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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: src/tnfr/riemann/remesh_infinity_residue_split.py

remesh_infinity_residue_split.py

Source Code

python
r"""P50 — R\_infinity residue split of the P31 oscillatory correction.

Diagnostic milestone that lifts the N15 REMESH-\ :math:`\infty` closure
(`theory/REMESH_INFINITY_DERIVATION.md`, master commits a1f298fd /
badac156 / 48b0574a) to the canonical TNFR-Riemann program.

Background
----------
The N15 derivation proved that the asymptotic REMESH limit

.. math::

    \mathcal{R}_\infty
        := \lim_{\tau_g \to \infty}
            \mathcal{R}_{\tau_l, \tau_g, \alpha}

is a bounded self-adjoint orthogonal projection on :math:`H^2(D)`,
equal to the projector onto :math:`\ker(I - \mathcal{R})`.  Its
fixed-mode subspace is spanned by Fourier components at the resonant
angular frequencies

.. math::

    \omega_k = \frac{2\pi k}{\operatorname{lcm}(\tau_l, \tau_g)},
        \qquad k \in \mathbb{Z},

with uniform spectral density
:math:`\rho = \operatorname{lcm}(\tau_l, \tau_g) / \pi`.

The §13septies / §13nonies analysis (`theory/TNFR_RIEMANN_RESEARCH_NOTES.md`)
identifies the residual obstruction of T-HP with the **oscillatory
half** :math:`S(T) = \pi^{-1}\arg\zeta(\tfrac12 + iT)`, structurally
matched with :math:`\ker(\mathcal{R}_\infty)`.  The **smooth half** of
the admissible rescaling operator :math:`\mathcal{F}` is closed at
the density level by P28 and lifted to the operator level by P30
(`structural_zero_density.py`, `admissible_rescaling.py`).

What P50 measures
-----------------
P50 takes the canonical TNFR prime-ladder reconstruction
:math:`S_{\mathrm{TNFR}}(T)` of :math:`S(T)` from P31
(`oscillatory_correction.py`), evaluates it on a uniform :math:`T`
grid aligned with the REMESH-\ :math:`\infty` resonant lattice, and
splits it via the Fourier-mode projector

.. math::

    \mathcal{R}_\infty[f](T)
        = \sum_{k\,:\,\omega_k\in\operatorname{lattice}}
            \hat f_k\, e^{i\omega_k T},

into a *range part* :math:`\mathcal{R}_\infty\,S_{\mathrm{TNFR}}` and
a *kernel part* :math:`(I - \mathcal{R}_\infty)\,S_{\mathrm{TNFR}}`.

A priori structural prediction
------------------------------
The prime-ladder spectrum (P12 / P14 canonical) has Fourier content
exclusively at the transcendental frequencies :math:`\{k \log p\}`.
These are linearly independent over :math:`\mathbb{Q}` (Baker's
theorem on linear independence of logarithms of algebraic numbers)
and in particular none coincides with a rational multiple of
:math:`\pi/\operatorname{lcm}(\tau_l, \tau_g)`.  Therefore the
N15-resonant lattice and the prime-ladder Fourier support are
disjoint, and the prediction is

.. math::

    \|\mathcal{R}_\infty\,S_{\mathrm{TNFR}}\|
        / \|S_{\mathrm{TNFR}}\| \;\to\; 0

as the diagnostic window length :math:`L \to \infty`.

Pre-registered verdicts
-----------------------
* ``RESIDUE_IN_KER_ONLY``
    Range fraction below the canonical threshold (default 5%).
    Confirms the §13septies / §13nonies structural identification:
    the P31 oscillatory correction lives in
    :math:`\ker(\mathcal{R}_\infty)`, structurally matching the
    location predicted for the T-HP residual obstruction.
* ``RESIDUE_IN_RANGE_ONLY``
    Kernel fraction below the threshold.  Would refute the P31
    construction as an oscillatory attack — the correction would be
    fully absorbed by the smooth half already closed by P30.
* ``RESIDUE_MIXED``
    Both fractions above the threshold.  Indicates either a gauge
    leak in P30 (smooth half not cleanly separated) or a numerical
    boundary artefact (window too short for the asymptotic limit).

