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Resonant Fractal Nature Theory — a mathematical framework for coherent patterns on graph-coupled networks.

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© 2026 TNFR project — MIT licensed.DOI 10.5281/zenodo.17602860
docs
grammar
PHYSICS_VERIFICATION.md
API_CONTRACTS.mdCANONICAL_OZ_SEQUENCES.mdEMPIRICAL_CONFRONTATION_EEG.mdREADME.mdSTRUCTURAL_FIELDS_TETRAD.mdSTRUCTURAL_INTERFACE_THEORY.md
theory
APPLIED_STRUCTURAL_ANALYSIS.mdCATALOG_TYPE_HYGIENE_PROGRAMME.mdDISSIPATIVE_AND_OPEN_SYSTEMS.mdEMERGENT_ONTOLOGY.mdEXTENDED_FIELDS_AND_DERIVED_QUANTITIES.mdFUNDAMENTAL_THEORY.mdGAUGE_SYMMETRY_AND_UNIFICATION.mdGLOSSARY.mdMATHEMATICAL_DYNAMICS_BASIS.mdMINIMAL_STRUCTURAL_DEGREES.mdNUCLEUS_A_PRIME_LADDER_ATLAS.mdNUCLEUS_B_EQUIVARIANCE_OBSTRUCTIONS.mdPHYSICAL_REGIME_CORRESPONDENCES.mdREADME.mdREMESH_INFINITY_DERIVATION.mdSTRUCTURAL_CONSERVATION_THEOREM.mdSTRUCTURAL_OPERATORS.mdSTRUCTURAL_STABILITY_AND_DYNAMICS.mdTNFR_BSD_RESEARCH_NOTES.mdTNFR_HODGE_RESEARCH_NOTES.mdTNFR_NAVIER_STOKES_RESEARCH_NOTES.mdTNFR_NUMBER_THEORY.mdTNFR_P_VS_NP_RESEARCH_NOTES.mdTNFR_RIEMANN_RESEARCH_NOTES.mdTNFR_VARIATIONAL_PRINCIPLE.mdTNFR_YANG_MILLS_RESEARCH_NOTES.mdTNFR.pdfUNIFIED_GRAMMAR_RULES.md
factorization-lab
analysis
analyze_patterns.pycertificate_manifest.py
benchmarks
benchmark_analysis.pybenchmark_expansion_suite.pyfull_spectrum_factorization.pypaley_gap_extended.pypaley_gap_smoke.pytest_benchmark_suite.py
demos
experiment_contexts
exp_0b1663cd19b7.jsonexp_0bf0054b7474.jsonexp_75a4c8ca616a.jsonexp_848ee0fd1857.jsonexp_f6fe00562193.jsonexp_fdf3da424e1e.json
failure_telemetry_batch.pyfeedback_integration_demo.pyintegration_demo_snapshots.dbseed_management_integration_demo.pysnapshot_integration_demo.pytrajectory_143.jsontrajectory_77.jsontrajectory_89.jsontrajectory_91.jsontrajectory_97.json
docs
FACTORING_PLAYBOOK.mdFALSE_POSITIVE_TEST_SUITE.mdOPERATOR_CERTIFICATES.mdROADMAP.mdSPECTRAL_ROUTE.md
experiment_contexts
exp_cebe1d9e7d8e.json
notebooks
spectral_history.ipynb
scripts
run_false_positive_tests.py
tests
run_false_positive_test_suite.pytest_cli.pytest_false_positive_methodology.pytest_false_positive_verifier.pytest_feedback_integration.pytest_partitioning.pytest_seed_management.pytest_self_opt_support.pytest_snapshot_system.pytest_spectral_paley.pytest_verification_robustness.py
tnfr_factorization
__init__.pyapi.pycli.pyfailure_telemetry.pyfeedback_adapter.pyfeedback_integration.pypartitioning.pyself_opt_support.pyspectral_paley.py
demo_snapshots.dbLICENSE_SNAPSHOT.mdPACKAGE_SUMMARY.mdREADME.mdseed_management.pysnapshot_system.pytest_certificate_hashing.pytest_installation.pyverification_trajectory_77.json
benchmarks
analyze_tetrad_universality.pyb0star_alpha_canonical_product_graphs.pybenchmark_optimization_tracks.pybenchmark_utils.pyboundary_vibration.pybridge_primes_riemann.pychiral_involution.pycli_utils.pycoherence_projector_sense_index.pycommutant_bridge.pycomposition_arithmetic.pyconfinement_zones_test.pyconservation_law_validation.pydirected_paley_bridge.pyemergent_arithmetic_pulse.pyemergent_atom_dynamics.pyemergent_atomic_shells.pyemergent_base_dimension.pyemergent_dimension_dynamics.pyemergent_fractal_pulse.pyemergent_fractal_simplex_dimension.pyemergent_integers_symmetry.pyemergent_musical_nfr.pyemergent_nfr_geometry.pyemergent_nfr_where.pyemergent_rationals.pyemergent_rhythm.pyemergent_screening.pyemergent_shell_cardinals.pyemergent_shell_ordering.pyemergent_simplex_dimension.pyemergent_substrate_symmetry.pyequivariance_wall.pyexternal_phase_gate_validation.pyfield_methods_battery.pygolden_residue_remesh_bridge.pyintegrated_force_regime_study.pyinverse_spectrum_to_symmetry.pyk_phi_safety_demo.pykuramoto_farey_bridge.pymissing_piece_bridge.pymultichannel_interface_benchmark.pynavier_stokes_recipe_bridge.pynodal_propagator_residue_bridge.pyns_moment_hierarchy_cascade.pyoperational_irreducibility.pypaley_bridge.pyphase_curvature_investigation.pyphase_wall.pyphi_s_confinement_investigation.pyprimes_as_consequence.pypulse_phase_coherence_budget.pyREADME.mdremesh_infinity_riemann_baseline.pyremesh_infinity_riemann_composed.pyremesh_infinity_riemann_modified_graph.pyremesh_infinity_riemann_operator.pyremesh_infinity_riemann_spectral_basis.pyremesh_infinity_riemann_spectral_robustness.pyremesh_infinity_riemann_spectral.pyresidue_phase_vs_riemann.pystructural_interface_benchmark.pytemporal_interface_benchmark.pytetrad_results_aggregate.pyu2_destabilization_irreversibility.pyuniversality_clusters.pyxi_c_fast_experiment.py
