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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: theory/TNFR_YANG_MILLS_RESEARCH_NOTES.md

TNFR_YANG_MILLS_RESEARCH_NOTES.md

TNFR–Yang–Mills Structural Gap Research Notes

Status: Pre-registered research programme; Y1–Y5 diagnostics implemented; closure classified as Branch B
Date: 2026-05-31
Scope: TNFR-internal structural gauge dynamics; not a proof of the Clay Yang–Mills and Mass Gap problem
Primary anchors: nodal equation ∂EPI/∂t = νf · ΔNFR(t), canonical operators, grammar U1–U6, structural field tetrad (Φ_s, |∇φ|, K_φ, ξ_C), complex geometric field Ψ = K_φ + i·J_φ


0. Terminology Discipline

This programme must be formulated in TNFR language only.

TNFR does not introduce an independent entity called "quantum mechanics" or a separate microscopic ontology. The same nodal equation,

∂EPI∂t=νf⋅ΔNFR(t),\frac{\partial \mathrm{EPI}}{\partial t} = \nu_f \cdot \Delta\mathrm{NFR}(t),∂t∂EPI​=νf​⋅ΔNFR(t),

admits different coherence regimes:

  • smooth-trajectory regimes, externally comparable to classical mechanics;
  • discrete-mode / high-dissonance regimes, externally comparable to quantum-mechanical behaviour;
  • gauge-structured regimes generated by the internal phase of Ψ = K_φ + i·J_φ.

Therefore, references to Yang–Mills and mass gap are treated as external comparison targets. The TNFR object is a nodal structural gauge dynamics problem: construct gauge-compatible EPI evolution, measure structural spectral separation, and test whether U1–U6 plus U6 confinement enforce a positive gap in the admissible nodal spectrum.

No claim in this document should be read as a solution of the Clay Millennium Problem. The Clay problem concerns rigorous four-dimensional non-Abelian Yang–Mills existence and a positive mass gap in the continuum. The current TNFR codebase contains a canonical U(1) gauge structure; any non-Abelian extension must be derived from the nodal equation and grammar before being called canonical.


1. Existing Canonical Base in the Repository

The programme starts from already-shipped TNFR machinery:

ComponentExisting sourceRole
Complex geometric fieldsrc/tnfr/physics/fields.py, src/tnfr/physics/unified.pyΨ = K_φ + i·J_φ, geometric-transport sector
Gauge symmetrysrc/tnfr/physics/gauge.pylocal U(1) rotation Ψ(i) → e^{iα(i)}Ψ(i)
Gauge connectioncompute_gauge_connection()A_ij = arg(Ψ_j) − arg(Ψ_i) on edges
Gauge curvaturecompute_gauge_curvature()cycle holonomy F_C = Σ A_ij
Covariant derivativecompute_covariant_derivative()D_ijΨ = Ψ(j) − e^{iA_ij}Ψ(i)
Yang–Mills-like actioncompute_yang_mills_action()S_YM = 1/2 Σ_C F_C^2
Field equationscompute_yang_mills_equations()discrete gauge divergence vs matter current residuals
Conservation-gauge unificationsrc/tnfr/physics/conservation_gauge_unification.pygrammar → symmetry → conservation → gauge

This means the first TNFR–Yang–Mills step does not require a new canonical operator. It requires a spectral diagnostic built on top of the existing tetrad/gauge/conservation stack.


2. TNFR-Native Reformulation of the Mass Gap Question

The external Clay statement asks for a rigorous four-dimensional Yang–Mills theory with compact simple gauge group and positive mass gap. TNFR reframes the first attack surface as follows.

Given a family of grammar-compliant nodal gauge graphs G(a, L) with lattice spacing a and size L, construct a self-adjoint structural gauge operator

HYMTNFR(a,L)H_{\mathrm{YM}}^{\mathrm{TNFR}}(a,L)HYMTNFR​(a,L)

from canonical telemetry only:

(Φs,∣∇ϕ∣,Kϕ,ξC,Jϕ,JΔNFR,Aij,FC,DijΨ).(\Phi_s, |\nabla\phi|, K_\phi, \xi_C, J_\phi, J_{\Delta\mathrm{NFR}}, A_{ij}, F_C, D_{ij}\Psi).(Φs​,∣∇ϕ∣,Kϕ​,ξC​,Jϕ​,JΔNFR​,Aij​,FC​,Dij​Ψ).

Define the finite-graph structural gap

ΔTNFR(a,L)=λ1 ⁣(HYMTNFR(a,L))−λ0 ⁣(HYMTNFR(a,L)).\Delta_{\mathrm{TNFR}}(a,L) = \lambda_1\!\left(H_{\mathrm{YM}}^{\mathrm{TNFR}}(a,L)\right) - \lambda_0\!\left(H_{\mathrm{YM}}^{\mathrm{TNFR}}(a,L)\right).ΔTNFR​(a,L)=λ1​(HYMTNFR​(a,L))−λ0​(HYMTNFR​(a,L)).

