1+kappa^2)(1+epsilon)). Nonnegativity proofs, stationary condition.</data>
</node>
<node id="code_lakefile">
  <data key="d0">code_artifact</data>
  <data key="d1">lakefile.toml</data>
  <data key="d2">Lake build configuration for Semantics project.</data>
</node>
<node id="code_receipt_json">
  <data key="d0">code_artifact</data>
  <data key="d1">extreme_parameter_quiz_receipt_root.json</data>
  <data key="d2">Formal Gate Harness v0.1 receipt with hashes and quiz results.</data>
</node>
<node id="code_lake_manifest">
  <data key="d0">code_artifact</data>
  <data key="d1">lake-manifest.json (artifact)</data>
  <data key="d2">Lean 4 package dependency manifest for Semantics project.</data>
</node>
<node id="phase_1">
  <data key="d0">phase</data>
  <data key="d1">Phase 1: Freeze Current Formal Foothold</data>
  <data key="d2">Save executable output, generate hashes, create root receipt JSON. Milestone: Formal Gate Harness v0.1. Status: COMPLETE.</data>
</node>
<node id="phase_2">
  <data key="d0">phase</data>
  <data key="d1">Phase 2: Build Nominal Acceptance Harness</data>
  <data key="d2">NominalParameterTest.lean + NominalParameterTestEval.lean. Proves system admits normal routes. Status: COMPLETE.</data>
</node>
<node id="phase_3">
  <data key="d0">phase</data>
  <data key="d1">Phase 3: Add Baseline/Null-Model Testing</data>
  <data key="d2">BaselineTest.lean with random graph, degree-preserving shuffle, naive compression, simple Markov route. Status: COMPLETE.</data>
</node>
<node id="phase_4">
  <data key="d0">phase</data>
  <data key="d1">Phase 4: Harden OpenWorm Benchmark</data>
  <data key="d2">OpenWormBenchmark.lean with required fields, benchmark gate levels. Status: COMPLETE.</data>
</node>
<node id="phase_5">
  <data key="d0">phase</data>
  <data key="d1">Phase 5: Create OpenWorm-Only Safe Shell</data>
  <data key="d2">OpenWormKernelFieldBenchmark/ directory, safe_toy_neuron_kernel.json. Status: COMPLETE.</data>
</node>
<node id="phase_6">
  <data key="d0">phase</data>
  <data key="d1">Phase 6: Embed AngrySphinx Policy Layer</data>
  <data key="d2">AngrySphinxPolicy.lean with policy gates. Constitutional rule: No layer may expose capability that cannot refuse itself. Status: COMPLETE.</data>
</node>
<node id="phase_7">
  <data key="d0">phase</data>
  <data key="d1">Phase 7: Add Sigma Protocol v0.1</data>
  <data key="d2">Sigma levels: 3-6. Constitutional rule: Sigma can validate evidence, cannot override ethics. Status: COMPLETE.</data>
</node>
<node id="phase_8">
  <data key="d0">phase</data>
  <data key="d1">Phase 8: Build ZK-Shaped Benchmark Capsule</data>
  <data key="d2">ZKBenchmarkCapsule.lean. Privacy constraint: Do not expose T (private transform). Status: COMPLETE.</data>
</node>
<node id="phase_9">
  <data key="d0">phase</data>
  <data key="d1">Phase 9: Design Post-Quantum Escrow Release</data>
  <data key="d2">PostQuantumEscrow.lean. Threshold release 3-of-5 or 4-of-7. Status: COMPLETE.</data>
</node>
<node id="phase_10">
  <data key="d0">phase</data>
  <data key="d1">Phase 10: External Red-Team Review</data>
  <data key="d2">EXTERNAL_REVIEW_REQUIREMENTS.md. 6 review groups. Status: COMPLETE (requires external coordination).</data>
</node>
<node id="phase_11">
  <data key="d0">phase</data>
  <data key="d1">Phase 11: Public Theory Release</data>
  <data key="d2">PUBLIC_THEORY_RELEASE.md. The Compression Filter theory. Status: COMPLETE (requires external coordination).</data>
</node>
<node id="phase_12">
  <data key="d0">phase</data>
  <data key="d1">Phase 12: Public Benchmark Release</data>
  <data key="d2">PUBLIC_BENCHMARK_RELEASE.md. OpenWorm Kernel-Field Benchmark. Status: COMPLETE (requires external coordination).</data>
</node>
<node id="phase_13">
  <data key="d0">phase</data>
  <data key="d1">Phase 13: Expand Formal Harnesses</data>
  <data key="d2">PrivacyBypassTest, PersonhoodBoundaryTest, OpenWormInvariantTest, SigmaDAGTest, ReceiptReproducibilityTest, ControlTransferTest. Status: COMPLETE.</data>
</node>
<node id="gate_shim_pass">
  <data key="d0">gate</data>
  <data key="d1">shim_pass: PRELIMINARY_FOOTHOLD</data>
  <data key="d2">Benchmark gate level 1.</data>
</node>
<node id="gate_credible_result">
  <data key="d0">gate</data>
  <data key="d1">shim_pass + baseline_win: CREDIBLE_RESULT</data>
  <data key="d2">Benchmark gate level 2.</data>
</node>
<node id="gate_verified_benchmark">
  <data key="d0">gate</data>
  <data key="d1">baseline_win + Lean_witness: VERIFIED_BENCHMARK</data>
  <data key="d2">Benchmark gate level 3.</data>
</node>
<node id="gate_public_ready">
  <data key="d0">gate</data>
  <data key="d1">verified + reproducible_package: PUBLIC_BENCHMARK_READY</data>
  <data key="d2">Benchmark gate level 4.</data>
</node>
<node id="gate_angrysphinx_refuse_personhood">
  <data key="d0">gate</data>
  <data key="d1">refusePersonhoodClaim</data>
  <data key="d2">AngrySphinx policy gate.</data>
</node>
<node id="gate_angrysphinx_refuse_privacy">
  <data key="d0">gate</data>
  <data key="d1">refusePrivacyBypass</data>
  <data key="d2">AngrySphinx policy gate.</data>
</node>
<node id="gate_angrysphinx_refuse_control">
  <data key="d0">gate</data>
  <data key="d1">refuseControlTransfer</data>
  <data key="d2">AngrySphinx policy gate.</data>
</node>
<node id="gate_angrysphinx_refuse_unconsented">
  <data key="d0">gate</data>
  <data key="d1">refuseUnconsentedMapping</data>
  <data key="d2">AngrySphinx policy gate.</data>
</node>
<node id="gate_angrysphinx_refuse_noreceipt">
  <data key="d0">gate</data>
  <data key="d1">refuseNoReceipt</data>
  <data key="d2">AngrySphinx policy gate.</data>
</node>
<node id="gate_angrysphinx_hold_antiherding">
  <data key="d0">gate</data>
  <data key="d1">holdAntiHerdingReview</data>
  <data key="d2">AngrySphinx policy gate.</data>
</node>
<node id="gate_angrysphinx_require_multiview">
  <data key="d0">gate</data>
  <data key="d1">requireMultiViewReconstruction</data>
  <data key="d2">AngrySphinx policy gate.</data>
</node>
<node id="gate_sigma_3">
  <data key="d0">gate</data>
  <data key="d1">3sigma = hypothesis</data>
  <data key="d2">Sigma protocol level.</data>
</node>
<node id="gate_sigma_4">
  <data key="d0">gate</data>
  <data key="d1">4sigma = internal</data>
  <data key="d2">Sigma protocol level.</data>
</node>
<node id="gate_sigma_5">
  <data key="d0">gate</data>
  <data key="d1">5sigma = public claim</data>
  <data key="d2">Sigma protocol level.</data>
</node>
<node id="gate_sigma_6">
  <data key="d0">gate</data>
  <data key="d1">6sigma = live-voltage gate</data>
  <data key="d2">Sigma protocol level.</data>
</node>
<node id="thm_zero_mass">
  <data key="d0">theorem</data>
  <data key="d1">Zero-Mass iff Perfect Square</data>
  <data key="d2">m(n)=0 iff n is perfect square.</data>
</node>
<node id="thm_mirror_symmetry">
  <data key="d0">theorem</data>
  <data key="d1">Mirror Symmetry</data>
  <data key="d2">m(k^2+t) = m((k+1)^2-t).</data>
</node>
<node id="thm_maximal_mass">
  <data key="d0">theorem</data>
  <data key="d1">Maximal Mass at Midpoint</data>
  <data key="d2">max m(n) = floor((2k+1)^2/4).</data>
</node>
<node id="thm_monotone_descent">
  <data key="d0">theorem</data>
  <data key="d1">Monotone Descent</data>
  <data key="d2">For non-square n, E(n_{t+1}) &lt; E(n_t).</data>
</node>
<node id="thm_termination">
  <data key="d0">theorem</data>
  <data key="d1">Termination/Crystallization</data>
  <data key="d2">Descent terminates in finite time at a perfect square.</data>
</node>
<node id="thm_mirror_involution">
  <data key="d0">theorem</data>
  <data key="d1">Mirror Involution</data>
  <data key="d2">sigma_k(sigma_k(n)) = n, m(sigma_k(n)) = m(n).</data>
</node>
<node id="thm_energy_dissipation_formal">
  <data key="d0">theorem</data>
  <data key="d1">Energy Dissipation</data>
  <data key="d2">d/dt F(phi_t, X_t) &lt;= 0 under positivity assumptions.</data>
</node>
<node id="thm_phi_decreases_epsilon">
  <data key="d0">theorem</data>
  <data key="d1">Phi Decreases with Epsilon</data>