primality-test
benchmarks
comprehensive_benchmark.py
docs
ADVANCED_INTEGRATION.mdmathematical_foundation.mdperformance_analysis.md
examples
advanced_examples.pybasic_usage.py
tnfr_primality
__init__.py__main__.pyadvanced_cli.pyadvanced_core.pycli.pyconstants.pycore.pyoptimized.py
MANIFEST.inPACKAGE_SUMMARY.mdREADME.mdRELEASE_NOTES_v1.0.mdsetup.pytest_installation.py
tests
core_physics
__init__.pytest_conservation_laws.pytest_delta_nfr_computation_paths.pytest_delta_nfr.pytest_dispersion_coherence_sign_invariance.pytest_emergent_constants_guard.pytest_lyapunov_operators.pytest_nodal_equation.pytest_structural_triad.py
data
replay_manifests
sample_run
_manifest_summary.json_manifest.json_partition_files.txt.gz
self_opt_validation
seed_alpha
paley.json
seed_beta
integration.json
seed_gamma
unknown.json
self_optimization
test_run
partitioned
test_run
test_run_p0.jsontest_run_p1.json
_manifest_summary.json_manifest.json
engines
test_pattern_discovery_manifest.pytest_self_optimization_engine.py
mathematics
__init__.pytest_autodiff.pytest_backends.pytest_dissipative_dynamics.pytest_epi.pytest_factory_patterns.pytest_metrics.pytest_navier_stokes_refounded.pytest_number_theory_canonical.pytest_operators.pytest_residue_networks.pytest_riemann_nodal_pulse.pytest_riemann_pulse_coherence.pytest_spaces.pytest_transforms.pytest_validator.py
operators
test_canonical_operators_modern.pytest_grammar_canon.pytest_grammar_canonical_consistency.pytest_grammar_dynamics.pytest_operator_contracts.pytest_operator_strategies.py
parallel
test_fractal_partition_manifest.py
physics
test_conservation_gauge_unification.pytest_dissipative_conservation.pytest_emergent_chemistry.pytest_field_cache_invalidation.pytest_gauge.pytest_phase_transition.pytest_signatures.pytest_spectral_conservation.pytest_structural_diffusion.pytest_structural_integrity.pytest_symplectic_substrate.pytest_tetrad_bounds.pytest_variational.pytest_yang_mills_closure.pytest_yang_mills_derivability.pytest_yang_mills_scaling.pytest_yang_mills_structural_gap.pytest_yang_mills_u6_sweep.py
scripts
test_run_self_opt_validation.pytest_run_self_optimization.py
sdk
__init__.pytest_simple_advanced.py
__init__.pyconftest.pyREADME.mdtest_breast_cancer_phase_gate_demo.pytest_classical_mechanics.pytest_distributed_fft.pytest_external_phase_gate_validation.pytest_factorization_entrypoint.pytest_multichannel_interface.pytest_nodal_optimizer.pytest_phase_gate_api.pytest_replay_register_manifest.pytest_signal_confrontation.pytest_structural_interface_api.pytest_structural_interface_baselines.pytest_structural_interface_benchmark.pytest_temporal_interface.pytest_vectorized_coherence_length_regression.pytest_wine_quality_phase_gate_demo.pyutils.py
examples
01_foundations
01_hello_world.py02_musical_resonance.py03_network_formation.py04_operator_sequences.py05_coherence_evolution.py06_network_topologies.py07_phase_transitions.py08_emergent_phenomena.py09_visualization_suite.py10_simplified_sdk_showcase.py
02_physics_regimes
11_classical_limit_comparison.py115_operator_contract_audit.py12_classical_mechanics_demo.py13_quantum_mechanics_demo.py14_uncertainty_and_interference.py15_train_crossing_demo.py17_conservation_law_demo.py26_gauge_structure_demo.py27_variational_principle_demo.py28_dissipative_systems_demo.py29_lyapunov_stability_demo.py30_self_optimization_demo.py31_mathematical_constants_basis.py33_complex_field_unification.py34_conservation_protocol_suite.py35_tetrad_irreducibility.py36_grammar_violation_detector.py37_operator_tetrad_synergy.py38_grammar_energy_landscape.py39_nodal_equation_decomposition.py
03_riemann_zeta