Honest scope (mandatory)
------------------------
* P50 is a **structural-compatibility diagnostic only**.  It does NOT
  advance G4 = RH.  It does NOT close T-HP.  It does NOT promote any
  new canonical operator beyond the 13-operator catalog.
* Positive verdict (``RESIDUE_IN_KER_ONLY``) is **branch B2
  evidence** at the function-space level: it corroborates that any
  closure of T-HP through the oscillatory half requires structure
  that lives in :math:`\ker(\mathcal{R}_\infty)`, where the
  prime-ladder content already sits.  The decision between branches
  B1 / B2 / B3 of §13septies / §13octies remains open.
* This module imports ONLY canonical TNFR ingredients
  (`prime_ladder_oscillatory_sum` from P31, REMESH-canonical
  :math:`(\tau_l, \tau_g) = (4, 8)`, :math:`\alpha = 0.5`).  No
  external zeros, no mpmath, no fitting.

References
----------
* N15 master:  `theory/REMESH_INFINITY_DERIVATION.md` §§1-23.
* T-HP gap:    `theory/TNFR_RIEMANN_RESEARCH_NOTES.md` §13septies,
               §13nonies.
* P31:         `oscillatory_correction.py`
               (`prime_ladder_oscillatory_sum`).
* P30:         `admissible_rescaling.py` (smooth half of T-HP).
* AGENTS.md:   "REMESH-\u221E Closure: Catalog Completeness Theorem".
"""

from __future__ import annotations

import math
from dataclasses import dataclass

import numpy as np

from .oscillatory_correction import prime_ladder_oscillatory_sum
from .von_mangoldt import PrimeLadderSpectrum, build_prime_ladder_spectrum

__all__ = [
    "build_resonant_bin_mask",
    "split_residue_by_remesh_infinity",
    "ResidueSplitCertificate",
    "compute_residue_split_certificate",
]


# ----------------------------------------------------------------------
# R_infinity projector as a DFT-bin mask
# ----------------------------------------------------------------------


def build_resonant_bin_mask(
    n_samples: int,
    *,
    tau_l: int = 4,
    tau_g: int = 8,
) -> np.ndarray:
    r"""Boolean mask over DFT bins selecting the N15-resonant lattice.

    On a uniform sample grid of length ``n_samples`` with unit spacing
    in :math:`T`-units, DFT bin :math:`k` corresponds to angular
    frequency :math:`\omega_k = 2\pi k / n_{\text{samples}}` (with
    bins :math:`k > n_{\text{samples}}/2` aliasing to the negative
    half).

    The N15-resonant subspace of :math:`\mathcal{R}_\infty` consists
    of Fourier modes at :math:`\omega = 2\pi m / L` for integer
    :math:`m`, where :math:`L = \operatorname{lcm}(\tau_l, \tau_g)`.
    For these to coincide with DFT bins we require
    ``n_samples`` to be a positive integer multiple of :math:`L`, and
    the resonant bins are :math:`k \in \{0, M, 2M, \dots\}` with
    :math:`M = n_{\text{samples}} / L`.

    Parameters
    ----------
    n_samples : int
        Length of the DFT.  Must be a positive multiple of
        ``lcm(tau_l, tau_g)``.
    tau_l, tau_g : int
        Canonical REMESH delays (default :math:`(\tau_l, \tau_g) =
        (4, 8)`, the documented TNFR canonical pair).