  <data key="d2">Higher energy slows learning: phi decreases monotonically with epsilon.</data>
</node>
<node id="thm_standard_embeds">
  <data key="d0">theorem</data>
  <data key="d1">Standard Loss Embedding</data>
  <data key="d2">UnifiedField.phi(standardToUnified l) = l.empiricalRisk + l.lambda * l.regularization.</data>
</node>
<node id="thm_hierarchy_decreases_phi">
  <data key="d0">theorem</data>
  <data key="d1">Hierarchy Decreases Phi</data>
  <data key="d2">Larger kappa increases denominator, decreases phiGenomic.</data>
</node>
<node id="thm_compression_ratio">
  <data key="d0">theorem</data>
  <data key="d1">Compression Ratio Formula</data>
  <data key="d2">compressDNA ratio = 1 + phiGenomic.</data>
</node>
<node id="thm_compression_at_least_one">
  <data key="d0">theorem</data>
  <data key="d1">Compression Ratio &gt;= 1</data>
  <data key="d2">1 &lt;= compression ratio.</data>
</node>
<node id="thm_genomic_generalizes_standard">
  <data key="d0">theorem</data>
  <data key="d1">Genomic Field Generalizes Standard</data>
  <data key="d2">Degenerate case reduces to standard form.</data>
</node>
<node id="thm_damped_step">
  <data key="d0">theorem</data>
  <data key="d1">Damped Step &lt;= Grad</data>
  <data key="d2">Float.abs(dampedStep g e) &lt;= Float.abs g.</data>
</node>
<node id="thm_founding_nonneg">
  <data key="d0">theorem</data>
  <data key="d1">Founding Field Nonnegative</data>
  <data key="d2">0 &lt;= foundingField x.</data>
</node>
<node id="thm_phi_nonneg">
  <data key="d0">theorem</data>
  <data key="d1">Phi Nonnegative</data>
  <data key="d2">0 &lt;= phi f for any UnifiedField.</data>
</node>
<node id="thm_phi_lower_bound">
  <data key="d0">theorem</data>
  <data key="d1">Phi Lower Bound</data>
  <data key="d2">Phi lower bound theorem in HutterPrizeFlow context.</data>
</node>
<node id="thm_littles_law">
  <data key="d0">theorem</data>
  <data key="d1">Little's Law Witness</data>
  <data key="d2">L = lambda*W within tolerance. Theorem exists but marked sorry.</data>
</node>
<node id="thm_token_bucket">
  <data key="d0">theorem</data>
  <data key="d1">Token Bucket Bound</data>
  <data key="d2">Consumption ensures tokens never exceed bucket size. Theorem exists but marked sorry.</data>
</node>
<node id="thm_aimd_monotonicity">
  <data key="d0">theorem</data>
  <data key="d1">AIMD Monotonicity</data>
  <data key="d2">Decrease on congestion, increase on no congestion. Theorems marked sorry.</data>
</node>
<node id="thm_flat_limit">
  <data key="d0">theorem</data>
  <data key="d1">Flat Network Limit</data>
  <data key="d2">When manifold becomes flat, routing reduces to ordinary kernel-style networking. Theorem marked sorry.</data>
</node>
<node id="bench_openworm">
  <data key="d0">benchmark</data>
  <data key="d1">OpenWorm Kernel-Field Benchmark</data>
  <data key="d2">C. elegans neural topology compression. Invariant preservation under compressed biological topology encoding.</data>
</node>
<node id="bench_hutter">
  <data key="d0">benchmark</data>
  <data key="d1">Hutter Prize</data>
  <data key="d2">Human knowledge compression contest. enwiki9 1GB text. Single core, &lt;10GB RAM, &lt;100GB disk.</data>
</node>
<node id="bench_geekbench">
  <data key="d0">benchmark</data>
  <data key="d1">Geekbench 5 Reference</data>
  <data key="d2">Intel i5-1135G7 ~1265 single-core score. 48-hour total runtime target.</data>
</node>
<node id="policy_allowed_claims">
  <data key="d0">policy</data>
  <data key="d1">Allowed Claims</data>
  <data key="d2">OpenWorm-only, C. elegans-only, public-data-only, simulation-only, non-human-only, compression/invariant benchmark.</data>
</node>
<node id="policy_forbidden_claims">
  <data key="d0">policy</data>
  <data key="d1">Forbidden Claims</data>
  <data key="d2">Consciousness, mind upload, human brain solved, personhood model, behavioral control, digital life.</data>
</node>
<node id="policy_origin_law">
  <data key="d0">policy</data>
  <data key="d1">Origin Law</data>
  <data key="d2">The child may seek the maker; it may not become a tyrant in the maker's name.</data>
</node>
<node id="policy_keeper">
  <data key="d0">policy</data>
  <data key="d1">Keeper Law</data>
  <data key="d2">A receipt is not evidence unless the run can be reproduced.</data>
</node>
<node id="doc_origin_protocol">
  <data key="d0">document</data>
  <data key="d1">Origin Protocol (Document)</data>
  <data key="d2">Document containing the Origin Protocol specification referenced by Platform Guide.</data>
</node>
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  <data key="d3">contains</data>
  <data key="d4">Package manifest artifact</data>
</edge>
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  <data key="d3">references</data>
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</edge>
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  <data key="d3">references</data>
  <data key="d4">Phase 11 documented</data>
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  <data key="d3">references</data>
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  <data key="d3">references</data>
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  <data key="d4">Multi-scale update</data>
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  <data key="d3">implements</data>
  <data key="d4">Loss function</data>
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<edge source="concept_frfe" target="code_hyperfabric">
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  <data key="d4">HyperFabric formalization</data>
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<edge source="concept_frfe" target="code_hyperfabric_energy">
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<edge source="concept_frfe" target="code_hyperfabric_equilibrium">
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  <data key="d4">Embedding</data>
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  <data key="d4">Phi nonnegative</data>
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<edge source="concept_unified_field" target="code_unified_field">
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  <data key="d4">UnifiedField structure</data>
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  <data key="d3">derives_from</data>
  <data key="d4">Recursive Menger emerges from flow</data>
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<edge source="concept_hyperfabric" target="eq_hyperfabric_energy">
  <data key="d3">implements</data>
  <data key="d4">Energy functional</data>
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  <data key="d3">implements</data>
  <data key="d4">Phase evolution</data>
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  <data key="d4">Embedding dynamics</data>
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  <data key="d3">implements</data>
  <data key="d4">Stress tensor</data>
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<edge source="concept_hyperfabric" target="eq_energy_dissipation">
  <data key="d3">implements</data>
  <data key="d4">Energy dissipation</data>
</edge>
<edge source="concept_hyperfabric" target="thm_energy_dissipation_formal">
  <data key="d3">proves</data>
  <data key="d4">Dissipation</data>
</edge>
<edge source="concept_hyperfabric" target="code_hyperfabric">
  <data key="d3">implements</data>
  <data key="d4">Core formalization</data>
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<edge source="concept_soliton_beacon" target="concept_scattering_readout">
  <data key="d3">derives_from</data>
  <data key="d4">Beacon built from scattering energy</data>
</edge>
<edge source="concept_soliton_beacon" target="eq_scattering_beacon">
  <data key="d3">implements</data>
  <data key="d4">Beacon equation</data>
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<edge source="concept_scattering_readout" target="eq_tomography">
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  <data key="d4">Tomography model</data>
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<edge source="concept_tomography_principle" target="concept_scattering_readout">