157_nodal_pulse_phase_attack.py41_von_mangoldt_zeta_demo.py42_riemann_zeros_as_resonances.py43_prime_ladder_hamiltonian_demo.py44_weil_explicit_formula_demo.py45_li_keiper_demo.py46_weil_tnfr_positivity_demo.py47_alpha_sweep_demo.py48_admissible_family_sweep_demo.py49_nodeaware_gauge_sweep_demo.py50_uniform_coercivity_demo.py51_adaptive_coercivity_demo.py52_paley_gap_coercivity_demo.py53_lyapunov_spectral_positivity_demo.py54_hilbert_polya_demo.py55_structural_zero_density_demo.py56_spectral_emergence_demo.py57_admissible_rescaling_demo.py58_oscillatory_correction_demo.py
04_riemann_L_twisted
59_dirichlet_l_function_demo.py60_dirichlet_l_continuation_demo.py61_dirichlet_l_hamiltonian_demo.py62_dirichlet_weil_explicit_formula_demo.py63_dirichlet_li_keiper_demo.py64_twisted_weil_positivity_demo.py65_twisted_alpha_sweep_demo.py66_twisted_admissible_family_sweep_demo.py67_twisted_nodeaware_gauge_sweep_demo.py68_twisted_hermite_family_demo.py69_twisted_coercivity_uniform_demo.py70_twisted_paley_gap_coercivity_demo.py71_twisted_lyapunov_spectral_demo.py72_twisted_hilbert_polya_demo.py73_twisted_structural_zero_density_demo.py74_twisted_spectral_emergence_demo.py75_twisted_admissible_rescaling_demo.py76_twisted_oscillatory_correction_demo.py
05_type_hygiene
77_remesh_infinity_residue_split_demo.py78_nuf_type_signature_demo.py79_epi_type_signature_demo.py80_phi_type_signature_demo.py81_dnfr_type_signature_demo.py82_remesh_window_type_signature_demo.py83_delta_phi_max_type_signature_demo.py84_coupling_weights_type_signature_demo.py85_tetrad_closure_signature_demo.py86_currents_closure_signature_demo.py87_aggregates_closure_signature_demo.py88_urules_consistency_signature_demo.py89_operator_catalog_discipline_signature_demo.py
06_navier_stokes
158_navier_stokes_two_face_refounded.py
07_number_theory
100_prime_families_orbits.py101_numbers_as_coupled_network.py102_nodal_flow_primes_equilibria.py116_nuf_emergent_prime_visibility.py146_primality_grammatical_inertness.py147_numbers_as_free_monoid_words.py148_capacity_arm_carries_von_mangoldt.py149_p14_is_the_capacity_arm_operator.py153_structural_frequency_rank_cyclotomy.py40_arithmetic_number_theory.py94_generative_number_construction.py95_primes_from_spectral_waves.py96_spectral_vibration_of_coherence.py97_goldbach_additive_multiplicative.pyemergent_chemistry_particles_demo.py
08_emergent_geometry
103_emergent_substrate_meets_riemann.py106_per_node_polarization_geometry.py107_orthogonal_structure_emergent_geometry.py108_emergent_field_generating_structure.py112_structure_predicts_coherence_flow.py113_overdamped_projection_bridge.py114_substrate_conserved_quantities.py117_emergent_geometry_residue_graph.py118_emergent_vs_classical_operator.py119_phase_sector_directed_residue.py120_symmetry_wall_substrate_vs_spectrum.py121_canonical_symmetry_break_negative.py122_factorization_phase_sector.py123_symmetry_sector_decomposition.py124_emergent_metric_fractal_consistency.py125_node_is_the_emergent_substrate.py126_two_layers_base_fiber.py127_base_is_emergent_not_imposed.py128_base_substrate_coemergence.py129_spectral_gap_base_fiber_clock.py130_operators_break_substrate_charges.py131_coemergent_loop_convergence.py132_geometric_phase_holonomy.py133_psi_topological_defects.py134_spectral_dimension_heat_kernel.py135_arrow_of_time_h_theorem.py136_heat_kernel_coefficients.py137_synchronization_transition.py138_structure_frequency_synchronization.py139_grammar_formal_language.py140_grammar_automaton.py141_grammar_rule_decomposition.py142_grammar_operator_quotient.py143_glyphic_function_sublanguage.py144_branching_combinator.py145_syntactic_monoid_starfree.py150_emergent_grammatical_pattern_parry.py151_grammar_in_emergent_geometry.py152_operator_contract_tetrahedron.py154_conductor_annotated_qr_spectrum.py155_ontological_position_of_numbers.py156_emergence_directness_law.py98_emergent_symplectic_substrate.py99_structural_diffusion.pyunified_fields_showcase.py
09_millennium
109_p_vs_np_coherence_synthesis.py110_bsd_rank_structural_pressure.py111_hodge_discrete_and_honest_gap.py
10_applications
159_empirical_confrontation_pipeline.py90_phase_gate_monitor_demo.py91_breast_cancer_phase_gate_demo.py92_wine_quality_phase_gate_demo.py93_structural_interface_demo.pypytorch_cuda_demo.py
README.md
scripts
replay
__init__.pyregister_manifest.py
__init__.pyREADME.mdrebuild_failure_manifest.pyrun_reproducible_benchmarks.pyrun_self_opt_validation.pyrun_self_optimization.pytnfr_is_prime.pyvalidate_conservation_law.pyverify_internal_references.py
src