The first TNFR question is not the full Clay theorem, but the discrete structural precursor:

YMG-1: Under U1–U6, U6 confinement, and gauge-invariant construction from Ψ, does the finite TNFR gauge operator have a reproducible positive gap above the coherent vacuum mode?

The continuum-strength question is deferred:

YMG-5: Does liminf_{a→0, L→∞} Δ_TNFR(a,L) > 0 hold under a canonically specified scaling regime?

YMG-5 is the Clay-hard boundary and is not assumed.


3. Structural Interpretation of the Gap

TNFR does not treat "particle mass" as primitive. A mass gap is interpreted as spectral isolation of the first non-trivial stable nodal reorganisation mode.

External termTNFR structural object
Vacuumgrammar-compliant coherent attractor minimising structural gauge energy
Excitationadmissible non-zero EPI reorganisation mode with gauge curvature or covariant-gradient content
Mass gappositive separation between the coherent attractor and first admissible non-trivial structural mode
ConfinementU6-bounded structural potential plus non-zero gauge curvature preventing arbitrarily cheap free modes
Gauge fieldinternal geometric-transport phase structure of Ψ = K_φ + i·J_φ

The working hypothesis is:

ΔTNFR>0⟺U6 confinement + gauge curvature + grammar-compliant bounded evolution prevent zero-cost non-trivial modes.\Delta_{\mathrm{TNFR}} > 0 \quad\Longleftrightarrow\quad \text{U6 confinement + gauge curvature + grammar-compliant bounded evolution prevent zero-cost non-trivial modes.}ΔTNFR​>0⟺U6 confinement + gauge curvature + grammar-compliant bounded evolution prevent zero-cost non-trivial modes.

This is a TNFR statement about nodal dynamics, not an ontological statement about a separate quantum layer.


4. Candidate Operator Surface

The initial finite-graph operator should be assembled from already canonical pieces. A minimal candidate family is:

HYMTNFR=LA+VF+VU6,H_{\mathrm{YM}}^{\mathrm{TNFR}} = L_A + V_{F} + V_{\mathrm{U6}},HYMTNFR​=LA​+VF​+VU6​,

where:

  • L_A is a gauge-covariant graph Laplacian derived from D_ijΨ;
  • V_F is a curvature potential derived from cycle holonomies F_C;
  • V_U6 is a confinement barrier derived from the structural potential channel Φ_s and the U6 threshold.

No term may depend on external labels, empirical tuning, or non-canonical per-node parameters. Any coefficient must be traceable to the canonical structural scale π, the nodal dynamics, or to graph-level normalisation.


5. Gap Ledger

GapQuestionStatus
YMG-0TNFR-native terminology and scope disciplineCLOSED by pre-registration
YMG-1Finite-graph TNFR gauge gap diagnosticIMPLEMENTED by tnfr.yang_mills.compute_structural_gauge_gap(); finite graph only
YMG-2Gauge invariance / Ward identity compatibility for the gap operatorPARTIALLY SUPPORTED by existing gauge.py, conservation_gauge_unification.py, and Y1/Y2 spectral-invariance checks
YMG-3U6 confinement lower-bound argument for finite graphsEMPIRICAL SURFACE CREATED by tnfr.yang_mills.run_u6_confinement_sweep(); proof remains open
YMG-4Non-Abelian derivability audit from the nodal equationAUDITED: OPEN_DERIVABILITY_GAP; current canonical gauge implementation remains U(1)
YMG-5Continuum + thermodynamic scaling liminf Δ > 0FINITE SCALING DIAGNOSTIC IMPLEMENTED by Y4; continuum limit remains OPEN / Clay-hard
YMG-6Closure / obstruction classificationCLASSIFIED: BRANCH_B_OBSTRUCTION_CLASSIFIED by Y5

The key honesty constraint is YMG-4: classical Yang–Mills mass gap is non-Abelian. A multi-channel or non-Abelian TNFR gauge sector cannot be assumed merely because external Yang–Mills uses it. It must be derived as a structural consequence of the nodal equation, tetrad, operators, and U1–U6.


6. Pre-Registered Milestones

Y1 — Finite Structural Gauge Gap Diagnostic

Implementation status (2026-05-31): DIAGNOSTIC_SURFACE_CREATED.