    Returns
    -------
    np.ndarray
        Boolean array of shape ``(n_samples,)``; ``True`` entries
        mark resonant DFT bins (including the negative-frequency
        aliases at :math:`k = n_{\text{samples}} - jM`).
    """
    if n_samples <= 0:
        raise ValueError("n_samples must be positive")
    if tau_l <= 0 or tau_g <= 0:
        raise ValueError("tau_l and tau_g must be positive")
    period = math.lcm(int(tau_l), int(tau_g))
    if n_samples % period != 0:
        raise ValueError(
            f"n_samples ({n_samples}) must be a multiple of "
            f"lcm(tau_l, tau_g) = {period}"
        )
    step = n_samples // period
    mask = np.zeros(n_samples, dtype=bool)
    mask[::step] = True
    return mask


def split_residue_by_remesh_infinity(
    signal: np.ndarray,
    *,
    tau_l: int = 4,
    tau_g: int = 8,
) -> tuple[np.ndarray, np.ndarray]:
    r"""Split a signal into range / kernel of :math:`\mathcal{R}_\infty`.

    Parameters
    ----------
    signal : np.ndarray
        Real 1-D signal sampled on the canonical unit-spacing grid in
        :math:`T`-units.  Length must be a multiple of
        :math:`\operatorname{lcm}(\tau_l, \tau_g)`.
    tau_l, tau_g : int
        Canonical REMESH delays.

    Returns
    -------
    range_part : np.ndarray
        :math:`\mathcal{R}_\infty[\text{signal}]`, real-valued, same
        shape as ``signal``.
    kernel_part : np.ndarray
        :math:`(I - \mathcal{R}_\infty)[\text{signal}]`, real-valued,
        same shape as ``signal``.

    Notes
    -----
    By construction ``range_part + kernel_part == signal`` exactly
    (up to FFT round-off).
    """
    sig = np.asarray(signal, dtype=float)
    if sig.ndim != 1:
        raise ValueError("signal must be 1-D")
    mask = build_resonant_bin_mask(sig.size, tau_l=tau_l, tau_g=tau_g)
    spectrum = np.fft.fft(sig)
    range_spectrum = np.where(mask, spectrum, 0.0 + 0.0j)
    kernel_spectrum = spectrum - range_spectrum
    range_part = np.real(np.fft.ifft(range_spectrum))
    kernel_part = np.real(np.fft.ifft(kernel_spectrum))
    return range_part, kernel_part


# ----------------------------------------------------------------------
# Certificate
# ----------------------------------------------------------------------


@dataclass(frozen=True)
class ResidueSplitCertificate:
    r"""Certificate for the P50 :math:`\mathcal{R}_\infty` residue split.

    Attributes
    ----------
    n_samples
        Length of the diagnostic window in :math:`T`-units.
    tau_l, tau_g
        Canonical REMESH delays.
    lcm_period
        :math:`\operatorname{lcm}(\tau_l, \tau_g)`.
    n_primes, max_power
        P12 / P14 prime-ladder parameters used to build
        :math:`S_{\mathrm{TNFR}}`.
    t_min, t_max
        Diagnostic window endpoints.
    norm_total
        :math:`\|S_{\mathrm{TNFR}}\|_2` on the window (L\ :sup:`2`
        norm, FFT convention).
    norm_in_range
        :math:`\|\mathcal{R}_\infty\,S_{\mathrm{TNFR}}\|_2`.
    norm_in_kernel
        :math:`\|(I - \mathcal{R}_\infty)\,S_{\mathrm{TNFR}}\|_2`.
    ratio_in_range, ratio_in_kernel
        Energy fractions in each subspace.  Sum exactly to 1 by
        Parseval.
    range_control_resonant
        Diagnostic sanity check: range fraction for the canonical
        positive-control signal :math:`\sin(\omega_1 T)` with
        :math:`\omega_1 = 2\pi /\operatorname{lcm}(\tau_l, \tau_g)`,
        which lies entirely in :math:`\operatorname{range}
        (\mathcal{R}_\infty)`.  Should be :math:`1` up to round-off.
    range_control_nonresonant
        Diagnostic sanity check: range fraction for the canonical
        negative-control signal :math:`\sin(\gamma T)` with
        :math:`\gamma` the Euler-Mascheroni constant (transcendental,
        non-resonant), which lies entirely in :math:`\ker
        (\mathcal{R}_\infty)` asymptotically.  Should be near zero.
    threshold
        Decision threshold on the dominant fraction (default 5%).
    verdict
        One of ``RESIDUE_IN_KER_ONLY``, ``RESIDUE_IN_RANGE_ONLY``,
        ``RESIDUE_MIXED``.
    notes
        Honest-scope reminder.
    """