core
__init__.pyevaluation.py
tnfr
backends
__init__.pyjax_backend.pynumpy_backend.pyoptimized_numpy.pyREADME.mdtorch_backend.py
cli
__init__.py__init__.pyiarguments.pyarguments.pyiexecution.pyexecution.pyiinteractive_validator.pyREADME.mdutils.pyutils.pyi
compat
__init__.pydataclass.pyjsonschema_stub.pymatplotlib_stub.pynumpy_stub.pyREADME.md
config
__init__.py__init__.pyiconstants.pyconstants.pyidefaults_core.pydefaults_init.pydefaults_metric.pydefaults.pyfeature_flags.pyfeature_flags.pyiglyph_constants.pyoperator_names.pyoperator_names.pyiphysics_derivation.pyprecision_modes.pypresets.pypresets.pyiREADME.mdsecurity.pythresholds.pytnfr_config.py
constants
__init__.py__init__.pyialiases.pyaliases.pyicanonical.pymetric.pymetric.pyioperational.py
core
__init__.pycontainer.pydefault_implementations.pyexceptions.pyinterfaces.pyREADME.md
dynamics
__init__.py__init__.pyiadaptation.pyadaptation.pyiadaptive_sequences.pyadaptive_sequences.pyiadelic.pyadvanced_cache_optimizer.pyadvanced_fft_arithmetic.pyaliases.pyaliases.pyibifurcation.pycache_aware_fft_engine.pycanonical.pycanonical.pyicomputational_hub.pycoordination.pycoordination.pyidistributed_fft.pydnfr.pydnfr.pyidynamic_limits.pyemergent_centralization.pyemergent_integration_engine.pyfeedback.pyfeedback.pyifft_backend.pyfft_cache_coordinator.pyfft_dispatchers.pyfft_engine.pyfft_workers.pyfused_dnfr.pyhomeostasis.pyhomeostasis.pyiintegrators.pyintegrators.pyilearning.pylearning.pyimetabolism.pymulti_modal_cache.pynbody_tnfr.pynbody.pynodal_optimizer.pyoptimization_orchestrator.pypropagation.pyREADME.mdruntime.pyruntime.pyisampling.pysampling.pyiselectors.pyselectors.pyiself_optimizing_engine.pyspectral_structural_fusion.pystructural_cache.pystructural_clip.pysymplectic.pyunified_backend.pyunified_mathematical_cache_orchestrator.py
engines
computation
__init__.pyfft_engine.pyunified_fft_engine.pyunified_gpu_system.py
constants
__init__.pycanonical.pyoperational.py
integration
__init__.pyemergent_integration.py
pattern_discovery
__init__.pymathematical_patterns.pymulti_modal_cache.py
self_optimization
__init__.pyengine.py
__init__.pyREADME.md
errors
__init__.pycontextual.py
factorization
__init__.py
flatten
README.md
gamma
README.md
glyph_history
README.md
glyph_runtime
README.md
immutable
README.md
initialization
README.md
io
README.md
math
__init__.pyfields_symbolic.pygrammar_validators.pyoptimizer.pyREADME.mdsymbolic.py
mathematics
__init__.pybackend.pybackend.pyidynamics.pydynamics.pyiepi.pyepi.pyigenerators.pygenerators.pyiliouville.pymetrics.pymetrics.pyinumber_theory.pyoperators_factory.pyoperators_factory.pyioperators.pyoperators.pyioptimized_primality.pyprojection.pyprojection.pyiREADME.mdruntime.pyruntime.pyispaces.pyspaces.pyispectral.pytransforms.pytransforms.pyiunified_cache.pyunified_numerical.pyzeta.py
metrics
__init__.py__init__.pyibuffer_cache.pybuffer_cache.pyicache_utils.pycoherence.pycoherence.pyicommon.pycommon.pyicore.pycore.pyidiagnosis.pydiagnosis.pyiemergence.pyexport.pyexport.pyiglyph_timing.pyglyph_timing.pyilearning_metrics.pylearning_metrics.pyilocal_coherence.pyphase_coherence.pyphase_compatibility.pyREADME.mdreporting.pyreporting.pyisense_index.pysense_index.pyitelemetry.pytetrad.pytrig_cache.pytrig_cache.pyitrig.pytrig.pyi
multiscale
__init__.pyhierarchical.pyREADME.md
navier_stokes
__init__.pyconservative_face.pyoperator.py
node
README.md
observers
README.md
operators
network_analysis
__init__.pysource_detection.py
postconditions
__init__.pymutation.py
preconditions
__init__.pycoherence.pydissonance.pyemission.pymutation.pyreception.pyresonance.py
strategies
__init__.pydefaults.pygpu_strategies.pystrategy.py
__init__.py__init__.pyialgebra.pycanonical_patterns.pycascade.pycoherence.pycontraction.pycoupling.pycycle_detection.pydefinitions_base.pydefinitions.pydefinitions.pyidissonance.pyemission.pyexpansion.pygrammar_application.pygrammar_canon.pygrammar_context.pygrammar_core.pygrammar_dynamics.pygrammar_error_factory.pygrammar_memoization.pygrammar_patterns.pygrammar_telemetry.pygrammar_types.pygrammar_u6.pygrammar_validate.pygrammar.pygrammar.pyihamiltonian.pyhealth_analyzer.pyintrospection.pyjitter.pyjitter.pyilifecycle.pymetabolism.pymetrics_basic.pymetrics_core.pymetrics_network.pymetrics_structural.pymetrics_u6.pymetrics.pymutation.pynodal_equation.pyoperator_contracts.pypattern_detection.pypatterns.pyREADME.mdreception.pyrecursivity.pyregistry.pyregistry.pyiremesh.pyremesh.pyiresonance.pyself_organization.pysilence.pystructural_units.pytransition.py
parallel