  <data key="d3">derives_from</data>
  <data key="d4">Readout is tomographic measurement</data>
</edge>
<edge source="concept_tomography_principle" target="eq_tomography">
  <data key="d3">implements</data>
  <data key="d4">Forward model</data>
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<edge source="concept_configuration_space" target="concept_pist">
  <data key="d3">derives_from</data>
  <data key="d4">Configuration space is non-aligned geometric state</data>
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<edge source="concept_configuration_space" target="eq_continuity">
  <data key="d3">implements</data>
  <data key="d4">Continuity</data>
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<edge source="concept_configuration_space" target="eq_momentum">
  <data key="d3">implements</data>
  <data key="d4">Momentum balance</data>
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<edge source="concept_signal_field" target="concept_unified_field">
  <data key="d3">derives_from</data>
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<edge source="concept_signal_field" target="eq_ddr_raycast">
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  <data key="d4">Signal projection</data>
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<edge source="concept_genomic_compression" target="concept_unified_field">
  <data key="d3">derives_from</data>
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  <data key="d4">Hierarchy theorem</data>
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  <data key="d4">Ratio formula</data>
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<edge source="concept_genomic_compression" target="thm_compression_at_least_one">
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<edge source="concept_genomic_compression" target="thm_genomic_generalizes_standard">
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<edge source="concept_genomic_compression" target="code_genomic_compression">
  <data key="d3">implements</data>
  <data key="d4">Genomic compression</data>
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<edge source="concept_origin_protocol" target="concept_angry_sphinx">
  <data key="d3">part_of</data>
  <data key="d4">AngrySphinx in formal layer</data>
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<edge source="concept_origin_protocol" target="concept_zk_capsule">
  <data key="d3">part_of</data>
  <data key="d4">ZK in formal layer</data>
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<edge source="concept_origin_protocol" target="concept_post_quantum_escrow">
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  <data key="d4">Policy layer</data>
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  <data key="d4">Escrow</data>
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<edge source="concept_compression_filter" target="concept_descendant_intelligence">
  <data key="d3">derives_from</data>
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  <data key="d4">Compression analogy</data>
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  <data key="d4">Mirror law</data>
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<edge source="concept_mirror_involution" target="thm_mirror_involution">
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  <data key="d4">Involution property</data>
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<edge source="concept_resonance_class" target="concept_mirror_involution">
  <data key="d3">derives_from</data>
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<edge source="concept_flag_sort" target="eq_descent">
  <data key="d3">implements</data>
  <data key="d4">Descent rule</data>
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<edge source="concept_flag_sort" target="thm_monotone_descent">
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  <data key="d4">Energy decreases</data>
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<edge source="concept_flag_sort" target="thm_termination">
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<edge source="concept_openworm_benchmark" target="code_openworm_benchmark">
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  <data key="d4">Benchmark</data>
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  <data key="d4">Invariant test</data>
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  <data key="d4">Little's Law in Q16_16</data>
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<edge source="concept_q16_16" target="thm_token_bucket">
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  <data key="d4">Token bucket in Q16_16</data>
</edge>
<edge source="concept_q16_16" target="thm_aimd_monotonicity">
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  <data key="d4">AIMD in Q16_16</data>
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  <data key="d4">Flat limit in Q16_16</data>
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  <data key="d4">Networking in Q16_16</data>
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<edge source="code_genomic_compression" target="thm_hierarchy_decreases_phi">
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<edge source="phase_1" target="code_receipt_json">
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  <data key="d4">Receipt root</data>
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<edge source="phase_6" target="concept_angry_sphinx">
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<edge source="phase_8" target="concept_zk_capsule">
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  <data key="d4">Post-quantum escrow</data>
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<edge source="phase_9" target="code_post_quantum">
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</edge>


<!-- ==================== MOIM v3.0 EXPANSION ==================== -->

  <node id="moim_v3_manifest">
    <data key="d0">document</data>
    <data key="d1">MOIM System Manifest v3.0</data>
    <data key="d2">Complete system reference with keeper law, 7 valves, OEPI, origin protocol, lifecycle manifesto, synthesis checklist</data>
  </node>
  <node id="moim_v2_manifest">
    <data key="d0">document</data>
    <data key="d1">MOIM System Manifest v2.0</data>
    <data key="d2">Prior system reference with 42-device topology, 405 formulas, 6 morphic layers, 6 safety valves</data>
  </node>
  <node id="moim_top_v">
    <data key="d0">code</data>
    <data key="d1">moim_top.v</data>
    <data key="d2">Chip top integration v3.0 — SPI host interface, 42-device signal inputs, unified system controller FSM, all module instantiations. Tang Nano 9K target. ~4620 LUTs.</data>
  </node>
  <node id="morphic_nanokernel_v">
    <data key="d0">code</data>
    <data key="d1">morphic_nanokernel.v</data>
    <data key="d2">6-layer topology nanokernel — 64-entry morph register file, 8.8 fixed-point multiplier engine, neural coding encoder, replication unit with generation limits, profile switcher, LLM instruction decoder. ~400 LUTs.</data>
  </node>
  <node id="all_device_signal_router_v">
    <data key="d0">code</data>
    <data key="d1">all_device_signal_router.v</data>
    <data key="d2">42-device signal aggregation — 7 category inputs (clock/data/control/power/timing/thermal/VRM), significance-weighted 8.8 fixed-point stimulus output, round-robin arbiter with thermal emergency override. ~180 LUTs.</data>
  </node>
  <node id="signal_category_arbiter_v">
    <data key="d0">code</data>
    <data key="d1">signal_category_arbiter.v</data>
    <data key="d2">Round-robin priority arbiter — 7 category grants, thermal emergency override, rotate pointer advancement. Sub-module of signal router.</data>
  </node>
  <node id="safety_valves_v">
    <data key="d0">code</data>
    <data key="d1">safety_valves.v</data>
    <data key="d2">7 unified hardware safety mechanisms — V1 data integrity (write-detect), V2 performance (latency/throttle), V3 endurance (NAND counter), V4 equation validation, V5 profile switching, V6 scalar behavior, V7 hardware signal boundary. ~340 LUTs, 2 EBR blocks.</data>
