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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
__init__.py__init__.pyi_compat.py_version.py_version.pyialias.pyalias.pyibackend_config.pycache.pycache.pyiexecution.pyexecution.pyiflatten.pyflatten.pyigamma.pygamma.pyiglyph_history.pyglyph_history.pyiglyph_runtime.pyglyph_runtime.pyiimmutable.pyimmutable.pyiinitialization.pyinitialization.pyiio.pyio.pyilocking.pylocking.pyinode.pynode.pyiobservers.pyobservers.pyiontosim.pyontosim.pyipy.typedrng.pyrng.pyisecure_config.pyselector.pyselector.pyisense.pysense.pyistructural.pystructural.pyitokens.pytokens.pyitrace.pytrace.pyitypes.pytypes.pyiunits.pyunits.pyi
tetrad_evaluator.py
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FILE: benchmarks/composition_arithmetic.py

composition_arithmetic.py

benchmarks/composition_arithmetic.py

Composition arithmetic — does the OPERATION (+ and ×) emerge from coupling coherent systems, instead of being injected by hand?

This is the forward edge of the emergent-number programme. Two earlier harnesses established:

  • emergent_integers_symmetry.py : geometry -> integers OUT (cardinals = irrep dims)
  • inverse_spectrum_to_symmetry.py: partial spectrum -> group -> predict a hidden cardinal Both PRODUCE cardinals but never the arithmetic operation itself. The primality module (primality-test/tnfr_primality) goes the other way: it CONSUMES divisibility (trial division n % i) to re-read primality as the equilibrium condition ΔNFR = 0.

The open frontier is exactly: can the additive/multiplicative COMPOSITION of integers itself arise from composing systems, with no arithmetic put in by hand?

ENGINE (known theorems — the independent ground truth):

  • Cartesian product G □ H : Laplacian eigenvalues = {λ_i + μ_j} -> ADDITION
  • Tensor product G × H : adjacency eigenvalues = {α_i · β_j} -> MULTIPLICATION
  • Aut(G) × Aut(H) acts on the product; product irreps are tensor products, dim(ρ ⊗ σ) = dim ρ · dim σ -> CARDINALS multiply

TNFR reading: the canonical discrete ΔNFR / phase-curvature operator is the emergent random-walk Laplacian L_rw = I − D⁻¹W. The Cartesian/tensor product spectral additivity/multiplicativity used here is a theorem of the COMBINATORIAL graph Laplacian L = D − A specifically (the emergent L_rw lacks clean product additivity), so this layer reads the imposed connectivity's product structure. Coupling two coherent systems is a physical act, and the spectrum of the composite realises + and × with no arithmetic supplied externally. This connects to the B0★-α canonical graph-product programme (Q1 = G □ G, Q2 = G × G) in AGENTS.md.

HONEST SCOPE: This PRODUCES the additive and multiplicative composition of spectra, and the multiplication of degeneracy cardinals. It does NOT make arithmetic primality equal to representational irreducibility. We exhibit a COMPOSITE integer (4) that is the dimension of an IRREDUCIBLE coherent mode (K5 / S5): "physically indivisible" is NOT "arithmetically prime". And the SAME cardinal 4 is of compositional origin (2 + 2 -> multiplicity 2·2) in a product system (K3 □ K3) yet atomic in an indivisible one (K5). Whether a cardinal "factorises" is a property of the SYSTEM's symmetry, not of the integer — in contrast with the unique-factorisation theorem. The frontier is mapped, not erased.

LAPLACIAN CORRECTION (emergent-geometry audit): the product-spectrum additivity {λ_i+μ_j} / multiplicativity {α_i·β_j} demonstrated here holds ONLY for the imposed COMBINATORIAL Laplacian D - A. The canonical EMERGENT operator L_rw = I - D^-1 W (and its self-adjoint twin L_sym) does NOT exhibit product additivity (MEASURED: on K3 □ P3 and K3 □ K3, additive=False for both). So the

  • / × emergence shown is a property of the imposed graph CONNECTIVITY, not of the emergent nodal dynamics. The genuine emergent arithmetic in TNFR is in the STRUCTURAL-FREQUENCY channel -- νf(p·q) = νf(p) + νf(q) (log-additivity, νf = log p; the number-theory program) -- a DIFFERENT mechanism.

Run: python benchmarks/composition_arithmetic.py

Status: RESEARCH (composition-arithmetic falsifier).

Source Code

python
"""
benchmarks/composition_arithmetic.py

Composition arithmetic — does the OPERATION (+ and ×) emerge from coupling
coherent systems, instead of being injected by hand?

