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

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© 2026 TNFR project — MIT licensed.DOI 10.5281/zenodo.17602860
docs
grammar
PHYSICS_VERIFICATION.md
API_CONTRACTS.mdCANONICAL_OZ_SEQUENCES.mdEMPIRICAL_CONFRONTATION_EEG.mdREADME.mdSTRUCTURAL_FIELDS_TETRAD.mdSTRUCTURAL_INTERFACE_THEORY.md
theory
APPLIED_STRUCTURAL_ANALYSIS.mdCATALOG_TYPE_HYGIENE_PROGRAMME.mdDISSIPATIVE_AND_OPEN_SYSTEMS.mdEMERGENT_ONTOLOGY.mdEXTENDED_FIELDS_AND_DERIVED_QUANTITIES.mdFUNDAMENTAL_THEORY.mdGAUGE_SYMMETRY_AND_UNIFICATION.mdGLOSSARY.mdMATHEMATICAL_DYNAMICS_BASIS.mdMINIMAL_STRUCTURAL_DEGREES.mdNUCLEUS_A_PRIME_LADDER_ATLAS.mdNUCLEUS_B_EQUIVARIANCE_OBSTRUCTIONS.mdPHYSICAL_REGIME_CORRESPONDENCES.mdREADME.mdREMESH_INFINITY_DERIVATION.mdSTRUCTURAL_CONSERVATION_THEOREM.mdSTRUCTURAL_OPERATORS.mdSTRUCTURAL_STABILITY_AND_DYNAMICS.mdTNFR_BSD_RESEARCH_NOTES.mdTNFR_HODGE_RESEARCH_NOTES.mdTNFR_NAVIER_STOKES_RESEARCH_NOTES.mdTNFR_NUMBER_THEORY.mdTNFR_P_VS_NP_RESEARCH_NOTES.mdTNFR_RIEMANN_RESEARCH_NOTES.mdTNFR_VARIATIONAL_PRINCIPLE.mdTNFR_YANG_MILLS_RESEARCH_NOTES.mdTNFR.pdfUNIFIED_GRAMMAR_RULES.md
factorization-lab
analysis
analyze_patterns.pycertificate_manifest.py
benchmarks
benchmark_analysis.pybenchmark_expansion_suite.pyfull_spectrum_factorization.pypaley_gap_extended.pypaley_gap_smoke.pytest_benchmark_suite.py
demos
experiment_contexts
exp_0b1663cd19b7.jsonexp_0bf0054b7474.jsonexp_75a4c8ca616a.jsonexp_848ee0fd1857.jsonexp_f6fe00562193.jsonexp_fdf3da424e1e.json
failure_telemetry_batch.pyfeedback_integration_demo.pyintegration_demo_snapshots.dbseed_management_integration_demo.pysnapshot_integration_demo.pytrajectory_143.jsontrajectory_77.jsontrajectory_89.jsontrajectory_91.jsontrajectory_97.json
docs
FACTORING_PLAYBOOK.mdFALSE_POSITIVE_TEST_SUITE.mdOPERATOR_CERTIFICATES.mdROADMAP.mdSPECTRAL_ROUTE.md
experiment_contexts
exp_cebe1d9e7d8e.json
notebooks
spectral_history.ipynb
scripts
run_false_positive_tests.py
tests
run_false_positive_test_suite.pytest_cli.pytest_false_positive_methodology.pytest_false_positive_verifier.pytest_feedback_integration.pytest_partitioning.pytest_seed_management.pytest_self_opt_support.pytest_snapshot_system.pytest_spectral_paley.pytest_verification_robustness.py
tnfr_factorization
__init__.pyapi.pycli.pyfailure_telemetry.pyfeedback_adapter.pyfeedback_integration.pypartitioning.pyself_opt_support.pyspectral_paley.py
demo_snapshots.dbLICENSE_SNAPSHOT.mdPACKAGE_SUMMARY.mdREADME.mdseed_management.pysnapshot_system.pytest_certificate_hashing.pytest_installation.pyverification_trajectory_77.json
benchmarks
analyze_tetrad_universality.pyb0star_alpha_canonical_product_graphs.pybenchmark_optimization_tracks.pybenchmark_utils.pyboundary_vibration.pybridge_primes_riemann.pychiral_involution.pycli_utils.pycoherence_projector_sense_index.pycommutant_bridge.pycomposition_arithmetic.pyconfinement_zones_test.pyconservation_law_validation.pydirected_paley_bridge.pyemergent_arithmetic_pulse.pyemergent_atom_dynamics.pyemergent_atomic_shells.pyemergent_base_dimension.pyemergent_dimension_dynamics.pyemergent_fractal_pulse.pyemergent_fractal_simplex_dimension.pyemergent_integers_symmetry.pyemergent_musical_nfr.pyemergent_nfr_geometry.pyemergent_nfr_where.pyemergent_rationals.pyemergent_rhythm.pyemergent_screening.pyemergent_shell_cardinals.pyemergent_shell_ordering.pyemergent_simplex_dimension.pyemergent_substrate_symmetry.pyequivariance_wall.pyexternal_phase_gate_validation.pyfield_methods_battery.pygolden_residue_remesh_bridge.pyintegrated_force_regime_study.pyinverse_spectrum_to_symmetry.pyk_phi_safety_demo.pykuramoto_farey_bridge.pymissing_piece_bridge.pymultichannel_interface_benchmark.pynavier_stokes_recipe_bridge.pynodal_propagator_residue_bridge.pyns_moment_hierarchy_cascade.pyoperational_irreducibility.pypaley_bridge.pyphase_curvature_investigation.pyphase_wall.pyphi_s_confinement_investigation.pyprimes_as_consequence.pypulse_phase_coherence_budget.pyREADME.mdremesh_infinity_riemann_baseline.pyremesh_infinity_riemann_composed.pyremesh_infinity_riemann_modified_graph.pyremesh_infinity_riemann_operator.pyremesh_infinity_riemann_spectral_basis.pyremesh_infinity_riemann_spectral_robustness.pyremesh_infinity_riemann_spectral.pyresidue_phase_vs_riemann.pystructural_interface_benchmark.pytemporal_interface_benchmark.pytetrad_results_aggregate.pyu2_destabilization_irreversibility.pyuniversality_clusters.pyxi_c_fast_experiment.py
primality-test
benchmarks
comprehensive_benchmark.py
docs
ADVANCED_INTEGRATION.mdmathematical_foundation.mdperformance_analysis.md
examples
advanced_examples.pybasic_usage.py
tnfr_primality
__init__.py__main__.pyadvanced_cli.pyadvanced_core.pycli.pyconstants.pycore.pyoptimized.py
MANIFEST.inPACKAGE_SUMMARY.mdREADME.mdRELEASE_NOTES_v1.0.mdsetup.pytest_installation.py
tests
core_physics
__init__.pytest_conservation_laws.pytest_delta_nfr_computation_paths.pytest_delta_nfr.pytest_dispersion_coherence_sign_invariance.pytest_emergent_constants_guard.pytest_lyapunov_operators.pytest_nodal_equation.pytest_structural_triad.py
data
replay_manifests
sample_run
_manifest_summary.json_manifest.json_partition_files.txt.gz
self_opt_validation
seed_alpha
paley.json
seed_beta
integration.json
seed_gamma
unknown.json
self_optimization
test_run
partitioned
test_run
test_run_p0.jsontest_run_p1.json
_manifest_summary.json_manifest.json
engines
test_pattern_discovery_manifest.pytest_self_optimization_engine.py
mathematics
__init__.pytest_autodiff.pytest_backends.pytest_dissipative_dynamics.pytest_epi.pytest_factory_patterns.pytest_metrics.pytest_navier_stokes_refounded.pytest_number_theory_canonical.pytest_operators.pytest_residue_networks.pytest_riemann_nodal_pulse.pytest_riemann_pulse_coherence.pytest_spaces.pytest_transforms.pytest_validator.py
operators
test_canonical_operators_modern.pytest_grammar_canon.pytest_grammar_canonical_consistency.pytest_grammar_dynamics.pytest_operator_contracts.pytest_operator_strategies.py
parallel
test_fractal_partition_manifest.py
physics
test_conservation_gauge_unification.pytest_dissipative_conservation.pytest_emergent_chemistry.pytest_field_cache_invalidation.pytest_gauge.pytest_phase_transition.pytest_signatures.pytest_spectral_conservation.pytest_structural_diffusion.pytest_structural_integrity.pytest_symplectic_substrate.pytest_tetrad_bounds.pytest_variational.pytest_yang_mills_closure.pytest_yang_mills_derivability.pytest_yang_mills_scaling.pytest_yang_mills_structural_gap.pytest_yang_mills_u6_sweep.py
scripts
test_run_self_opt_validation.pytest_run_self_optimization.py
sdk
__init__.pytest_simple_advanced.py
__init__.pyconftest.pyREADME.mdtest_breast_cancer_phase_gate_demo.pytest_classical_mechanics.pytest_distributed_fft.pytest_external_phase_gate_validation.pytest_factorization_entrypoint.pytest_multichannel_interface.pytest_nodal_optimizer.pytest_phase_gate_api.pytest_replay_register_manifest.pytest_signal_confrontation.pytest_structural_interface_api.pytest_structural_interface_baselines.pytest_structural_interface_benchmark.pytest_temporal_interface.pytest_vectorized_coherence_length_regression.pytest_wine_quality_phase_gate_demo.pyutils.py
examples