__init__.pyauto_scaler.pydistributed.pyengine.pymonitoring.pypartitioner.pyREADME.md
performance
guardrails.py
physics
__init__.py_helpers.pycalibration.pycanonical.pycell.pyclassical_mechanics.pyconservation_gauge_unification.pyconservation.pydissipative_conservation.pyemergent_chemistry.pyemergent_particles.pyextended.pyfields.pygauge.pyintegrity.pyinteractions.pylife.pylyapunov.pypatterns.pyphase_transition.pyquantum_mechanics.pyREADME.mdsignatures.pyspectral_conservation.pyspectral_metrics.pystructural_diffusion.pysymplectic_substrate.pytelemetry.pyunified.pyvariational.pyvectorized_ops.py
primality
__init__.py
recipes
__init__.pycookbook.pyREADME.md
riemann
__init__.pyadmissible_family_sweep.pyadmissible_rescaling.pyaggregates_closure_signature.pyalpha_sweep.pyanalytic_continuation_dirichlet.pyanalytic_continuation.pycoercivity_uniform.pycoupling_weights_type_signature.pycurrents_closure_signature.pydelta_phi_max_type_signature.pydirichlet_l.pydnfr_type_signature.pyepi_type_signature.pyhilbert_polya.pyli_keiper.pylyapunov_spectral_positivity.pynodal_pulse.pynodeaware_gauge_sweep.pynuf_type_signature.pyoperator_catalog_discipline_signature.pyoperator.pyoscillatory_correction.pypaley_gap_coercivity.pyphi_type_signature.pyprime_ladder_hamiltonian.pypulse_coherence.pyremesh_infinity_residue_split.pyremesh_window_type_signature.pyspectral_emergence.pystructural_zero_density.pytelemetry.pytetrad_closure_signature.pytwisted_admissible_family_sweep.pytwisted_admissible_rescaling.pytwisted_alpha_sweep.pytwisted_coercivity_uniform.pytwisted_hermite_family.pytwisted_hilbert_polya.pytwisted_li_keiper.pytwisted_lyapunov_spectral_positivity.pytwisted_nodeaware_gauge_sweep.pytwisted_oscillatory_correction.pytwisted_paley_gap_coercivity.pytwisted_prime_ladder_hamiltonian.pytwisted_spectral_emergence.pytwisted_structural_zero_density.pytwisted_weil_explicit_formula.pytwisted_weil_positivity.pyurules_consistency_signature.pyvon_mangoldt.pyweil_explicit_formula.pyweil_positivity.py
schemas
__init__.pygrammar.jsonREADME.md
sdk
__init__.py__init__.pyiadaptive_system.pyadaptive_system.pyibuilders.pybuilders.pyifluent.pyfluent.pyiREADME.mdself_opt.pysimple.pytemplates.pytemplates.pyiutils.py
security
__init__.pycrypto.pydatabase.pyREADME.mdsubprocess.pyvalidation.py
sequencing
__init__.pypatterns.pyREADME.md
services
__init__.pyorchestrator.pyREADME.md
sparse
__init__.pyREADME.mdrepresentations.py
structural
README.md
telemetry
__init__.pycache_metrics.pycache_metrics.pyiconstants.pynu_f.pynu_f.pyiREADME.mdunified_telemetry_system.pyverbosity.pyverbosity.pyi
tools
__init__.pydomain_templates.pyREADME.mdsequence_generator.pytnfr_is_prime_cli_optimized.pytnfr_is_prime_cli.py
topology
__init__.pyasymmetry.pyREADME.md
utils
cache_layers.pycache.pycache.pyicallbacks.pycallbacks.pyichunks.pychunks.pyidata.pydata.pyifast_diameter.pygraph.pygraph.pyiinit.pyinit.pyiio.pyio.pyinumeric.pynumeric.pyiREADME.mdtopology.pyunified_cache.py
validation
__init__.py__init__.pyiaggregator.pybase.pycompatibility.pycompatibility.pyiconfig.pygraph.pygraph.pyihealth.pyinput_validation.pyinterface_baselines.pyinvariants.pymultichannel_interface.pyphase_gate.pyREADME.mdrules.pyrules.pyiruntime.pyruntime.pyisequence_validator.pysignal_confrontation.pysoft_filters.pysoft_filters.pyispectral.pyspectral.pyistructural_interface.pytemporal_interface.pyunified_validation_system.pyvalidator.pywindow.pywindow.pyi
visualization
__init__.pycascade_viz.pyhierarchy.pyREADME.mdsequence_plotter.py
yang_mills
__init__.pyclosure.pyderivability.pyscaling.pystructural_gap.pyu6_sweep.py
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tetrad_evaluator.py
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FILE: examples/07_number_theory/146_primality_grammatical_inertness.py