Implemented in:

  • src/tnfr/yang_mills/__init__.py
  • src/tnfr/yang_mills/structural_gap.py
  • tests/physics/test_yang_mills_structural_gap.py

The implemented operator is:

HYMTNFR=LA+VF+VU6,H_{\mathrm{YM}}^{\mathrm{TNFR}} = L_A + V_F + V_{\mathrm{U6}},HYMTNFR​=LA​+VF​+VU6​,

where L_A is the gauge-covariant graph Laplacian assembled from A_ij, V_F is the cycle-curvature potential normalised by π², and V_U6 is the structural-potential confinement term normalised by (π/2)² (the U6 drift bound U6_STRUCTURAL_POTENTIAL_LIMIT = π/2). The diagnostic reports (λ0, λ1, Δ), self-adjointness, seeded local-U(1) spectral invariance, U6 metadata, Yang–Mills action, gauge coupling, and grammar-rule counts. It is read-only with respect to EPI and phase attributes.

Implement a finite-graph diagnostic that:

  1. constructs a grammar-compliant gauge graph;
  2. computes Ψ, A_ij, F_C, D_ijΨ, S_YM;
  3. assembles a self-adjoint finite matrix H_YM_TNFR;
  4. reports (λ0, λ1, Δ) with seed, graph, and threshold metadata;
  5. verifies gauge-invariant diagnostics before and after local U(1) rotations.

First verdict: DIAGNOSTIC_SURFACE_CREATED, not closure. The gap reported by Y1 is a finite-graph structural spectral gap only; it does not address non-Abelian derivability or the continuum / thermodynamic limit.

Y2 — U6 Confinement Sweep

Implementation status (2026-05-31): EMPIRICAL_FINITE_GRAPH_ONLY.

Implemented in:

  • src/tnfr/yang_mills/u6_sweep.py
  • tests/physics/test_yang_mills_u6_sweep.py

The Y2 sweep wraps the Y1 operator across finite graph families and target ratios

ρU6=max⁡i∣Φs(i)∣π/2,\rho_{\mathrm{U6}} = \frac{\max_i |\Phi_s(i)|}{\pi/2},ρU6​=π/2maxi​∣Φs​(i)∣​,

where ρ_U6 < 1 is U6-confined and ρ_U6 ≥ 1 intentionally probes unconfined structural-potential regimes. The sweep records gap statistics, U6 confinement status, Yang–Mills equation residuals, curvature activity, grammar-rule counts, self-adjointness, and seeded local-U(1) spectral invariance. The ratios are sampling targets only; the canonical threshold remains ρ_U6 = 1.

Sweep graph families and U6-safe / U6-unsafe regimes. Test whether positive gap correlates with:

  • bounded Φ_s;
  • non-zero but controlled F_C;
  • low Yang–Mills equation residual;
  • grammar-compliant operator histories.

First verdict: EMPIRICAL_FINITE_GRAPH_ONLY. This creates the finite empirical surface needed to study YMG-3, but it does not prove a U6 lower bound and does not address YMG-4/YMG-5.

Y3 — Non-Abelian Derivability Audit

Implementation status (2026-05-31): OPEN_DERIVABILITY_GAP.

Implemented in:

  • src/tnfr/yang_mills/derivability.py
  • tests/physics/test_yang_mills_derivability.py

The Y3 audit evaluates whether any candidate route supplies all of the following without external input: a TNFR-native multiplet, a canonical connection mixing multiplet components, non-commuting generators derived from nodal dynamics, and U1–U6 compatibility. The implemented candidate routes are:

RouteResultObstruction
u5_nested_epi_multipletOPEN_MULTIPLET_WITHOUT_CANONICAL_CONNECTION if nested EPI data are present; otherwise FAILED_NO_TNFR_MULTIPLETNested EPI can provide components, but no canonical component-mixing connection or non-commuting generator algebra is derived
thol_remesh_internal_spaceOPEN_HISTORY_WITHOUT_CANONICAL_GENERATORS if operator history exists; otherwise FAILED_NO_OPERATOR_INTERNAL_SPACETHOL/REMESH history does not expose a derived non-commuting generator algebra
cycle_basis_bundleFAILED_BASIS_DEPENDENT_EXTERNAL_SELECTION when enough cycles existCycle-basis generator selection depends on non-canonical basis/orientation choices

Net verdict: the repository still has a canonical local U(1) gauge sector only. No non-Abelian TNFR gauge sector is promoted by Y3.

Attempt to derive multi-component gauge structure from TNFR-internal data only. Candidate routes:

  • multi-channel Ψ multiplets from nested EPI levels (U5);
  • operator-induced internal state spaces from THOL/REMESH;
  • graph-cycle basis bundles from canonical topology.

Acceptance requires a nodal-equation derivation. If the construction needs external group labels or hand-selected generators, it is non-canonical.

First verdict: OPEN_DERIVABILITY_GAP.