01_foundations
01_hello_world.py02_musical_resonance.py03_network_formation.py04_operator_sequences.py05_coherence_evolution.py06_network_topologies.py07_phase_transitions.py08_emergent_phenomena.py09_visualization_suite.py10_simplified_sdk_showcase.py
02_physics_regimes
11_classical_limit_comparison.py115_operator_contract_audit.py12_classical_mechanics_demo.py13_quantum_mechanics_demo.py14_uncertainty_and_interference.py15_train_crossing_demo.py17_conservation_law_demo.py26_gauge_structure_demo.py27_variational_principle_demo.py28_dissipative_systems_demo.py29_lyapunov_stability_demo.py30_self_optimization_demo.py31_mathematical_constants_basis.py33_complex_field_unification.py34_conservation_protocol_suite.py35_tetrad_irreducibility.py36_grammar_violation_detector.py37_operator_tetrad_synergy.py38_grammar_energy_landscape.py39_nodal_equation_decomposition.py
03_riemann_zeta
157_nodal_pulse_phase_attack.py41_von_mangoldt_zeta_demo.py42_riemann_zeros_as_resonances.py43_prime_ladder_hamiltonian_demo.py44_weil_explicit_formula_demo.py45_li_keiper_demo.py46_weil_tnfr_positivity_demo.py47_alpha_sweep_demo.py48_admissible_family_sweep_demo.py49_nodeaware_gauge_sweep_demo.py50_uniform_coercivity_demo.py51_adaptive_coercivity_demo.py52_paley_gap_coercivity_demo.py53_lyapunov_spectral_positivity_demo.py54_hilbert_polya_demo.py55_structural_zero_density_demo.py56_spectral_emergence_demo.py57_admissible_rescaling_demo.py58_oscillatory_correction_demo.py
04_riemann_L_twisted
59_dirichlet_l_function_demo.py60_dirichlet_l_continuation_demo.py61_dirichlet_l_hamiltonian_demo.py62_dirichlet_weil_explicit_formula_demo.py63_dirichlet_li_keiper_demo.py64_twisted_weil_positivity_demo.py65_twisted_alpha_sweep_demo.py66_twisted_admissible_family_sweep_demo.py67_twisted_nodeaware_gauge_sweep_demo.py68_twisted_hermite_family_demo.py69_twisted_coercivity_uniform_demo.py70_twisted_paley_gap_coercivity_demo.py71_twisted_lyapunov_spectral_demo.py72_twisted_hilbert_polya_demo.py73_twisted_structural_zero_density_demo.py74_twisted_spectral_emergence_demo.py75_twisted_admissible_rescaling_demo.py76_twisted_oscillatory_correction_demo.py
05_type_hygiene
77_remesh_infinity_residue_split_demo.py78_nuf_type_signature_demo.py79_epi_type_signature_demo.py80_phi_type_signature_demo.py81_dnfr_type_signature_demo.py82_remesh_window_type_signature_demo.py83_delta_phi_max_type_signature_demo.py84_coupling_weights_type_signature_demo.py85_tetrad_closure_signature_demo.py86_currents_closure_signature_demo.py87_aggregates_closure_signature_demo.py88_urules_consistency_signature_demo.py89_operator_catalog_discipline_signature_demo.py
06_navier_stokes
158_navier_stokes_two_face_refounded.py
07_number_theory
100_prime_families_orbits.py101_numbers_as_coupled_network.py102_nodal_flow_primes_equilibria.py116_nuf_emergent_prime_visibility.py146_primality_grammatical_inertness.py147_numbers_as_free_monoid_words.py148_capacity_arm_carries_von_mangoldt.py149_p14_is_the_capacity_arm_operator.py153_structural_frequency_rank_cyclotomy.py40_arithmetic_number_theory.py94_generative_number_construction.py95_primes_from_spectral_waves.py96_spectral_vibration_of_coherence.py97_goldbach_additive_multiplicative.pyemergent_chemistry_particles_demo.py
08_emergent_geometry