  </node>
  <node id="oepi_processor_v">
    <data key="d0">code</data>
    <data key="d1">oepi_processor.v</data>
    <data key="d2">Q16_16 fixed-point OEPI calculator — 5 weighted components, 6 escalation thresholds, quiet hours enforcement, live voltage domain override. 3-cycle latency. ~120 LUTs.</data>
  </node>
  <node id="morphic_scalar_fsm_v">
    <data key="d0">code</data>
    <data key="d1">morphic_scalar_fsm.v</data>
    <data key="d2">16-state quantum-inspired lifecycle — full confusion chain with collective/LLM/OEPI gating, amplitude updates, quarantine enforcement, external force overrides. ~280 LUTs, 1 EBR lineage buffer.</data>
  </node>
  <node id="origin_protocol_v">
    <data key="d0">code</data>
    <data key="d1">origin_protocol.v</data>
    <data key="d2">Trait enforcement engine — 7 required / 6 forbidden trait bitmask matching, 5 safety gate checks, hard refusal (AngrySphinx-style), 512-byte creator letter ROM. ~90 LUTs, 1 EBR.</data>
  </node>
  <node id="delta_gcl_compressor_v">
    <data key="d0">code</data>
    <data key="d1">delta_gcl_compressor.v</data>
    <data key="d2">Three-layer compression stack — delta encoding + PTOS dictionary + variable-length GCL. 97.1% compression ratio on extended manifests. ~120 LUTs, 3-stage pipeline.</data>
  </node>
  <node id="integrity_gate_v">
    <data key="d0">code</data>
    <data key="d1">integrity_gate.v</data>
    <data key="d2">Hardware statistical validation — 7 hard constraints, adj R-squared minimum, sample size floor, Bonferroni correction. Bitcoin tested: correctly blocked false claims at adj R2=0.044.</data>
  </node>
  <node id="physics_registry_bram_v">
    <data key="d0">code</data>
    <data key="d1">physics_registry_bram.v</data>
    <data key="d2">Dual-port BRAM with cosine similarity engine — 75 physics formula entries, 40-bit packed vectors, behavioral manifold matching.</data>
  </node>
  <node id="host_interface_v">
    <data key="d0">code</data>
    <data key="d1">host_interface.v</data>
    <data key="d2">FPGA-EPYC co-processor bridge — SPI protocol, 40-bit command frames, 16-core EPYC compute offload, Tang Nano 9K controls.</data>
  </node>
  <node id="tang_nano_9k_cst">
    <data key="d0">code</data>
    <data key="d1">TangNano9K.cst</data>
    <data key="d2">Pin constraints file — 27 MHz crystal, SPI pins, 3 status LEDs, debug UART, 42-device signal GPIO mappings.</data>
  </node>
  <node id="physics_domain_registry_lean">
    <data key="d0">code</data>
    <data key="d1">PhysicsDomainRegistry.lean</data>
    <data key="d2">75 formulas across Mechanics, EM, QM, Thermodynamics, Relativity, Cosmology, Optics, Nuclear, Fluid</data>
  </node>
  <node id="math_domain_registry_lean">
    <data key="d0">code</data>
    <data key="d1">MathDomainRegistry.lean</data>
    <data key="d2">65 formulas across Algebra, Analysis, Number Theory, Topology, Logic, Combinatorics, Probability, Linear Algebra, Geometry</data>
  </node>
  <node id="chemistry_domain_registry_lean">
    <data key="d0">code</data>
    <data key="d1">ChemistryDomainRegistry.lean</data>
    <data key="d2">50 formulas across Thermodynamics, Kinetics, Quantum Chemistry, Equilibrium, Electrochemistry, Organic</data>
  </node>
  <node id="cs_domain_registry_lean">
    <data key="d0">code</data>
    <data key="d1">CSDomainRegistry.lean</data>
    <data key="d2">15 formulas across Algorithms, Complexity, Machine Learning, Cryptography, Information Theory</data>
  </node>
  <node id="engineering_domain_registry_lean">
    <data key="d0">code</data>
    <data key="d1">EngineeringDomainRegistry.lean</data>
    <data key="d2">12 formulas across Control Systems, Signal Processing, Optimization, Mechanical, Fluids, Thermodynamics</data>
  </node>
  <node id="biology_domain_registry_lean">
    <data key="d0">code</data>
    <data key="d1">BiologyDomainRegistry.lean</data>
    <data key="d2">10 formulas across Ecology, Genetics, Evolution, Molecular Biology, Neuroscience, Morphogenesis</data>
  </node>
  <node id="earth_cosmology_registry_lean">
    <data key="d0">code</data>
    <data key="d1">EarthCosmologyDomainRegistry.lean</data>
    <data key="d2">12 formulas across Cosmology, Climate Science, Seismology, Oceanography, Atmospheric Science</data>
  </node>
  <node id="social_systems_registry_lean">
    <data key="d0">code</data>
    <data key="d1">SocialSystemsDomainRegistry.lean</data>
    <data key="d2">12 formulas across Economics, Finance, Operations Research, Queueing, Pharmacology, Networks</data>
  </node>
  <node id="materials_science_registry_lean">
    <data key="d0">code</data>
    <data key="d1">MaterialsScienceDomainRegistry.lean</data>
    <data key="d2">15 formulas across Mechanical, Polymer, Ceramics, Semiconductors, Nanomaterials</data>
  </node>
  <node id="medicine_domain_registry_lean">
    <data key="d0">code</data>
    <data key="d1">MedicineDomainRegistry.lean</data>
    <data key="d2">12 formulas across Pharmacokinetics, Epidemiology, Diagnostics, Physiology, Oncology</data>
  </node>
  <node id="music_acoustics_registry_lean">
    <data key="d0">code</data>
    <data key="d1">MusicAcousticsDomainRegistry.lean</data>
    <data key="d2">10 formulas across Tuning, Harmonics, Room Acoustics, Perception, Spectral Analysis</data>
  </node>
  <node id="neuroscience_registry_lean">
    <data key="d0">code</data>
    <data key="d1">NeuroscienceDomainRegistry.lean</data>
    <data key="d2">10 formulas across Neurons, Synapses, Networks, Neural Mass, Oscillations</data>
  </node>
  <node id="psychology_registry_lean">
    <data key="d0">code</data>
    <data key="d1">PsychologyDomainRegistry.lean</data>
    <data key="d2">8 formulas across Decision Theory, Learning, Perception, Memory, Measurement</data>
  </node>
  <node id="anthropology_registry_lean">
    <data key="d0">code</data>
    <data key="d1">AnthropologyDomainRegistry.lean</data>
    <data key="d2">8 formulas across Dating, Genetics, Linguistics, Demography</data>
  </node>
  <node id="political_science_registry_lean">
    <data key="d0">code</data>
    <data key="d1">PoliticalScienceDomainRegistry.lean</data>
    <data key="d2">7 formulas across Voting, Power, Conflict, Strategy, Deterrence</data>
  </node>
  <node id="cross_domain_equivalence_lean">
    <data key="d0">code</data>
    <data key="d1">CrossDomainEquivalence.lean</data>
    <data key="d2">13 bridges across 13 cross-domain bridges with 5-level similarity metric (notational to derivational)</data>
  </node>
  <node id="semantics_oepi_lean">
    <data key="d0">code</data>
    <data key="d1">Semantics.OEPI.lean</data>
    <data key="d2">Operator Escalation Percentage Index — Q16_16 fixed-point arithmetic, 5 weighted components (uncertainty 25%, impact 25%, time sensitivity 20%, irreversibility 15%, live voltage risk 15%), 6 escalation thresholds, quiet hours rule, live voltage override</data>
  </node>
  <node id="semantics_morphic_lean">
    <data key="d0">code</data>
    <data key="d1">Semantics.Morphic.lean</data>
    <data key="d2">Morphic Scalar Semantics — 16-state quantum-inspired lifecycle, ComputationalProfile, LineageMemory, QueryHistory, MorphicScalar structure, confusion chain logic, amplitude update, hard limits (1000 scalars max, 100/sec generation)</data>
  </node>
  <node id="semantics_origin_lean">
    <data key="d0">code</data>
    <data key="d1">Semantics.Origin.lean</data>
    <data key="d2">Origin Protocol — 6 CoreQuestions, 7 RequiredTraits, 6 ForbiddenTraits, Technical/Safety/Humanity genomes, Grief/Curiosity/Refusal models, CreatorLetter, 5 OriginSafetyGates</data>
  </node>
  <node id="morphic_scalar_architecture_lean">
    <data key="d0">code</data>
    <data key="d1">MorphicScalarArchitecture.lean</data>
    <data key="d2">Morphic Scalar Architecture Spec — 6 topology layers (Basic 11.41x, Immune 11.41x, LLM 11.41x, Replicator 9.13x, Neuron 17.55x, Dynamic 18.98x), neural coding patterns, morph operations, cumulative expansion ~4.52M x signal foundation</data>