146_primality_grammatical_inertness.py

Example 146 — Primality as Grammatical Inertness: the Dual-Lever and the U2 Convergence Target Read on the Arithmetic Nodes

This bridges two threads that had never been connected: the operator-GRAMMAR thread (examples 139-145, which characterized the unified grammar U1-U6 as a formal language, its automaton, its dual-lever role classes, and its star-free syntactic monoid) and the NUMBER-THEORY thread (examples 40, 100-102, which established primality as the structural equilibrium ΔNFR = 0). The user's intuition is that the dynamics implied by the grammar is a lens onto the other modules; here that lens falls on primality.

The single bridge is the nodal equation itself

Every operator ("word" in the grammar) acts on form through ONE rule:

text
∂EPI/∂t = νf · ΔNFR

The dual-lever (examples 37, 130): each operator acts via the CAPACITY lever νf (how fast the node reorganizes) or the PRESSURE lever ΔNFR (the structural forcing). On an arithmetic node the pressure is the canonical primality field (TNFR_NUMBER_THEORY.md §4):

text
ΔNFR(n) = ζ·(Ω−1) + η·(τ−2) + θ·(σ/n − (1+1/n)),   n prime ⟺ ΔNFR(n)=0

with Ω = number of prime factors with multiplicity, τ = divisor count, σ = divisor sum, and ζ=φ·γ, η=(γ/φ)·π, θ=1/φ the canonical arithmetic constants.

The consequence is exact: since every word acts through νf·ΔNFR, and ΔNFR=0 at primes, NO valid grammatical program can move a prime's form. A prime is structurally INERT — it is the fixed point of the entire grammar's action on arithmetic nodes. Primality is grammatical inertness.

Doctrine compliance

The arithmetic ΔNFR is the canonical per-node primality field (ArithmeticTNFRFormalism), NOT the graph-diffusion Laplacian, so the bridge is read at the NODAL-EQUATION level (nodal flow EPI += dt·νf·ΔNFR), exactly as example 102 established. Nothing is imposed; the dual-lever factorization and the U2 coherence target are measured against the canonical formalism.

Three measured results

M1 ONE EQUILIBRIUM, THREE READINGS. n is prime ⟺ ΔNFR(n) = 0 (the §4 theorem) ⟺ the local coherence C(n) = 1/(1+|ΔNFR|) equals 1 (maximal). The primes are exactly the maximal-coherence, zero-pressure nodes (verified, 0 mismatches).

M2 THE CAPACITY LEVER — PRIMES ARE THE GRAMMATICAL KERNEL. Under the nodal flow EPI += dt·νf·ΔNFR, every prime is FROZEN for every νf (12/12 at νf ∈ {0.5,1,2}); a composite drifts, and its drift FACTORS exactly as (νf gain) × (arithmetic pressure) — doubling νf doubles the drift exactly (27/27). The capacity lever scales the RATE but can never move a prime: the primes are the kernel of the whole νf-lever sub-grammar.

M3 THE U2 PRESSURE AXIS — THE GRAMMAR'S CONVERGENCE TARGET IS PRIMALITY. U2 (convergence/boundedness) drives ΔNFR → 0; in coherence terms C → 1. The maximal-coherence target C=1 is EXACTLY primality, and C decreases monotonically with Ω (mean C: prime 1.000, Ω=2 0.239, Ω=3 0.130, Ω=4 0.089, Ω=5 0.085) — factorization complexity is structural coherence debt. A prime needs the EMPTY word (the identity of the star-free syntactic monoid, ex 145): it is already at the grammar's convergence target.

Honest scope

Primality ⟺ ΔNFR=0 is the existing §4 theorem; the NEW content is the GRAMMAR- LENS reading of it — primes as the dual-lever kernel (νf-lever-invariant set), the U2 convergence target ΔNFR→0 identified with primality, and the empty word / monoid identity as the program a prime needs. The arithmetic ΔNFR is a per-node function, so the canonical graph operators (which recompute ΔNFR from neighbours) are deliberately NOT used; the bridge lives at the nodal-equation level. This restates the primality theorem through the grammar dynamics; it is not new number theory and closes no open problem. It does deliver the user's thesis concretely: the grammar's dynamics is a lens that unifies the number-theory module with the operator grammar.

References

  • theory/TNFR_NUMBER_THEORY.md §4 (primality as ΔNFR=0, the canonical constants)
  • src/tnfr/mathematics/number_theory.py (ArithmeticTNFRFormalism)
  • examples/07_number_theory/102_nodal_flow_primes_equilibria.py (primes = equilibria)
  • examples/08_emergent_geometry/130_operators_break_substrate_charges.py (dual-lever)
  • examples/08_emergent_geometry/145_syntactic_monoid_starfree.py (the monoid identity)
  • AGENTS.md "Operator-Tetrad Synergies" (dual-lever), "Unified Grammar U2"

Source Code

python
#!/usr/bin/env python3
"""
Example 146 — Primality as Grammatical Inertness: the Dual-Lever and the U2
Convergence Target Read on the Arithmetic Nodes
==============================================================================

This bridges two threads that had never been connected: the operator-GRAMMAR
thread (examples 139-145, which characterized the unified grammar U1-U6 as a
formal language, its automaton, its dual-lever role classes, and its star-free
syntactic monoid) and the NUMBER-THEORY thread (examples 40, 100-102, which
established primality as the structural equilibrium ΔNFR = 0). The user's
intuition is that the dynamics implied by the grammar is a lens onto the other
modules; here that lens falls on primality.