103_emergent_substrate_meets_riemann.py106_per_node_polarization_geometry.py107_orthogonal_structure_emergent_geometry.py108_emergent_field_generating_structure.py112_structure_predicts_coherence_flow.py113_overdamped_projection_bridge.py114_substrate_conserved_quantities.py117_emergent_geometry_residue_graph.py118_emergent_vs_classical_operator.py119_phase_sector_directed_residue.py120_symmetry_wall_substrate_vs_spectrum.py121_canonical_symmetry_break_negative.py122_factorization_phase_sector.py123_symmetry_sector_decomposition.py124_emergent_metric_fractal_consistency.py125_node_is_the_emergent_substrate.py126_two_layers_base_fiber.py127_base_is_emergent_not_imposed.py128_base_substrate_coemergence.py129_spectral_gap_base_fiber_clock.py130_operators_break_substrate_charges.py131_coemergent_loop_convergence.py132_geometric_phase_holonomy.py133_psi_topological_defects.py134_spectral_dimension_heat_kernel.py135_arrow_of_time_h_theorem.py136_heat_kernel_coefficients.py137_synchronization_transition.py138_structure_frequency_synchronization.py139_grammar_formal_language.py140_grammar_automaton.py141_grammar_rule_decomposition.py142_grammar_operator_quotient.py143_glyphic_function_sublanguage.py144_branching_combinator.py145_syntactic_monoid_starfree.py150_emergent_grammatical_pattern_parry.py151_grammar_in_emergent_geometry.py152_operator_contract_tetrahedron.py154_conductor_annotated_qr_spectrum.py155_ontological_position_of_numbers.py156_emergence_directness_law.py98_emergent_symplectic_substrate.py99_structural_diffusion.pyunified_fields_showcase.py
09_millennium
109_p_vs_np_coherence_synthesis.py110_bsd_rank_structural_pressure.py111_hodge_discrete_and_honest_gap.py
10_applications
159_empirical_confrontation_pipeline.py90_phase_gate_monitor_demo.py91_breast_cancer_phase_gate_demo.py92_wine_quality_phase_gate_demo.py93_structural_interface_demo.pypytorch_cuda_demo.py
README.md
scripts
replay
__init__.pyregister_manifest.py
__init__.pyREADME.mdrebuild_failure_manifest.pyrun_reproducible_benchmarks.pyrun_self_opt_validation.pyrun_self_optimization.pytnfr_is_prime.pyvalidate_conservation_law.pyverify_internal_references.py
src
core
__init__.pyevaluation.py
tnfr
backends
__init__.pyjax_backend.pynumpy_backend.pyoptimized_numpy.pyREADME.mdtorch_backend.py
cli
__init__.py__init__.pyiarguments.pyarguments.pyiexecution.pyexecution.pyiinteractive_validator.pyREADME.mdutils.pyutils.pyi
compat
__init__.pydataclass.pyjsonschema_stub.pymatplotlib_stub.pynumpy_stub.pyREADME.md
config
__init__.py__init__.pyiconstants.pyconstants.pyidefaults_core.pydefaults_init.pydefaults_metric.pydefaults.pyfeature_flags.pyfeature_flags.pyiglyph_constants.pyoperator_names.pyoperator_names.pyiphysics_derivation.pyprecision_modes.pypresets.pypresets.pyiREADME.mdsecurity.pythresholds.pytnfr_config.py
constants
__init__.py__init__.pyialiases.pyaliases.pyicanonical.pymetric.pymetric.pyioperational.py
core
__init__.pycontainer.pydefault_implementations.pyexceptions.pyinterfaces.pyREADME.md
dynamics
__init__.py__init__.pyiadaptation.pyadaptation.pyiadaptive_sequences.pyadaptive_sequences.pyiadelic.pyadvanced_cache_optimizer.pyadvanced_fft_arithmetic.pyaliases.pyaliases.pyibifurcation.pycache_aware_fft_engine.pycanonical.pycanonical.pyicomputational_hub.pycoordination.pycoordination.pyidistributed_fft.pydnfr.pydnfr.pyidynamic_limits.pyemergent_centralization.pyemergent_integration_engine.pyfeedback.pyfeedback.pyifft_backend.pyfft_cache_coordinator.pyfft_dispatchers.pyfft_engine.pyfft_workers.pyfused_dnfr.pyhomeostasis.pyhomeostasis.pyiintegrators.pyintegrators.pyilearning.pylearning.pyimetabolism.pymulti_modal_cache.pynbody_tnfr.pynbody.pynodal_optimizer.pyoptimization_orchestrator.pypropagation.pyREADME.mdruntime.pyruntime.pyisampling.pysampling.pyiselectors.pyselectors.pyiself_optimizing_engine.pyspectral_structural_fusion.pystructural_cache.pystructural_clip.pysymplectic.pyunified_backend.pyunified_mathematical_cache_orchestrator.py
engines