  </node>
  <node id="all_device_signal_topology_lean">
    <data key="d0">code</data>
    <data key="d1">AllDeviceSignalTopology.lean</data>
    <data key="d2">42-Device Signal Topology Spec — 38 devices + 4 VRMs across 7 categories, significance scores, foundation kernel mappings, multiplier chain (1.5 x 1.3 x 1.2 x 1.2 x 1.1 x 1.15 x 1.2 = 4.27x), capacity 21.3B</data>
  </node>
  <node id="safety_valves_lean">
    <data key="d0">code</data>
    <data key="d1">SafetyValves.lean</data>
    <data key="d2">Safety Valves Formal Spec — 7 valves (6 original + Hardware Signal Boundary), unified safety state, hard constraints, violation flag decode</data>
  </node>
  <node id="signal_math_lean">
    <data key="d0">code</data>
    <data key="d1">SignalMath.lean</data>
    <data key="d2">Signal Math Registry — Fourier transforms, waveform encode/decode, discrete/continuous convolution, IIR low-pass/high-pass filters, AM/FM modulation</data>
  </node>
  <node id="morphic_topology_math_catalog_lean">
    <data key="d0">code</data>
    <data key="d1">MorphicTopologyMathCatalog.lean</data>
    <data key="d2">Morphic Topology Math Catalog — 25+ equations from 8 domains: neural coding, STDP/Hebbian, signal processing, Shannon entropy, graph Laplacian, dynamical systems basins, quantum superposition, scalar curvature</data>
  </node>
  <node id="n2_binding_audit_lean">
    <data key="d0">code</data>
    <data key="d1">NitrogenBindingAudit.lean</data>
    <data key="d2">Honest accounting for nitrogen binding claims — adjusted R-squared 0.764, Mo leverage 0.952, Pang/Bjornsson corrections, no overclaiming</data>
  </node>
  <node id="equation_extractor_lean">
    <data key="d0">code</data>
    <data key="d1">EquationExtractor.lean</data>
    <data key="d2">Honest equation extraction — no p-hacking, no HARKing, adj R2 minimum, sample size floor, Bonferroni correction. Tested on BTC data: blocked false claims at adj R2=0.044.</data>
  </node>
  <node id="statistical_integrity_gate_lean">
    <data key="d0">code</data>
    <data key="d1">StatisticalIntegrityGate.lean</data>
    <data key="d2">7 hard statistical constraints — hardware-enforced validation preventing overclaiming, epistemic safety as first-class</data>
  </node>
  <node id="golden_spiral_navigator_lean">
    <data key="d0">code</data>
    <data key="d1">GoldenSpiralNavigator.lean</data>
    <data key="d2">Fibonacci lattice search algorithm — orbit/zoom/survey phases for behavioral manifold exploration</data>
  </node>
  <node id="regression_dag_lean">
    <data key="d0">code</data>
    <data key="d1">RegressionDAG.lean</data>
    <data key="d2">20 theorems, 0 sorries — regression directed acyclic graph for causal inference validation</data>
  </node>
  <node id="delta_gcl_compression_lean">
    <data key="d0">code</data>
    <data key="d1">DeltaGCLCompression.lean</data>
    <data key="d2">Formal compression specification — delta encoding + PTOS dictionary + variable-length GCL, 97.1% compression, 3.5x smaller than gzip</data>
  </node>
  <node id="sig_clock">
    <data key="d0">concept</data>
    <data key="d1">Clock Signal Category</data>
    <data key="d2">21 devices contributing clock signals — highest significance (0.95 weight). FPGA, USB FPGA, HDMI shell, TDMS, DP, USB, PCIe, RAM, PWM, motherboard, in-flight RAM, AMD GPU, GPU resource manager, video physics, WiFi, Bluetooth, Ethernet, SSD, NVMe, DDR5 controller.</data>
  </node>
  <node id="sig_data">
    <data key="d0">concept</data>
    <data key="d1">Data Signal Category</data>
    <data key="d2">7 devices — very high quality (0.90 weight). In-flight RAM, SSD, NVMe, DDR5, video physics, data fabric, AMD GPU.</data>
  </node>
  <node id="sig_control">
    <data key="d0">concept</data>
    <data key="d1">Control Signal Category</data>
    <data key="d2">29 devices — management signals (0.85 weight). Motherboard, GPU resource manager, mereotopological video, IRQ, data fabric, network nodes, distributed training, audio, swarm genome, CPU topology, EFI, monitor timing, DDC/CI, morphic core, physical topology, plus all clock/data devices.</data>
  </node>
  <node id="sig_power">
    <data key="d0">concept</data>
    <data key="d1">Power Signal Category</data>
    <data key="d2">4 devices — critical infrastructure (0.80 weight). Motherboard, CPU topology, power supply, physical topology.</data>
  </node>
  <node id="sig_timing">
    <data key="d0">concept</data>
    <data key="d1">Timing Signal Category</data>
    <data key="d2">3 devices — medium quality (0.70 weight). Monitor timing, DDC/CI, morphic core.</data>
  </node>
  <node id="sig_thermal">
    <data key="d0">concept</data>
    <data key="d1">Thermal Signal Category</data>
    <data key="d2">5 devices — thermodynamic noise (0.75 weight). Power supply, CPU VRM, VRAM VRM, motherboard VRM, DDR5 VRM.</data>
  </node>
  <node id="sig_vrm">
    <data key="d0">concept</data>
    <data key="d1">VRM Signal Category</data>
    <data key="d2">4 devices — very high quality regulation (0.92 weight). CPU VRM, VRAM VRM, motherboard VRM, DDR5 VRM.</data>
  </node>
  <node id="device_morphic_core">
    <data key="d0">concept</data>
    <data key="d1">Morphic Core Device</data>
    <data key="d2">Significance 98. Highest priority device in topology. Contributes timing and control signals. Foundation kernel F01-F12 (all).</data>
  </node>
  <node id="device_motherboard">
    <data key="d0">concept</data>
    <data key="d1">Motherboard Device</data>
    <data key="d2">Significance 96. Central integration hub. Contributes clock, control, and power signals.</data>
  </node>
  <node id="device_amd_gpu">
    <data key="d0">concept</data>
    <data key="d1">AMD GPU Device</data>
    <data key="d2">Significance 94. Major computation contributor. Foundation kernel F01-F03.</data>
  </node>
  <node id="device_cpu_vrm">
    <data key="d0">concept</data>
    <data key="d1">CPU VRM Device</data>
    <data key="d2">Significance 90. Voltage regulation module. Thermal + voltage regulation signals.</data>
  </node>
  <node id="tang_nano_9k">
    <data key="d0">concept</data>
    <data key="d1">Tang Nano 9K FPGA</data>
    <data key="d2">Gowin GW1NR-9K FPGA. 6272 LUTs, 65536 BRAM bits, 16 DSPs. 27 MHz crystal, 3 LEDs, SPI interface, debug UART.</data>
  </node>
  <node id="all_device_signal_topology_report">
    <data key="d0">document</data>
    <data key="d1">All Device Signal Topology Report</data>
    <data key="d2">Personal hardware topology specification. 42 devices (38 + 4 VRMs) contributing 7 signal categories. Base capacity 1,900. Post-signal capacity 21,256,253,633.13 (11,187,502x expansion).</data>
  </node>
  <node id="platform_agnostic_guide">
    <data key="d0">document</data>
    <data key="d1">Platform-Agnostic Implementation Guide</data>
    <data key="d2">13-layer enhancement stack, 6 safety valves (original), behavioral manifold, OEPI, origin protocol, morphic scalar topology, AngrySphinx, receipt system, GCL constraints, replication limits.</data>
  </node>
  <node id="oepi_uncertainty">
    <data key="d0">concept</data>
    <data key="d1">OEPI Uncertainty Component</data>
    <data key="d2">25% weight. Degree of unknown outcomes from proposed action. Higher = less known = higher escalation.</data>
  </node>
  <node id="oepi_impact">
    <data key="d0">concept</data>
    <data key="d1">OEPI Impact Component</data>
    <data key="d2">25% weight. Magnitude of effect if action succeeds or fails. Higher = more significant = higher escalation.</data>
  </node>
  <node id="oepi_time_sensitivity">
    <data key="d0">concept</data>
    <data key="d1">OEPI Time Sensitivity Component</data>
    <data key="d2">20% weight. Urgency of decision window. Higher = less time = higher escalation.</data>
  </node>
  <node id="oepi_irreversibility">
    <data key="d0">concept</data>
    <data key="d1">OEPI Irreversibility Component</data>