The single bridge is the nodal equation itself
----------------------------------------------
Every operator ("word" in the grammar) acts on form through ONE rule:

    ∂EPI/∂t = νf · ΔNFR

The dual-lever (examples 37, 130): each operator acts via the CAPACITY lever νf
(how fast the node reorganizes) or the PRESSURE lever ΔNFR (the structural
forcing). On an arithmetic node the pressure is the canonical primality field
(TNFR_NUMBER_THEORY.md §4):

    ΔNFR(n) = ζ·(Ω−1) + η·(τ−2) + θ·(σ/n − (1+1/n)),   n prime ⟺ ΔNFR(n)=0

with Ω = number of prime factors with multiplicity, τ = divisor count, σ =
divisor sum, and ζ=φ·γ, η=(γ/φ)·π, θ=1/φ the canonical arithmetic constants.

The consequence is exact: since every word acts through νf·ΔNFR, and ΔNFR=0 at
primes, NO valid grammatical program can move a prime's form. A prime is
structurally INERT — it is the fixed point of the entire grammar's action on
arithmetic nodes. Primality is grammatical inertness.

Doctrine compliance
-------------------
The arithmetic ΔNFR is the canonical per-node primality field
(ArithmeticTNFRFormalism), NOT the graph-diffusion Laplacian, so the bridge is
read at the NODAL-EQUATION level (nodal flow EPI += dt·νf·ΔNFR), exactly as
example 102 established. Nothing is imposed; the dual-lever factorization and the
U2 coherence target are measured against the canonical formalism.

Three measured results
----------------------
M1 ONE EQUILIBRIUM, THREE READINGS. n is prime ⟺ ΔNFR(n) = 0 (the §4 theorem)
   ⟺ the local coherence C(n) = 1/(1+|ΔNFR|) equals 1 (maximal). The primes are
   exactly the maximal-coherence, zero-pressure nodes (verified, 0 mismatches).

M2 THE CAPACITY LEVER — PRIMES ARE THE GRAMMATICAL KERNEL. Under the nodal flow
   EPI += dt·νf·ΔNFR, every prime is FROZEN for every νf (12/12 at νf ∈
   {0.5,1,2}); a composite drifts, and its drift FACTORS exactly as (νf gain) ×
   (arithmetic pressure) — doubling νf doubles the drift exactly (27/27). The
   capacity lever scales the RATE but can never move a prime: the primes are the
   kernel of the whole νf-lever sub-grammar.

M3 THE U2 PRESSURE AXIS — THE GRAMMAR'S CONVERGENCE TARGET IS PRIMALITY. U2
   (convergence/boundedness) drives ΔNFR → 0; in coherence terms C → 1. The
   maximal-coherence target C=1 is EXACTLY primality, and C decreases
   monotonically with Ω (mean C: prime 1.000, Ω=2 0.239, Ω=3 0.130, Ω=4 0.089,
   Ω=5 0.085) — factorization complexity is structural coherence debt. A prime
   needs the EMPTY word (the identity of the star-free syntactic monoid, ex 145):
   it is already at the grammar's convergence target.

Honest scope
------------
Primality ⟺ ΔNFR=0 is the existing §4 theorem; the NEW content is the GRAMMAR-
LENS reading of it — primes as the dual-lever kernel (νf-lever-invariant set),
the U2 convergence target ΔNFR→0 identified with primality, and the empty word /
monoid identity as the program a prime needs. The arithmetic ΔNFR is a per-node
function, so the canonical graph operators (which recompute ΔNFR from neighbours)
are deliberately NOT used; the bridge lives at the nodal-equation level. This
restates the primality theorem through the grammar dynamics; it is not new number
theory and closes no open problem. It does deliver the user's thesis concretely:
the grammar's dynamics is a lens that unifies the number-theory module with the
operator grammar.

References
----------
- theory/TNFR_NUMBER_THEORY.md §4 (primality as ΔNFR=0, the canonical constants)
- src/tnfr/mathematics/number_theory.py (ArithmeticTNFRFormalism)
- examples/07_number_theory/102_nodal_flow_primes_equilibria.py (primes = equilibria)
- examples/08_emergent_geometry/130_operators_break_substrate_charges.py (dual-lever)
- examples/08_emergent_geometry/145_syntactic_monoid_starfree.py (the monoid identity)
- AGENTS.md "Operator-Tetrad Synergies" (dual-lever), "Unified Grammar U2"
"""

import os
import statistics
import sys

sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", "src"))

import sympy as sp

from tnfr.mathematics.number_theory import (
    ArithmeticStructuralTerms,
    ArithmeticTNFRFormalism,
    ArithmeticTNFRParameters,
)

PARAMS = ArithmeticTNFRParameters()
F = ArithmeticTNFRFormalism


def arithmetic_terms(n):
    """Canonical structural terms (Omega with multiplicity, tau, sigma)."""
    factorisation = sp.factorint(n)
    big_omega = int(sum(factorisation.values()))  # prime factors w/ multiplicity
    tau = int(sp.divisor_count(n))
    sigma = int(sp.divisor_sigma(n))
    return ArithmeticStructuralTerms(tau=tau, sigma=sigma, omega=big_omega)


def delta_nfr(n):
    return F.delta_nfr_value(n, arithmetic_terms(n), PARAMS)