computation
__init__.pyfft_engine.pyunified_fft_engine.pyunified_gpu_system.py
constants
__init__.pycanonical.pyoperational.py
integration
__init__.pyemergent_integration.py
pattern_discovery
__init__.pymathematical_patterns.pymulti_modal_cache.py
self_optimization
__init__.pyengine.py
__init__.pyREADME.md
errors
__init__.pycontextual.py
factorization
__init__.py
flatten
README.md
gamma
README.md
glyph_history
README.md
glyph_runtime
README.md
immutable
README.md
initialization
README.md
io
README.md
math
__init__.pyfields_symbolic.pygrammar_validators.pyoptimizer.pyREADME.mdsymbolic.py
mathematics
__init__.pybackend.pybackend.pyidynamics.pydynamics.pyiepi.pyepi.pyigenerators.pygenerators.pyiliouville.pymetrics.pymetrics.pyinumber_theory.pyoperators_factory.pyoperators_factory.pyioperators.pyoperators.pyioptimized_primality.pyprojection.pyprojection.pyiREADME.mdruntime.pyruntime.pyispaces.pyspaces.pyispectral.pytransforms.pytransforms.pyiunified_cache.pyunified_numerical.pyzeta.py
metrics
__init__.py__init__.pyibuffer_cache.pybuffer_cache.pyicache_utils.pycoherence.pycoherence.pyicommon.pycommon.pyicore.pycore.pyidiagnosis.pydiagnosis.pyiemergence.pyexport.pyexport.pyiglyph_timing.pyglyph_timing.pyilearning_metrics.pylearning_metrics.pyilocal_coherence.pyphase_coherence.pyphase_compatibility.pyREADME.mdreporting.pyreporting.pyisense_index.pysense_index.pyitelemetry.pytetrad.pytrig_cache.pytrig_cache.pyitrig.pytrig.pyi
multiscale
__init__.pyhierarchical.pyREADME.md
navier_stokes
__init__.pyconservative_face.pyoperator.py
node
README.md
observers
README.md
operators
network_analysis
__init__.pysource_detection.py
postconditions
__init__.pymutation.py
preconditions
__init__.pycoherence.pydissonance.pyemission.pymutation.pyreception.pyresonance.py
strategies
__init__.pydefaults.pygpu_strategies.pystrategy.py
__init__.py__init__.pyialgebra.pycanonical_patterns.pycascade.pycoherence.pycontraction.pycoupling.pycycle_detection.pydefinitions_base.pydefinitions.pydefinitions.pyidissonance.pyemission.pyexpansion.pygrammar_application.pygrammar_canon.pygrammar_context.pygrammar_core.pygrammar_dynamics.pygrammar_error_factory.pygrammar_memoization.pygrammar_patterns.pygrammar_telemetry.pygrammar_types.pygrammar_u6.pygrammar_validate.pygrammar.pygrammar.pyihamiltonian.pyhealth_analyzer.pyintrospection.pyjitter.pyjitter.pyilifecycle.pymetabolism.pymetrics_basic.pymetrics_core.pymetrics_network.pymetrics_structural.pymetrics_u6.pymetrics.pymutation.pynodal_equation.pyoperator_contracts.pypattern_detection.pypatterns.pyREADME.mdreception.pyrecursivity.pyregistry.pyregistry.pyiremesh.pyremesh.pyiresonance.pyself_organization.pysilence.pystructural_units.pytransition.py
parallel
__init__.pyauto_scaler.pydistributed.pyengine.pymonitoring.pypartitioner.pyREADME.md
performance
guardrails.py
physics