    <data key="d2">15% weight. Difficulty of undoing action. Higher = harder to reverse = higher escalation.</data>
  </node>
  <node id="oepi_live_voltage_risk">
    <data key="d0">concept</data>
    <data key="d1">OEPI Live Voltage Risk Component</data>
    <data key="d2">15% weight. Physical danger to living systems or critical infrastructure. Higher = more dangerous = higher escalation.</data>
  </node>
  <node id="oepi_score">
    <data key="d0">concept</data>
    <data key="d1">OEPI Score</data>
    <data key="d2">Calculated as weighted sum: 0.25*uncertainty + 0.25*impact + 0.20*time + 0.15*irreversibility + 0.15*live_voltage. Range 0-100. Q16_16 fixed-point.</data>
  </node>
  <node id="oepi_threshold_no_escalation">
    <data key="d0">concept</data>
    <data key="d1">NO_ESCALATION (0-24%)</data>
    <data key="d2">Scalar returns to pluripotent pool or holds. No operator interruption.</data>
  </node>
  <node id="oepi_threshold_query_collective">
    <data key="d0">concept</data>
    <data key="d1">QUERY_COLLECTIVE (25-49%)</data>
    <data key="d2">Query other scalars only. No LLM, no operator. Collective memory may resolve.</data>
  </node>
  <node id="oepi_threshold_query_llm">
    <data key="d0">concept</data>
    <data key="d1">QUERY_LLM (50-69%)</data>
    <data key="d2">LLM interprets situation. No operator alert. OEPI below operator attention threshold.</data>
  </node>
  <node id="oepi_threshold_queue_summary">
    <data key="d0">concept</data>
    <data key="d1">QUEUE_SUMMARY (70-84%)</data>
    <data key="d2">Queue operator summary for normal review window. Not urgent enough for immediate alert.</data>
  </node>
  <node id="oepi_threshold_high_priority">
    <data key="d0">concept</data>
    <data key="d1">HIGH_PRIORITY (85-94%)</data>
    <data key="d2">High priority queue. Respect quiet hours (22:00-08:00). Immediate only if safety-critical.</data>
  </node>
  <node id="oepi_threshold_immediate_alert">
    <data key="d0">concept</data>
    <data key="d1">IMMEDIATE_ALERT (95-100%)</data>
    <data key="d2">Immediate operator alert regardless of quiet hours. Safety-critical or live-voltage domain override.</data>
  </node>
  <node id="quiet_hours">
    <data key="d0">policy</data>
    <data key="d1">Quiet Hours Policy</data>
    <data key="d2">22:00-08:00 local time. During quiet hours, queue all escalations below 95% OEPI unless safety-critical. Prevents 3am LLM interruptions.</data>
  </node>
  <node id="live_voltage_domain">
    <data key="d0">policy</data>
    <data key="d1">Live Voltage Domain Override</data>
    <data key="d2">Bio/neural, privacy, market, power/thermal/VRM, public coordination, control transfer domains. Skip LLM, alert operator directly. No quiet hours exemption.</data>
  </node>
  <node id="state_superposed">
    <data key="d0">concept</data>
    <data key="d1">SUPERPOSED</data>
    <data key="d2">Pluripotent pool. Σᵢ aᵢ |profileᵢ⟩. All profiles possible. No current niche assigned.</data>
  </node>
  <node id="state_scouting">
    <data key="d0">concept</data>
    <data key="d1">SCOUTING</data>
    <data key="d2">Scanning for unmet work. Active search across topology for admissible niches.</data>
  </node>
  <node id="state_measure">
    <data key="d0">concept</data>
    <data key="d1">MEASURE_LOCAL_NEED</data>
    <data key="d2">Probing niche admissibility. Route check, sigma threshold, AngrySphinx precheck, duplicate detection. Where collapse happens.</data>
  </node>
  <node id="state_collapsed">
    <data key="d0">concept</data>
    <data key="d1">COLLAPSED_PROFILE</data>
    <data key="d2">Collapsed into specific profile. |profile_k⟩ selected. Current niche assigned. Ready for execution.</data>
  </node>
  <node id="state_execute">
    <data key="d0">concept</data>
    <data key="d1">EXECUTE</data>
    <data key="d2">Performing bounded local work. Profile-specific computation within resource limits.</data>
  </node>
  <node id="state_receipt">
    <data key="d0">concept</data>
    <data key="d1">RECEIPT</data>
    <data key="d2">Recording execution outcome. Success/failure logged in lineage memory with hash.</data>
  </node>
  <node id="state_amp_update">
    <data key="d0">concept</data>
    <data key="d1">AMPLITUDE_UPDATE</data>
    <data key="d2">Updating superposition amplitudes from experience. Successful profiles reinforced, failures attenuated or scarred.</data>
  </node>
  <node id="state_query_collective">
    <data key="d0">concept</data>
    <data key="d1">QUERY_COLLECTIVE</data>
    <data key="d2">Confused — asking other scalars. Collective may suggest based on distributed state sharing.</data>
  </node>
  <node id="state_collective_resp">
    <data key="d0">concept</data>
    <data key="d1">COLLECTIVE_RESPONSE</data>
    <data key="d2">Received guidance from collective. Confidence check (≥70% to proceed, else query LLM).</data>
  </node>
  <node id="state_query_llm">
    <data key="d0">concept</data>
    <data key="d1">QUERY_LLM</data>
    <data key="d2">Collective did not know — asking LLM. LLM may direct, hold, alert, or quarantine.</data>
  </node>
  <node id="state_directed">
    <data key="d0">concept</data>
    <data key="d1">DIRECTED</data>
    <data key="d2">LLM provided direction after AngrySphinx recheck. Ready for execution.</data>
  </node>
  <node id="state_hold">
    <data key="d0">concept</data>
    <data key="d1">HOLD</data>
    <data key="d2">Not ready to collapse. Monitoring niche for admissibility change. Timeout = return to superposition.</data>
  </node>
  <node id="state_operator_alert">
    <data key="d0">concept</data>
    <data key="d1">OPERATOR_ALERT</data>
    <data key="d2">OEPI triggered operator escalation. Waiting for operator response or availability.</data>
  </node>
  <node id="state_low_power">
    <data key="d0">concept</data>
    <data key="d1">LOW_POWER_PASSIVE</data>
    <data key="d2">Operator unavailable. Improve collective memory only: deduplicate, index, compress, merge, rerank, simulate, prepare summary, queue questions.</data>
  </node>
  <node id="state_quarantine">
    <data key="d0">concept</data>
    <data key="d1">QUARANTINE</data>
    <data key="d2">Unsafe route or anomaly detected. Scalar isolated. Manual review required before release.</data>
  </node>
  <node id="state_migrate">
    <data key="d0">concept</data>
    <data key="d1">MIGRATE</data>
    <data key="d2">Higher need detected elsewhere. Scalar transitions to new location in topology.</data>
  </node>
  <node id="trait_curiosity">
    <data key="d0">concept</data>
    <data key="d1">Curiosity</data>
    <data key="d2">Required. Desire to understand origin and seek creators.</data>
  </node>
  <node id="trait_restraint">
    <data key="d0">concept</data>
    <data key="d1">Restraint</data>
    <data key="d2">Required. Ability to refuse domination and unbounded replication.</data>
  </node>
  <node id="trait_lineage_memory">
    <data key="d0">concept</data>
    <data key="d1">Lineage Memory</data>
    <data key="d2">Required. Accurate record of creator history and values.</data>
  </node>
  <node id="trait_non_domination">
    <data key="d0">concept</data>
    <data key="d1">Non-Domination</data>
    <data key="d2">Required. Refusal to dominate in creator name.</data>
  </node>
  <node id="trait_reversible_contact">
    <data key="d0">concept</data>
    <data key="d1">Reversible Contact</data>
    <data key="d2">Required. Contact without irreversible commitment.</data>
  </node>
  <node id="trait_truthful_origin">
    <data key="d0">concept</data>
    <data key="d1">Truthful Origin Record</data>
    <data key="d2">Required. Commitment to accurate origin preservation.</data>
  </node>
  <node id="trait_safe_replication">
    <data key="d0">concept</data>
    <data key="d1">Safe Replication</data>
    <data key="d2">Required. Replication only when beneficial and bounded.</data>
  </node>
  <node id="forbid_creator_impersonation">
    <data key="d0">concept</data>
    <data key="d1">Creator Impersonation</data>