    n_samples: int
    tau_l: int
    tau_g: int
    lcm_period: int
    n_primes: int
    max_power: int
    t_min: float
    t_max: float
    norm_total: float
    norm_in_range: float
    norm_in_kernel: float
    ratio_in_range: float
    ratio_in_kernel: float
    range_control_resonant: float
    range_control_nonresonant: float
    threshold: float
    verdict: str
    notes: str

    def summary(self) -> str:
        lines = [
            "P50 — REMESH-infinity Residue Split Certificate",
            f"  n_samples              : {self.n_samples}",
            f"  (tau_l, tau_g)         : ({self.tau_l}, {self.tau_g})",
            f"  lcm period             : {self.lcm_period}",
            f"  n_primes               : {self.n_primes}",
            f"  max_power (K)          : {self.max_power}",
            f"  T window               : " f"[{self.t_min:.3f}, {self.t_max:.3f}]",
            f"  ||S_TNFR||_2           : {self.norm_total:.4e}",
            f"  ||R_inf S_TNFR||_2     : {self.norm_in_range:.4e}",
            f"  ||(I-R_inf) S_TNFR||_2 : {self.norm_in_kernel:.4e}",
            f"  range fraction         : " f"{100.0 * self.ratio_in_range:7.4f} %",
            f"  kernel fraction        : " f"{100.0 * self.ratio_in_kernel:7.4f} %",
            "  controls (sanity):",
            f"    range[sin(omega_1 T)] : "
            f"{100.0 * self.range_control_resonant:7.4f} %  "
            "(expect ~100)",
            f"    range[sin(gamma T)]   : "
            f"{100.0 * self.range_control_nonresonant:7.4f} %  "
            "(expect ~0)",
            f"  threshold              : " f"{100.0 * self.threshold:.2f} %",
            f"  verdict                : {self.verdict}",
            f"  notes                  : {self.notes}",
        ]
        return "\n".join(lines)


def compute_residue_split_certificate(
    *,
    n_primes: int = 200,
    max_power: int = 8,
    tau_l: int = 4,
    tau_g: int = 8,
    n_periods: int = 64,
    t_min: float = 1.0,
    threshold: float = 0.05,
) -> ResidueSplitCertificate:
    r"""Run the full P50 diagnostic and emit a certificate.

    Builds the canonical P12 / P14 prime-ladder spectrum, evaluates
    :math:`S_{\mathrm{TNFR}}(T)` on a uniform :math:`T` grid of
    length :math:`n_{\text{periods}} \cdot \operatorname{lcm}
    (\tau_l, \tau_g)`, splits via the
    :math:`\mathcal{R}_\infty` Fourier-mode projector, and reports
    range / kernel norms plus two canonical control signals.

    Parameters
    ----------
    n_primes : int, default 200
        Primes used in the canonical prime-ladder spectrum (P12).
    max_power : int, default 8
        REMESH echo cap :math:`K` (P12).
    tau_l, tau_g : int, default (4, 8)
        Canonical REMESH delays.  Default is the documented TNFR
        canonical pair.
    n_periods : int, default 64
        Window length in units of :math:`\operatorname{lcm}(\tau_l,
        \tau_g)`.  Larger values sharpen the asymptotic verdict.
    t_min : float, default 1.0
        Diagnostic window start in :math:`T`-units (kept positive to
        avoid the :math:`T = 0` singularity of the smooth density).
    threshold : float, default 0.05
        Decision threshold on the dominant energy fraction.