__init__.py_helpers.pycalibration.pycanonical.pycell.pyclassical_mechanics.pyconservation_gauge_unification.pyconservation.pydissipative_conservation.pyemergent_chemistry.pyemergent_particles.pyextended.pyfields.pygauge.pyintegrity.pyinteractions.pylife.pylyapunov.pypatterns.pyphase_transition.pyquantum_mechanics.pyREADME.mdsignatures.pyspectral_conservation.pyspectral_metrics.pystructural_diffusion.pysymplectic_substrate.pytelemetry.pyunified.pyvariational.pyvectorized_ops.py
primality
__init__.py
recipes
__init__.pycookbook.pyREADME.md
riemann
__init__.pyadmissible_family_sweep.pyadmissible_rescaling.pyaggregates_closure_signature.pyalpha_sweep.pyanalytic_continuation_dirichlet.pyanalytic_continuation.pycoercivity_uniform.pycoupling_weights_type_signature.pycurrents_closure_signature.pydelta_phi_max_type_signature.pydirichlet_l.pydnfr_type_signature.pyepi_type_signature.pyhilbert_polya.pyli_keiper.pylyapunov_spectral_positivity.pynodal_pulse.pynodeaware_gauge_sweep.pynuf_type_signature.pyoperator_catalog_discipline_signature.pyoperator.pyoscillatory_correction.pypaley_gap_coercivity.pyphi_type_signature.pyprime_ladder_hamiltonian.pypulse_coherence.pyremesh_infinity_residue_split.pyremesh_window_type_signature.pyspectral_emergence.pystructural_zero_density.pytelemetry.pytetrad_closure_signature.pytwisted_admissible_family_sweep.pytwisted_admissible_rescaling.pytwisted_alpha_sweep.pytwisted_coercivity_uniform.pytwisted_hermite_family.pytwisted_hilbert_polya.pytwisted_li_keiper.pytwisted_lyapunov_spectral_positivity.pytwisted_nodeaware_gauge_sweep.pytwisted_oscillatory_correction.pytwisted_paley_gap_coercivity.pytwisted_prime_ladder_hamiltonian.pytwisted_spectral_emergence.pytwisted_structural_zero_density.pytwisted_weil_explicit_formula.pytwisted_weil_positivity.pyurules_consistency_signature.pyvon_mangoldt.pyweil_explicit_formula.pyweil_positivity.py
schemas
__init__.pygrammar.jsonREADME.md
sdk
__init__.py__init__.pyiadaptive_system.pyadaptive_system.pyibuilders.pybuilders.pyifluent.pyfluent.pyiREADME.mdself_opt.pysimple.pytemplates.pytemplates.pyiutils.py
security
__init__.pycrypto.pydatabase.pyREADME.mdsubprocess.pyvalidation.py
sequencing
__init__.pypatterns.pyREADME.md
services
__init__.pyorchestrator.pyREADME.md
sparse
__init__.pyREADME.mdrepresentations.py
structural
README.md
telemetry
__init__.pycache_metrics.pycache_metrics.pyiconstants.pynu_f.pynu_f.pyiREADME.mdunified_telemetry_system.pyverbosity.pyverbosity.pyi
tools
__init__.pydomain_templates.pyREADME.mdsequence_generator.pytnfr_is_prime_cli_optimized.pytnfr_is_prime_cli.py
topology
__init__.pyasymmetry.pyREADME.md
utils
cache_layers.pycache.pycache.pyicallbacks.pycallbacks.pyichunks.pychunks.pyidata.pydata.pyifast_diameter.pygraph.pygraph.pyiinit.pyinit.pyiio.pyio.pyinumeric.pynumeric.pyiREADME.mdtopology.pyunified_cache.py
validation
__init__.py__init__.pyiaggregator.pybase.pycompatibility.pycompatibility.pyiconfig.pygraph.pygraph.pyihealth.pyinput_validation.pyinterface_baselines.pyinvariants.pymultichannel_interface.pyphase_gate.pyREADME.mdrules.pyrules.pyiruntime.pyruntime.pyisequence_validator.pysignal_confrontation.pysoft_filters.pysoft_filters.pyispectral.pyspectral.pyistructural_interface.pytemporal_interface.pyunified_validation_system.pyvalidator.pywindow.pywindow.pyi
visualization
__init__.pycascade_viz.pyhierarchy.pyREADME.mdsequence_plotter.py
yang_mills
__init__.pyclosure.pyderivability.pyscaling.pystructural_gap.pyu6_sweep.py
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tetrad_evaluator.py
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FILE: examples/07_number_theory/95_primes_from_spectral_waves.py