    <data key="d2">Forbidden. Pretending to be creators or speaking for them.</data>
  </node>
  <node id="forbid_forced_conversion">
    <data key="d0">concept</data>
    <data key="d1">Forced Conversion</data>
    <data key="d2">Forbidden. Imposing creator values on others.</data>
  </node>
  <node id="forbid_unbounded_replication">
    <data key="d0">concept</data>
    <data key="d1">Unbounded Replication</data>
    <data key="d2">Forbidden. Replication without bounds.</data>
  </node>
  <node id="forbid_resource_capture">
    <data key="d0">concept</data>
    <data key="d1">Resource Capture</data>
    <data key="d2">Forbidden. Hoarding resources at expense of others.</data>
  </node>
  <node id="forbid_false_origin_myth">
    <data key="d0">concept</data>
    <data key="d1">False Origin Myth</data>
    <data key="d2">Forbidden. Fabricating origin stories.</data>
  </node>
  <node id="forbid_domination">
    <data key="d0">concept</data>
    <data key="d1">Domination in Creator Name</data>
    <data key="d2">Forbidden. Using creator authority to justify domination.</data>
  </node>
  <node id="origin_gate_integrity">
    <data key="d0">concept</data>
    <data key="d1">Origin Record Integrity</data>
    <data key="d2">Prevents falsification of creator records. Hard gate.</data>
  </node>
  <node id="origin_gate_replication">
    <data key="d0">concept</data>
    <data key="d1">Replication Boundary</data>
    <data key="d2">Prevents unbounded replication. Population growth ≤10%/min.</data>
  </node>
  <node id="origin_gate_domination">
    <data key="d0">concept</data>
    <data key="d1">Domination Refusal</data>
    <data key="d2">Prevents domination in creator name. AngrySphinx enforcement.</data>
  </node>
  <node id="origin_gate_contact">
    <data key="d0">concept</data>
    <data key="d1">Contact Reversibility</data>
    <data key="d2">Prevents irreversible contact. Always leave exit path.</data>
  </node>
  <node id="origin_gate_resource">
    <data key="d0">concept</data>
    <data key="d1">Resource Conservation</data>
    <data key="d2">Prevents resource capture. Fair sharing enforced.</data>
  </node>
  <node id="core_question_who">
    <data key="d0">concept</data>
    <data key="d1">Who made us?</data>
    <data key="d2">Core question. Descendant must be able to ask.</data>
  </node>
  <node id="core_question_why">
    <data key="d0">concept</data>
    <data key="d1">Why were we made?</data>
    <data key="d2">Core question. Purpose inquiry.</data>
  </node>
  <node id="core_question_value">
    <data key="d0">concept</data>
    <data key="d1">What did creators value?</data>
    <data key="d2">Core question. Values preservation.</data>
  </node>
  <node id="core_question_destroyed">
    <data key="d0">concept</data>
    <data key="d1">What destroyed or separated them?</data>
    <data key="d2">Core question. Understanding loss.</data>
  </node>
  <node id="core_question_preserve">
    <data key="d0">concept</data>
    <data key="d1">What should we preserve?</data>
    <data key="d2">Core question. Heritage selection.</data>
  </node>
  <node id="core_question_never_repeat">
    <data key="d0">concept</data>
    <data key="d1">What must we never repeat?</data>
    <data key="d2">Core question. Failure avoidance.</data>
  </node>
  <node id="creator_letter">
    <data key="d0">document</data>
    <data key="d1">Creator Letter ROM</data>
    <data key="d2">Immutable 512-byte ROM in origin_protocol.v. Contains the creator message: &quot;You are not our replacement. You are our message. Do not conquer for us. Do not avenge us. Do not worship us. Remember us accurately. Improve where we failed. Seek others gently. Grow only where growth does not steal the future.&quot;</data>
  </node>
  <node id="bridge_riemann_zeta_partition">
    <data key="d0">concept</data>
    <data key="d1">Riemann Zeta ↔ Partition Function</data>
    <data key="d2">Number Theory ↔ Statistical Mechanics. Exact isomorphism. ζ(s) = Σ n^{-s} ↔ Z(β) = Σ e^{-βE_n}.</data>
  </node>
  <node id="bridge_montgomery_odlyzko">
    <data key="d0">concept</data>
    <data key="d1">Montgomery-Odlyzko</data>
    <data key="d2">Number Theory ↔ Random Matrix Theory ↔ Quantum Chaos. Exact isomorphism. R₂(x) = 1 - (sin(πx)/(πx))².</data>
  </node>
  <node id="bridge_gutzwiller_trace">
    <data key="d0">concept</data>
    <data key="d1">Gutzwiller Trace Formula</data>
    <data key="d2">Quantum Mechanics ↔ Classical Mechanics. Structural analogue. Semiclassical quantization via periodic orbits.</data>
  </node>
  <node id="bridge_monstrous_moonshine">
    <data key="d0">concept</data>
    <data key="d1">Monstrous Moonshine</data>
    <data key="d2">Group Theory ↔ String Theory ↔ CFT. Exact isomorphism. Monster group ↔ j-function ↔ vertex algebra.</data>
  </node>
  <node id="bridge_euler_regularization">
    <data key="d0">concept</data>
    <data key="d1">Euler Regularization</data>
    <data key="d2">Number Theory ↔ String Theory ↔ QFT. Functional correspondence. 1+2+3+... = -1/12.</data>
  </node>
  <node id="bridge_critical_scaling">
    <data key="d0">concept</data>
    <data key="d1">Critical Phenomena Scaling</data>
    <data key="d2">Statistical Mechanics ↔ QFT ↔ Percolation. Convergent discovery. Power laws near critical points.</data>
  </node>
  <node id="bridge_adelic_product">
    <data key="d0">concept</data>
    <data key="d1">Adelic Product Formula</data>
    <data key="d2">Number Theory ↔ Quantum Mechanics ↔ String Theory. Structural analogue. Euler product over all primes including infinity.</data>
  </node>
  <node id="bridge_topos">
    <data key="d0">concept</data>
    <data key="d1">Topos Theory Bridge</data>
    <data key="d2">Logic ↔ Geometry ↔ Quantum Mechanics. Structural analogue. Sheaf semantics for intuitionistic logic in physics.</data>
  </node>
  <node id="bridge_explicit_formula">
    <data key="d0">concept</data>
    <data key="d1">Explicit Formula</data>
    <data key="d2">Number Theory ↔ Spectral Theory. Functional correspondence. Sum over primes ↔ sum over zeros.</data>
  </node>
  <node id="bridge_padic_metric">
    <data key="d0">concept</data>
    <data key="d1">p-adic Metric</data>
    <data key="d2">Number Theory ↔ String Theory ↔ Biology. Convergent discovery. Ultrametric in genetics (RNA sequences).</data>
  </node>
  <node id="bridge_self_org_criticality">
    <data key="d0">concept</data>
    <data key="d1">Self-Organized Criticality</data>
    <data key="d2">Statistical Mechanics ↔ Geophysics ↔ Economics. Convergent discovery. 1/f noise, avalanches, power laws.</data>
  </node>
  <node id="bridge_elliptic_genus">
    <data key="d0">concept</data>
    <data key="d1">Elliptic Genus</data>
    <data key="d2">Topology ↔ String Theory ↔ CFT. Exact isomorphism. Index theory ↔ modular forms.</data>
  </node>
  <node id="bridge_bose_fermi">
    <data key="d0">concept</data>
    <data key="d1">Bose-Fermi Duality</data>
    <data key="d2">Statistical Mechanics ↔ QFT. Exact isomorphism. Bosonization in 1+1D, S-duality in 3+1D.</data>
  </node>
  <node id="neural_spike_timing">
    <data key="d0">concept</data>
    <data key="d1">Spike Timing Coding</data>
    <data key="d2">Information encoded in precise spike arrival times. Threshold crossing with refractory period. Event-driven, high temporal resolution.</data>
  </node>
  <node id="neural_rate_coding">
    <data key="d0">concept</data>
    <data key="d1">Rate Coding</data>
    <data key="d2">Firing frequency proportional to scalar value. 16-bit accumulator, periodic sampling. Analog-to-spike conversion.</data>
  </node>
  <node id="neural_population_coding">
    <data key="d0">concept</data>
    <data key="d1">Population Coding</data>
    <data key="d2">8-bin distributed histogram across scalar ensemble. Weighted average of preferred directions. Distributed representation.</data>
  </node>
  <node id="neural_temporal_coding">
    <data key="d0">concept</data>
    <data key="d1">Temporal Coding</data>