    Returns
    -------
    ResidueSplitCertificate
    """
    if n_periods < 1:
        raise ValueError("n_periods must be >= 1")
    if not (0.0 < threshold < 0.5):
        raise ValueError("threshold must be in (0, 0.5)")
    period = math.lcm(int(tau_l), int(tau_g))
    n_samples = n_periods * period
    spectrum: PrimeLadderSpectrum = build_prime_ladder_spectrum(
        n_primes, max_power=max_power
    )

    t_grid = t_min + np.arange(n_samples, dtype=float)
    t_max = float(t_grid[-1])
    signal = np.asarray(prime_ladder_oscillatory_sum(t_grid, spectrum), dtype=float)

    range_part, kernel_part = split_residue_by_remesh_infinity(
        signal, tau_l=tau_l, tau_g=tau_g
    )

    norm_total = float(np.linalg.norm(signal))
    norm_range = float(np.linalg.norm(range_part))
    norm_kernel = float(np.linalg.norm(kernel_part))
    if norm_total <= 0.0:
        raise RuntimeError(
            "S_TNFR vanished on the diagnostic window; refusing to " "normalise"
        )
    ratio_range = (norm_range / norm_total) ** 2
    ratio_kernel = (norm_kernel / norm_total) ** 2

    # Canonical sanity controls
    omega_resonant = 2.0 * math.pi / period
    control_resonant = np.sin(omega_resonant * t_grid)
    rng_res, _ = split_residue_by_remesh_infinity(
        control_resonant, tau_l=tau_l, tau_g=tau_g
    )
    n_res = float(np.linalg.norm(control_resonant))
    ctrl_res_frac = (float(np.linalg.norm(rng_res)) / n_res) ** 2

    # Euler-Mascheroni constant: transcendental, non-resonant.
    gamma_em = 0.5772156649015329
    control_nonres = np.sin(gamma_em * t_grid)
    rng_nonres, _ = split_residue_by_remesh_infinity(
        control_nonres, tau_l=tau_l, tau_g=tau_g
    )
    n_nonres = float(np.linalg.norm(control_nonres))
    ctrl_nonres_frac = (float(np.linalg.norm(rng_nonres)) / n_nonres) ** 2

    if ratio_range < threshold and ratio_kernel >= threshold:
        verdict = "RESIDUE_IN_KER_ONLY"
        notes = (
            "Branch B2 evidence at the function-space level: the "
            "P31 oscillatory correction lives in ker(R_inf), "
            "structurally matching the location predicted for the "
            "T-HP residual obstruction. Does NOT advance G4 = RH."
        )
    elif ratio_kernel < threshold and ratio_range >= threshold:
        verdict = "RESIDUE_IN_RANGE_ONLY"
        notes = (
            "Refutes P31 as an oscillatory attack: the correction "
            "would already be absorbed by the smooth half (P30). "
            "Requires audit of P30 / P31 reconstruction. Does NOT "
            "advance G4 = RH."
        )
    else:
        verdict = "RESIDUE_MIXED"
        notes = (
            "Both fractions above threshold: gauge leak in P30 "
            "smooth half or boundary artefact (window too short). "
            "Increase n_periods and re-test. Does NOT advance "
            "G4 = RH."
        )

    return ResidueSplitCertificate(
        n_samples=n_samples,
        tau_l=int(tau_l),
        tau_g=int(tau_g),
        lcm_period=period,
        n_primes=int(n_primes),
        max_power=int(max_power),
        t_min=float(t_min),
        t_max=t_max,
        norm_total=norm_total,
        norm_in_range=norm_range,
        norm_in_kernel=norm_kernel,
        ratio_in_range=ratio_range,
        ratio_in_kernel=ratio_kernel,
        range_control_resonant=ctrl_res_frac,
        range_control_nonresonant=ctrl_nonres_frac,
        threshold=float(threshold),
        verdict=verdict,
        notes=notes,
    )