95_primes_from_spectral_waves.py

Example 95 — Primes from Spectral Waves

Reconstructs the prime-counting staircase ψ(x) as a superposition of spectral waves — one per Riemann zero — making tangible the duality

text
prime positions  ⟷  spectral geometry {γ_n}.

Physics

The Riemann–von Mangoldt explicit formula expresses the prime staircase ψ(x) = Σ_{p^k ≤ x} log p as

text
ψ(x) = x  −  Σ_n x^{ρ_n}/ρ_n  −  log(2π)  −  ½ log(1 − x^{-2})

with ρ_n = ½ + i·γ_n the non-trivial zeros. Each oscillatory term

text
x^{ρ_n}/ρ_n = (√x / |ρ_n|) · exp(i·γ_n·log x − i·arg ρ_n)

is a WAVE of angular frequency γ_n in the coordinate log x and amplitude √x/|ρ_n|. Primes appear where they do because their distribution is the Fourier synthesis of these spectral waves: the "coherence flow ordering itself" is literally the superposition of e^{i·γ_n·log x}.

Spectral coherence = Riemann Hypothesis

RH states Re(ρ_n) = ½ for EVERY zero. Then every wave has amplitude √x/|ρ_n| — uniformly bounded — and the staircase stays coherent (|ψ(x) − x| = O(√x log²x)). A single off-critical-line zero at Re = ½ + δ would inject a wave of amplitude x^{½+δ} that grows faster and DESTROYS the bound. So RH ⟺ "all spectral waves equally bounded" ⟺ the spectral geometry is maximally coherent.

Experiments

  1. Staircase synthesis: ψ(x) reconstructed from N = 5, 20, 80 zeros
  2. Wave decomposition: each zero as a bounded wave (√x/|ρ_n|, freq γ_n)
  3. Coherence ⟺ RH: on-line (Re=½) stays √x-bounded; off-line (Re=0.7) error grows like x^{0.7} — incoherent

Honest scope

This REPRODUCES the classical explicit formula (Riemann 1859, von Mangoldt 1895); it is NOT a TNFR discovery. TNFR's contribution is to realise the prime-side spectrum as a self-adjoint prime-ladder Hamiltonian (P14, spectrum {k·log p}) and verify the identity to machine precision (P15). The "spectral geometry" is the geometry of an operator on the critical line — NOT physical space; no cosmological claim is made.

PROVING the geometry is coherent (all γ_n real ⟺ spectrum real ⟺ RH) is the OPEN problem. TNFR formalises it as Conjecture T-HP and supplies RH-equivalent coherence/positivity diagnostics (P16 Li–Keiper, P26 Lyapunov-spectral), but the residual oscillation S(T) = (1/π)·arg ζ(½+iT) — visible here as the slow N^{-1/2} convergence — is the genuine obstruction. The TNFR-Riemann program is PAUSED at this boundary; G4 = RH remains open. Coincidence of names ("coherence", "sense") with the TNFR metrics C(t), Si is suggestive but is NOT a proof: see the closing notes.

References

  • theory/TNFR_NUMBER_THEORY.md §10 (prime path graphs, Riemann link)
  • theory/TNFR_RIEMANN_RESEARCH_NOTES.md §13septies (Conjecture T-HP)
  • src/tnfr/riemann/analytic_continuation.py (P13 explicit formula)
  • src/tnfr/riemann/prime_ladder_hamiltonian.py (P14 spectrum {k log p})
  • AGENTS.md §"TNFR-Riemann Program Overview" (status, open G4)

Source Code

python
#!/usr/bin/env python3
"""
Example 95 — Primes from Spectral Waves
========================================

Reconstructs the prime-counting staircase ψ(x) as a superposition of
spectral waves — one per Riemann zero — making tangible the duality

    prime positions  ⟷  spectral geometry {γ_n}.

Physics
-------
The Riemann–von Mangoldt explicit formula expresses the prime staircase
ψ(x) = Σ_{p^k ≤ x} log p as

    ψ(x) = x  −  Σ_n x^{ρ_n}/ρ_n  −  log(2π)  −  ½ log(1 − x^{-2})

with ρ_n = ½ + i·γ_n the non-trivial zeros. Each oscillatory term

    x^{ρ_n}/ρ_n = (√x / |ρ_n|) · exp(i·γ_n·log x − i·arg ρ_n)

is a WAVE of angular frequency γ_n in the coordinate log x and amplitude
√x/|ρ_n|. Primes appear where they do because their distribution is the
Fourier synthesis of these spectral waves: the "coherence flow ordering
itself" is literally the superposition of e^{i·γ_n·log x}.

Spectral coherence = Riemann Hypothesis
---------------------------------------
RH states Re(ρ_n) = ½ for EVERY zero. Then every wave has amplitude
√x/|ρ_n| — uniformly bounded — and the staircase stays coherent
(|ψ(x) − x| = O(√x log²x)). A single off-critical-line zero at
Re = ½ + δ would inject a wave of amplitude x^{½+δ} that grows faster
and DESTROYS the bound. So RH ⟺ "all spectral waves equally bounded"
⟺ the spectral geometry is maximally coherent.

Experiments
-----------
1. Staircase synthesis: ψ(x) reconstructed from N = 5, 20, 80 zeros
2. Wave decomposition: each zero as a bounded wave (√x/|ρ_n|, freq γ_n)
3. Coherence ⟺ RH: on-line (Re=½) stays √x-bounded; off-line (Re=0.7)
   error grows like x^{0.7} — incoherent

Honest scope
------------
This REPRODUCES the classical explicit formula (Riemann 1859, von
Mangoldt 1895); it is NOT a TNFR discovery. TNFR's contribution is to
realise the prime-side spectrum as a self-adjoint prime-ladder
Hamiltonian (P14, spectrum {k·log p}) and verify the identity to machine
precision (P15). The "spectral geometry" is the geometry of an operator
on the critical line — NOT physical space; no cosmological claim is made.