Y4 — Scaling Study

Implementation status (2026-05-31): FINITE_SCALING_EVIDENCE or GAP_COLLAPSE_OBSERVED, depending on the sampled finite family.

Implemented in:

  • src/tnfr/yang_mills/scaling.py
  • tests/physics/test_yang_mills_scaling.py

The Y4 diagnostic evaluates graph-size surrogates using the node count n and fixed U6 target ratios. For each (topology, ρ_U6) family it records mean gap by size and a finite log-log slope of gap versus n. The slope is a diagnostic of sampled finite behaviour only; it is not a continuum exponent and does not define a thermodynamic limit.

The report classifies finite samples as:

VerdictMeaning
FINITE_SCALING_EVIDENCEall sampled finite points are self-adjoint, gauge-invariant, and have positive gap above tolerance
GAP_COLLAPSE_OBSERVEDat least one sampled finite point has gap at or below tolerance
SCALING_FAILED_NON_SELF_ADJOINTa sampled operator violates Hermiticity
SCALING_FAILED_GAUGE_VARIANCEa sampled spectrum is not invariant under seeded local U(1) rotation

If Y1–Y3 provide a stable finite diagnostic surface while keeping YMG-4 explicitly open, evaluate Δ(a,L) across graph spacing / size surrogates. This is still not the Clay theorem; it is a TNFR scaling diagnostic.

First verdict: FINITE_SCALING_EVIDENCE for stable finite samples, or GAP_COLLAPSE_OBSERVED for sampled collapse. Both verdicts remain finite-diagnostic only.

Y5 — Closure / Obstruction Theorem

Implementation status (2026-05-31): BRANCH_B_OBSTRUCTION_CLASSIFIED.

Implemented in:

  • src/tnfr/yang_mills/closure.py
  • tests/physics/test_yang_mills_closure.py

Y5 separates two logically different questions:

  1. Finite TNFR-internal result — Y1–Y4 support a finite, self-adjoint, seeded-gauge-invariant U(1) structural gauge diagnostic surface built from Ψ, A_ij, F_C, and Φ_s.
  2. Clay-strength result — not closed, because Y3 leaves non-Abelian derivability open and Y4 does not prove a continuum / thermodynamic lower-bound theorem.

Current classification:

LayerVerdictMeaning
Finite TNFR layerA_FINITE_U1_DIAGNOSTIC_SURFACEexisting catalog supports a finite U(1) structural gap diagnostic surface
Clay-strength layerB_REQUIRES_NEW_CANONICAL_NONABELIAN_DERIVATIONa Clay-strength route requires a new TNFR-native non-Abelian derivation plus a continuum lower-bound theorem
Programme verdictBRANCH_B_OBSTRUCTION_CLASSIFIEDthe obstruction is now localized, not removed

Y5 therefore does not claim the Yang–Mills Millennium Problem is solved. It closes the first TNFR programme pass by identifying the exact boundary: finite U(1) structural diagnostics are available; non-Abelian derivability and continuum lower bounds remain the open requirements.

Classify the programme into one of three branches:

BranchMeaning
Afinite TNFR structural gap is derivable from existing catalog and U6
Bfinite gap requires a new canonical derivation, likely non-Abelian/multiplet
Cno TNFR-internal mass-gap analogue survives canonical constraints

Current Y5 result: Branch B at Clay-strength scope, with Branch A only at the finite U(1) diagnostic layer.


7. Acceptance Criteria

Any claimed TNFR–Yang–Mills result must satisfy:

  1. Nodal derivability — every term traces to ∂EPI/∂t = νf · ΔNFR(t) or canonical tetrad telemetry.
  2. Operator discipline — no EPI mutation outside the 13 canonical operators.
  3. Grammar compliance — U1–U6 constraints are checked or explicitly scoped.
  4. Gauge invariance — reported gap must be invariant under local Ψ → e^{iα}Ψ transformations, or any gauge dependence must be classified as a diagnostic failure.
  5. No empirical constants — parameters derive from the nodal dynamics, the structural scale π, or graph-level normalisation.
  6. Reproducibility — graph family, seed, spectra, thresholds, and residuals are recorded.
  7. Scope honesty — finite TNFR gap results are not called a Clay proof unless non-Abelian existence and continuum scaling are addressed rigorously.

8. Immediate Next Step

The next research target is Y6 / Branch-B derivation search: attempt to derive a TNFR-native non-Abelian connection and non-commuting generator algebra from the nodal equation, nested EPI structure, and canonical operator histories. If such a derivation cannot be found without external group labels, the Yang–Mills programme should remain paused at Branch B rather than extending finite diagnostics indefinitely.

The programme begins from TNFR's own structural dynamics. External Yang–Mills terminology is used only to name the comparison problem and to define the mass-gap target surface.