This is the forward edge of the emergent-number programme. Two earlier harnesses
established:
  - emergent_integers_symmetry.py  : geometry -> integers OUT (cardinals = irrep dims)
  - inverse_spectrum_to_symmetry.py: partial spectrum -> group -> predict a hidden cardinal
Both PRODUCE cardinals but never the arithmetic operation itself. The primality
module (primality-test/tnfr_primality) goes the other way: it CONSUMES divisibility
(trial division n % i) to re-read primality as the equilibrium condition ΔNFR = 0.

The open frontier is exactly: can the additive/multiplicative COMPOSITION of
integers itself arise from composing systems, with no arithmetic put in by hand?

ENGINE (known theorems — the independent ground truth):
  - Cartesian product  G □ H : Laplacian eigenvalues = {λ_i + μ_j}   -> ADDITION
  - Tensor   product   G × H : adjacency eigenvalues = {α_i · β_j}   -> MULTIPLICATION
  - Aut(G) × Aut(H) acts on the product; product irreps are tensor products,
    dim(ρ ⊗ σ) = dim ρ · dim σ                                       -> CARDINALS multiply

TNFR reading: the canonical discrete ΔNFR / phase-curvature operator is the
emergent random-walk Laplacian L_rw = I − D⁻¹W. The Cartesian/tensor product
spectral additivity/multiplicativity used here is a theorem of the COMBINATORIAL
graph Laplacian L = D − A specifically (the emergent L_rw lacks clean product
additivity), so this layer reads the imposed connectivity's product structure.
Coupling two coherent systems is a physical act, and the spectrum of the composite
realises + and × with no arithmetic supplied externally. This connects to the
B0★-α canonical graph-product programme (Q1 = G □ G, Q2 = G × G) in AGENTS.md.

HONEST SCOPE:
  This PRODUCES the additive and multiplicative composition of spectra, and the
  multiplication of degeneracy cardinals. It does NOT make arithmetic primality
  equal to representational irreducibility. We exhibit a COMPOSITE integer (4) that
  is the dimension of an IRREDUCIBLE coherent mode (K5 / S5): "physically
  indivisible" is NOT "arithmetically prime". And the SAME cardinal 4 is of
  compositional origin (2 + 2 -> multiplicity 2·2) in a product system (K3 □ K3)
  yet atomic in an indivisible one (K5). Whether a cardinal "factorises" is a
  property of the SYSTEM's symmetry, not of the integer — in contrast with the
  unique-factorisation theorem. The frontier is mapped, not erased.

  LAPLACIAN CORRECTION (emergent-geometry audit): the product-spectrum
  additivity {λ_i+μ_j} / multiplicativity {α_i·β_j} demonstrated here holds ONLY
  for the imposed COMBINATORIAL Laplacian D - A. The canonical EMERGENT operator
  L_rw = I - D^-1 W (and its self-adjoint twin L_sym) does NOT exhibit product
  additivity (MEASURED: on K3 □ P3 and K3 □ K3, additive=False for both). So the
  + / × emergence shown is a property of the imposed graph CONNECTIVITY, not of
  the emergent nodal dynamics. The genuine emergent arithmetic in TNFR is in the
  STRUCTURAL-FREQUENCY channel -- νf(p·q) = νf(p) + νf(q) (log-additivity,
  νf = log p; the number-theory program) -- a DIFFERENT mechanism.

Run:
    python benchmarks/composition_arithmetic.py

Status: RESEARCH (composition-arithmetic falsifier).
"""

from __future__ import annotations

import networkx as nx
import numpy as np
from networkx.algorithms.isomorphism import GraphMatcher


# --------------------------------------------------------------------------- #
# Spectra. L = D - A is the COMBINATORIAL graph Laplacian, whose product spectra
# are additive/multiplicative (a combinatorial theorem); the canonical emergent
# ΔNFR operator is L_rw = I - D^-1 W. A is the coupling matrix.
# --------------------------------------------------------------------------- #
def lap_spectrum(G, nodes=None):
    """Sorted eigenvalues of the combinatorial Laplacian L = D - A."""
    A = nx.to_numpy_array(G, nodelist=nodes if nodes else list(G.nodes()))
    L = np.diag(A.sum(axis=1)) - A
    return np.sort(np.linalg.eigvalsh(L))


def adj_spectrum(G, nodes=None):
    """Sorted eigenvalues of the adjacency matrix A."""
    A = nx.to_numpy_array(G, nodelist=nodes if nodes else list(G.nodes()))
    return np.sort(np.linalg.eigvalsh(A))


def multiset_close(a, b, tol=1e-8):
    """True if two float multisets coincide (as sorted sequences) within tol."""
    a = np.sort(np.asarray(a, dtype=float))
    b = np.sort(np.asarray(b, dtype=float))
    return a.shape == b.shape and bool(np.allclose(a, b, atol=tol))


def outer_sum(x, y):
    """All pairwise sums {x_i + y_j}."""
    return np.array([xi + yj for xi in x for yj in y])


def outer_prod(x, y):
    """All pairwise products {x_i * y_j}."""
    return np.array([xi * yj for xi in x for yj in y])


# --------------------------------------------------------------------------- #
# Emergence of + and ×
# --------------------------------------------------------------------------- #
def cartesian_addition_emerges(G, H, tol=1e-8):
    """Laplacian spectrum of G □ H equals the outer SUM of the factor spectra."""
    specG = lap_spectrum(G)
    specH = lap_spectrum(H)
    spec_prod = lap_spectrum(nx.cartesian_product(G, H))
    return multiset_close(spec_prod, outer_sum(specG, specH), tol), specG, specH


def tensor_multiplication_emerges(G, H, tol=1e-8):
    """Adjacency spectrum of G × H equals the outer PRODUCT of the factor spectra."""
    specG = adj_spectrum(G)
    specH = adj_spectrum(H)
    spec_prod = adj_spectrum(nx.tensor_product(G, H))
    return multiset_close(spec_prod, outer_prod(specG, specH), tol), specG, specH


# --------------------------------------------------------------------------- #
# Character irreducibility (reused engine: <χ,χ> over Aut(G))
# --------------------------------------------------------------------------- #
def automorphism_matrices(G, nodes, limit=20000):
    """Permutation matrices of Aut(G), in the fixed node order `nodes`."""
    index = {node: i for i, node in enumerate(nodes)}
    n = len(nodes)
    mats = []
    for k, mapping in enumerate(GraphMatcher(G, G).isomorphisms_iter()):
        if k >= limit:
            break
        M = np.zeros((n, n))
        for src, dst in mapping.items():
            M[index[dst], index[src]] = 1.0
        mats.append(M)
    return mats


def eigenspaces(G, nodes, tol=1e-6):
    """Return [(eigenvalue, multiplicity, projector)] of the Laplacian."""
    A = nx.to_numpy_array(G, nodelist=nodes)
    L = np.diag(A.sum(axis=1)) - A
    vals, vecs = np.linalg.eigh(L)
    groups = []
    i = 0
    while i < len(vals):
        j = i + 1
        while j < len(vals) and abs(vals[j] - vals[i]) < tol:
            j += 1
        U = vecs[:, i:j]
        groups.append((float(np.mean(vals[i:j])), j - i, U @ U.T))
        i = j
    return groups


def character_norm(P, mats, order):
    """<χ,χ> = (1/|Aut|) Σ_g trace(P·M_g)^2 ; ≈1 irreducible, k>1 reducible."""
    return sum(float(np.trace(P @ M)) ** 2 for M in mats) / order


# --------------------------------------------------------------------------- #
# Tests
# --------------------------------------------------------------------------- #
def test_addition():
    print("=" * 78)
    print("ADDITION emerges from the Cartesian product (Laplacian spectrum)")
    print("=" * 78)
    cases = [
        ("C4", nx.cycle_graph(4), "C5", nx.cycle_graph(5)),
        ("K3", nx.complete_graph(3), "P3", nx.path_graph(3)),
        ("K3", nx.complete_graph(3), "K3", nx.complete_graph(3)),
    ]
    all_ok = True
    for nG, G, nH, H in cases:
        ok, sG, sH = cartesian_addition_emerges(G, H)
        all_ok &= ok
        print(f"  {nG} [] {nH}: spec(L) == {{lambda_i + mu_j}} ? {ok}")
        print(f"      spec({nG}) = {np.round(sG, 3)}    spec({nH}) = {np.round(sH, 3)}")
    print(
        f"  VERDICT: {'PASS' if all_ok else 'FAIL'} "
        "-- '+' is read off the composite, not supplied"
    )
    return all_ok


def test_multiplication():
    print()
    print("=" * 78)
    print("MULTIPLICATION emerges from the tensor product (adjacency spectrum)")
    print("=" * 78)
    cases = [
        ("K3", nx.complete_graph(3), "K3", nx.complete_graph(3)),
        ("K3", nx.complete_graph(3), "C5", nx.cycle_graph(5)),
        ("K4", nx.complete_graph(4), "K3", nx.complete_graph(3)),
    ]
    all_ok = True
    for nG, G, nH, H in cases:
        ok, sG, sH = tensor_multiplication_emerges(G, H)
        all_ok &= ok
        print(f"  {nG} x {nH}: spec(A) == {{alpha_i * beta_j}} ? {ok}")
        print(f"      spec({nG}) = {np.round(sG, 3)}    spec({nH}) = {np.round(sH, 3)}")
    print(
        f"  VERDICT: {'PASS' if all_ok else 'FAIL'} "
        "-- 'x' is read off the composite, not supplied"
    )
    return all_ok