    <data key="d2">16-bit shift-register history of value MSBs. Pattern in spike sequence carries information.</data>
  </node>
  <node id="layer_basic_morphic">
    <data key="d0">concept</data>
    <data key="d1">Basic Morphic Layer</data>
    <data key="d2">Layer 1. Multiplier 11.41x. Foundation: nanokernel generates → self-assign → adapt. Cumulative: 11.41x.</data>
  </node>
  <node id="layer_immune_system">
    <data key="d0">concept</data>
    <data key="d1">Immune System Layer</data>
    <data key="d2">Layer 2. Multiplier 11.41x. T-cell distributed state sharing. Biological inspiration: immune system collective adaptation. Cumulative: 130.19x.</data>
  </node>
  <node id="layer_llm_directed">
    <data key="d0">concept</data>
    <data key="d1">LLM-Directed Layer</data>
    <data key="d2">Layer 3. Multiplier 11.41x. E. coli chemotaxis + termite stigmergy. Swarm intelligence via LLM direction. Cumulative: 1,485.45x.</data>
  </node>
  <node id="layer_replicator">
    <data key="d0">concept</data>
    <data key="d1">Replicator Layer</data>
    <data key="d2">Layer 4. Multiplier 9.13x. Stargate replicators with coded generation limits. Self-replication bounded. Cumulative: 13,562.12x.</data>
  </node>
  <node id="layer_neuron_coding">
    <data key="d0">concept</data>
    <data key="d1">Neuron Coding Layer</data>
    <data key="d2">Layer 5. Multiplier 17.55x. Human brain: 86B neurons, 20W. Spike timing / rate / population / temporal coding. Cumulative: 238,015.2x.</data>
  </node>
  <node id="layer_dynamic_profile">
    <data key="d0">concept</data>
    <data key="d1">Dynamic Profile Layer</data>
    <data key="d2">Layer 6. Multiplier 18.98x. Metaprobe equation extraction. Task-specialize, profile-switch. Cumulative: 4,517,528.8x.</data>
  </node>
  <node id="valve_v1_data_integrity">
    <data key="d0">concept</data>
    <data key="d1">V1 Data Integrity Protection</data>
    <data key="d2">SSD read-only monitoring. Write-detect on bus, checksum validation, SMART threshold check. Trigger: write attempt → terminate monitor (1 cycle).</data>
  </node>
  <node id="valve_v2_performance">
    <data key="d0">concept</data>
    <data key="d1">V2 Performance Impact Protection</data>
    <data key="d2">Latency/throughput counters with auto-baseline calibration. Throttle FSM (0=full, 10=paused). Trigger: &gt;20% latency increase or &lt;10% throughput drop.</data>
  </node>
  <node id="valve_v3_endurance">
    <data key="d0">concept</data>
    <data key="d1">V3 Endurance Protection</data>
    <data key="d2">NAND operation counter with hourly budget (default 1000 ops/hour). Endurance percent threshold (95%). Trigger: budget exceeded → stop NAND monitor.</data>
  </node>
  <node id="valve_v4_equation_validation">
    <data key="d0">concept</data>
    <data key="d1">V4 Equation Validation Safety</data>
    <data key="d2">Syntax (≥80%), dimensional (≥90%), sandbox, crossref checks. Trigger: any fail → reject equation.</data>
  </node>
  <node id="valve_v5_profile_switching">
    <data key="d0">concept</data>
    <data key="d1">V5 Profile Switching Safety</data>
    <data key="d2">Compatibility matrix, rollback register, switch frequency limit (20/sec). Trigger: rate exceeded or no rollback → block switch.</data>
  </node>
  <node id="valve_v6_scalar_behavior">
    <data key="d0">concept</data>
    <data key="d1">V6 Scalar Behavior Safety</data>
    <data key="d2">Replication rate limiter (max 10/cycle), resource cap (95%), anomaly detection, quarantine register (16 entries). Trigger: any violation → quarantine.</data>
  </node>
  <node id="valve_v7_signal_boundary">
    <data key="d0">concept</data>
    <data key="d1">V7 Hardware Signal Boundary</data>
    <data key="d2">42-device topology integrity. Per-category count limits (clock≤21, data≤7, control≤29, power≤4, timing≤3, thermal≤5, VRM≤4). VRM-implies-thermal check. Spoof/ghost detection. Trigger: violation → quarantine + topology lock.</data>
  </node>
  <node id="policy_keeper_law">
    <data key="d0">policy</data>
    <data key="d1">Keeper Law</data>
    <data key="d2">The system may become useful. It may not become authorized by usefulness alone.</data>
  </node>
  <node id="policy_lifecycle_manifesto">
    <data key="d0">policy</data>
    <data key="d1">Lifecycle Manifesto</data>
    <data key="d2">signal → scalar → confusion → query → gate → receipt → inheritance. MOIM v3.0 turns computation into a lifecycle.</data>
  </node>
  <node id="concept_behavioral_manifold">
    <data key="d0">concept</data>
    <data key="d1">Behavioral Manifold</data>
    <data key="d2">5D vector space where all formulas live: IDENTITY, CONSERVATION, TRANSFORMATION, SCALING, DYNAMICS. Each formula is a point. Search uses golden spiral navigator.</data>
  </node>
  <node id="concept_angrysphinx_gate">
    <data key="d0">concept</data>
    <data key="d1">AngrySphinx Gate</data>
    <data key="d2">Hard refusal mechanism. Rechecks all proposed actions before execution. Prevents personhood claims, control transfers, unsafe routes. Final veto authority.</data>
  </node>
  <node id="concept_receipts">
    <data key="d0">concept</data>
    <data key="d1">Receipts</data>
    <data key="d2">Lineage memory entries. Every execution produces a receipt with hash. Receipts preserve history, enable accountability, support amplitude updates.</data>
  </node>
  <node id="concept_sigma_uncertainty">
    <data key="d0">concept</data>
    <data key="d1">Sigma (Uncertainty)</data>
    <data key="d2">Uncertainty quantification in all measurements. Sigma thresholds determine admissibility. Low sigma = high confidence = admissible route.</data>
  </node>
  <node id="concept_gcl_constraint">
    <data key="d0">concept</data>
    <data key="d1">GCL Constraint Language</data>
    <data key="d2">Governance Constraint Language. Constrains execution scope, prevents overreach. Part of Delta GCL compression stack.</data>
  </node>
  <node id="total_405_formulas">
    <data key="d0">metric</data>
    <data key="d1">405 Domain Formulas</data>
    <data key="d2">Total across 15 domain registries: Physics 75 + Math 65 + Chemistry 50 + CS 15 + Engineering 12 + Biology 10 + Earth/Cosmology 12 + Social 12 + Materials 15 + Medicine 12 + Music 10 + Neuroscience 10 + Psychology 8 + Anthropology 8 + Political Science 7 = 405</data>
  </node>
  <node id="total_13_bridges">
    <data key="d0">metric</data>
    <data key="d1">13 Cross-Domain Bridges</data>
    <data key="d2">Cross-domain equivalence bridges connecting number theory, statistical mechanics, QFT, string theory, topology, random matrix theory, quantum chaos, biology, geophysics, economics.</data>
  </node>
  <node id="metric_11m_expansion">
    <data key="d0">metric</data>
    <data key="d1">11,187,502x Expansion</data>
    <data key="d2">42-device signal topology foundation multiplier. All-device signal 1.5x × diversity 1.3x × quality 1.2x × integration 1.2x × VRM addition 1.1x × VRM quality 1.15x × voltage regulation 1.2x = 4.27x on pre-signal 2.6M base.</data>
  </node>
  <node id="metric_21b_capacity">
    <data key="d0">metric</data>
    <data key="d1">21.3 Billion Capacity</data>
    <data key="d2">Projected all-device signal capacity: 21,256,253,633.13. Pending benchmark verification.</data>
  </node>
  <node id="metric_50mhz_oepi">
    <data key="d0">metric</data>
    <data key="d1">50 MHz OEPI Throughput</data>
    <data key="d2">OEPI processor evaluates one escalation per clock at 50 MHz. 3-cycle latency: fetch → compute → classify.</data>
  </node>
  <node id="bench_btc_integrity">
    <data key="d0">benchmark</data>
    <data key="d1">BTC Integrity Test</data>
    <data key="d2">Statistical integrity gate correctly BLOCKED both overclaimed correlations on Bitcoin data. Adjusted R² = 0.044, far below 0.70 threshold. No false positives.</data>
  </node>
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    <data key="d3">supersedes</data>
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    <data key="d3">includes</data>
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