def experiment_1_three_readings(limit=60):
    print("=" * 72)
    print("M1: one equilibrium, three readings -- prime <=> dNFR=0 <=> C=1")
    print("=" * 72)
    primes = [n for n in range(2, limit + 1) if sp.isprime(n)]
    zero_pressure = []
    max_coherence = []
    for n in range(2, limit + 1):
        d = delta_nfr(n)
        c = F.local_coherence(d)
        if abs(d) <= 1e-12:
            zero_pressure.append(n)
        if abs(c - 1.0) <= 1e-12:
            max_coherence.append(n)
    print(f"  primes in [2,{limit}]:           {len(primes)}")
    print(
        f"  zero-pressure nodes (dNFR=0):   {len(zero_pressure)}  "
        f"== primes: {zero_pressure == primes}"
    )
    print(
        f"  maximal-coherence nodes (C=1):  {len(max_coherence)}  "
        f"== primes: {max_coherence == primes}"
    )
    print("  sample (n, dNFR, C):")
    for n in (2, 3, 4, 6, 7, 12, 13, 30):
        d = delta_nfr(n)
        c = F.local_coherence(d)
        kind = "prime" if sp.isprime(n) else "composite"
        print(f"    n={n:3d}  dNFR={d:+8.4f}  C={c:.4f}  ({kind})")
    print("  -> primes are exactly the zero-pressure, maximal-coherence nodes.")


def experiment_2_capacity_lever(limit=40):
    print()
    print("=" * 72)
    print("M2: the capacity lever (nu_f) -- primes are the grammatical kernel")
    print("=" * 72)
    dt, steps = 0.1, 50
    primes = [n for n in range(2, limit + 1) if sp.isprime(n)]
    composites = [n for n in range(2, limit + 1) if not sp.isprime(n)]
    for nu_f in (0.5, 1.0, 2.0):
        frozen = 0
        factored = 0
        for n in range(2, limit + 1):
            d = delta_nfr(n)
            epi = 1.0
            for _ in range(steps):
                epi += dt * nu_f * d
            drift = epi - 1.0
            if sp.isprime(n):
                if abs(drift) <= 1e-12:
                    frozen += 1
            else:
                predicted = steps * dt * nu_f * d  # (nu_f gain) x pressure
                if abs(drift - predicted) <= 1e-9:
                    factored += 1
        print(
            f"  nu_f={nu_f}:  primes frozen {frozen}/{len(primes)};  "
            f"composite drift = nu_f x pressure exactly {factored}/{len(composites)}"
        )
    # capacity is a pure scalar gain: doubling nu_f doubles the drift
    base = {n: steps * dt * 1.0 * delta_nfr(n) for n in range(2, limit + 1)}
    gain_ok = sum(
        1
        for n in composites
        if base[n] != 0
        and abs((steps * dt * 2.0 * delta_nfr(n)) / base[n] - 2.0) <= 1e-9
    )
    kernel = all(abs(base[n]) <= 1e-12 for n in primes)
    print(
        f"  doubling nu_f doubles the composite drift exactly: "
        f"{gain_ok}/{len(composites)}"
    )
    print(f"  every prime is in the kernel (zero drift for all nu_f): {kernel}")
    print("  -> the capacity lever scales the RATE; it can never move a prime.")


def experiment_3_pressure_axis(limit=60):
    print()
    print("=" * 72)
    print("M3: the U2 pressure axis -- the grammar's convergence target IS primality")
    print("=" * 72)
    by_omega = {}
    for n in range(2, limit + 1):
        t = arithmetic_terms(n)
        c = F.local_coherence(delta_nfr(n))
        by_omega.setdefault(t.omega, []).append(c)
    print("  U2 drives dNFR -> 0, i.e. coherence C = 1/(1+|dNFR|) -> 1.")
    print("  mean coherence C by Omega (factorization complexity = coherence debt):")
    prev = None
    monotone = True
    for om in sorted(by_omega):
        mean_c = statistics.mean(by_omega[om])
        label = "prime (Omega=1)" if om == 1 else f"Omega={om}"
        print(f"    {label:16s}  mean C = {mean_c:.4f}   (count {len(by_omega[om])})")
        if prev is not None and mean_c > prev + 1e-9:
            monotone = False
        prev = mean_c
    print(f"  C decreases monotonically with Omega: {monotone}")
    print("  -> the U2 target dNFR->0 (maximal coherence C=1) IS primality;")
    print("     a prime needs the EMPTY word (the identity of the star-free")
    print("     syntactic monoid, ex 145) -- it is already at the convergence")
    print("     target. Primality = grammatical inertness.")


def main():
    print()
    print("#" * 72)
    print("# Example 146 - Primality as Grammatical Inertness")
    print("#" * 72)
    print()
    experiment_1_three_readings()
    experiment_2_capacity_lever()
    experiment_3_pressure_axis()
    print()
    print("=" * 72)
    print("Summary")
    print("=" * 72)
    print("  The grammar acts on form through the single nodal rule dEPI/dt =")
    print("  nu_f * dNFR. On arithmetic nodes dNFR is the primality field, so:")
    print("  primes are the kernel of the capacity (nu_f) lever (frozen under")
    print("  every program), and the U2 pressure target dNFR->0 = maximal")
    print("  coherence C=1 = primality. A prime needs the empty word: it is")
    print("  grammatically inert. The grammar dynamics is the lens that unifies")
    print("  the number-theory module with the operator grammar. Restates the")
    print("  primality theorem through the grammar; no new number theory, no")
    print("  open problem closed.")
    print()


if __name__ == "__main__":
    main()