def test_cardinals_multiply():
    print()
    print("=" * 78)
    print("CARDINALS multiply: two 2-fold modes compose into a 4-fold mode")
    print("=" * 78)
    # K3 has Laplacian spectrum {0, 3, 3}: the 3 is a 2D irrep of S3.
    G = nx.complete_graph(3)
    print(
        f"  K3 Laplacian spectrum    = {np.round(lap_spectrum(G), 3)}  "
        "(degeneracy 2 at lambda=3)"
    )
    prod = nx.cartesian_product(G, G)
    groups = eigenspaces(prod, list(prod.nodes()))
    print("  K3 [] K3 Laplacian levels:")
    for val, mult, _ in groups:
        tag = ""
        if abs(val - 6.0) < 1e-6:
            tag = (
                "  <- 6 = 3+3 : multiplicity 2*2 = 4 (PRODUCT of the two 2-fold modes)"
            )
        elif abs(val - 3.0) < 1e-6:
            tag = "  <- 3 = 0+3 & 3+0 : accidental sum, NOT a product"
        print(f"      lambda = {val:5.2f}   multiplicity = {mult}{tag}")
    has_4 = any(abs(v - 6.0) < 1e-6 and m == 4 for v, m, _ in groups)
    print(
        f"  VERDICT: {'PASS' if has_4 else 'FAIL'} "
        "-- 2 x 2 = 4 realised by coupling, no 'x' put in"
    )
    return has_4


def test_irreducibility_is_not_primality():
    print()
    print("=" * 78)
    print("HONEST FRONTIER: irreducibility (physics) is NOT primality (arithmetic)")
    print("=" * 78)
    # K5: Aut = S5, Laplacian {0, 5,5,5,5}. The 4-fold mode is the standard irrep
    # of S5, which is IRREDUCIBLE — yet 4 = 2 x 2 arithmetically.
    K5 = nx.complete_graph(5)
    nodes5 = list(K5.nodes())
    mats5 = automorphism_matrices(K5, nodes5)
    order5 = len(mats5)
    print(f"  K5: |Aut| = {order5} (expected 5! = 120)")
    four_irreducible = False
    for val, mult, P in eigenspaces(K5, nodes5):
        chi = character_norm(P, mats5, order5)
        tag = ""
        if mult == 4:
            four_irreducible = abs(chi - 1.0) < 0.4
            tag = "  <- dim 4 is COMPOSITE (2*2) yet IRREDUCIBLE (atomic mode)"
        print(f"      lambda = {val:5.2f}  mult = {mult}  <chi,chi> = {chi:4.1f}{tag}")
    print()
    print(
        "  Meanwhile (test above) K3 [] K3 produced a 4-fold mode at lambda = 6 = 3+3"
    )
    print("  whose multiplicity is exactly 2*2 -- a 4 of COMPOSITIONAL origin.")
    print("  So the cardinal 4 is atomic in K5 (simple group S5) and compositional")
    print("  in K3 [] K3 (product group): whether it 'factorises' depends on the")
    print("  SYSTEM's symmetry, not on the integer. Arithmetic unique factorisation")
    print("  is a strictly stronger structure than representational composition.")
    print(
        f"  VERDICT: {'PASS' if four_irreducible else 'FAIL'} "
        "-- 'prime <=> irreducible' is correctly REFUTED"
    )
    return four_irreducible


def main():
    print(__doc__)
    r1 = test_addition()
    r2 = test_multiplication()
    r3 = test_cardinals_multiply()
    r4 = test_irreducibility_is_not_primality()
    print()
    print("=" * 78)
    print("SUMMARY")
    print("=" * 78)
    print(f"  '+' emerges (Cartesian product)         : {'PASS' if r1 else 'FAIL'}")
    print(f"  'x' emerges (tensor product)            : {'PASS' if r2 else 'FAIL'}")
    print(f"  cardinals multiply (2 x 2 = 4)          : {'PASS' if r3 else 'FAIL'}")
    print(f"  irreducibility != primality (frontier)  : {'PASS' if r4 else 'FAIL'}")
    overall = all([r1, r2, r3, r4])
    print(f"\n  OVERALL: {'ALL PASS' if overall else 'SOME FAILED'}")
    print()
    print("  Reading: the additive and multiplicative COMPOSITION of integers")
    print("  emerges from coupling coherent systems (no arithmetic injected) -- '+'")
    print("  from the Cartesian product, 'x' from the tensor product, and cardinals")
    print("  multiply. But representational irreducibility does NOT reproduce")
    print("  arithmetic primality: the same cardinal factorises or not depending on")
    print("  the system's symmetry. Coupling PRODUCES (+, x) on spectra and cardinals;")
    print("  the unique factorisation of integers remains a separate, stronger fact.")


if __name__ == "__main__":
    main()