PROVING the geometry is coherent (all γ_n real ⟺ spectrum real ⟺ RH) is
the OPEN problem. TNFR formalises it as Conjecture T-HP and supplies
RH-equivalent coherence/positivity diagnostics (P16 Li–Keiper, P26
Lyapunov-spectral), but the residual oscillation S(T) = (1/π)·arg ζ(½+iT)
— visible here as the slow N^{-1/2} convergence — is the genuine
obstruction. The TNFR-Riemann program is PAUSED at this boundary; G4 = RH
remains open. Coincidence of names ("coherence", "sense") with the TNFR
metrics C(t), Si is suggestive but is NOT a proof: see the closing notes.

References
----------
- theory/TNFR_NUMBER_THEORY.md §10 (prime path graphs, Riemann link)
- theory/TNFR_RIEMANN_RESEARCH_NOTES.md §13septies (Conjecture T-HP)
- src/tnfr/riemann/analytic_continuation.py (P13 explicit formula)
- src/tnfr/riemann/prime_ladder_hamiltonian.py (P14 spectrum {k log p})
- AGENTS.md §"TNFR-Riemann Program Overview" (status, open G4)
"""

import math
import os
import sys

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

from tnfr.riemann.analytic_continuation import (
    fetch_riemann_zeros,
    reconstruct_psi_via_explicit_formula,
)


# ============================================================================
# EXPERIMENT 1: Staircase synthesis from spectral waves
# ============================================================================
def experiment_1_staircase_synthesis():
    """Reconstruct ψ(x) from increasing numbers of spectral modes."""
    print("=" * 72)
    print("EXPERIMENT 1: Prime Staircase from Spectral Waves")
    print("=" * 72)
    print()
    print("ψ(x) = x − Σ_n x^{ρ_n}/ρ_n − log(2π) − ½log(1−x^{-2})")
    print("Each Riemann zero adds one wave. More zeros → sharper staircase.")
    print()

    xs = [10.5, 12.5, 16.5, 18.5, 22.5, 28.5]
    zeros80 = fetch_riemann_zeros(80)
    res = {
        n: reconstruct_psi_via_explicit_formula(xs, zeros=list(zeros80[:n]))
        for n in (5, 20, 80)
    }

    print(f"{'x':>6}  {'ψ_true':>9}  {'N=5':>8}  {'N=20':>8}  {'N=80':>8}")
    print("-" * 50)
    for i, x in enumerate(xs):
        print(
            f"{x:>6.1f}  {res[80].psi_classical[i]:>9.3f}  "
            f"{res[5].psi_explicit[i]:>8.3f}  "
            f"{res[20].psi_explicit[i]:>8.3f}  "
            f"{res[80].psi_explicit[i]:>8.3f}"
        )

    print()
    for n in (5, 20, 80):
        max_err = float(max(res[n].abs_error))
        print(f"  N={n:>3} zeros → max reconstruction error = {max_err:.3f}")
    print()
    print("Error shrinks with more spectral modes (slowly, ~N^{-1/2} — the")
    print("explicit formula converges only conditionally). Primes ARE the")
    print("synthesis of these waves.")
    print()


# ============================================================================
# EXPERIMENT 2: Each zero is a bounded spectral wave
# ============================================================================
def experiment_2_wave_decomposition():
    """Show each zero as a wave: amplitude √x/|ρ|, frequency γ_n."""
    print("=" * 72)
    print("EXPERIMENT 2: Each Zero is a Spectral Wave")
    print("=" * 72)
    print()
    print("x^{ρ}/ρ = (√x/|ρ|)·exp(i·γ·log x − i·arg ρ)  with ρ = ½ + i·γ")
    print("→ amplitude √x/|ρ|, angular frequency γ in the log-x coordinate.")
    print()

    x = 100.5
    zeros = fetch_riemann_zeros(8)
    sqrt_x = math.sqrt(x)
    log_x = math.log(x)

    print(f"At x = {x}:  √x = {sqrt_x:.3f},  log x = {log_x:.4f}")
    print()
    print(
        f"{'n':>3}  {'γ_n':>9}  {'|ρ_n|':>8}  {'amplitude':>10}"
        f"  {'phase γ·logx':>12}"
    )
    print("-" * 54)
    for n, rho in enumerate(zeros, start=1):
        gamma = float(rho.imag)
        mod = abs(complex(0.5, gamma))
        amplitude = 2.0 * sqrt_x / mod  # factor 2 from ρ + conjugate
        phase = (gamma * log_x) % (2 * math.pi)
        print(
            f"{n:>3}  {gamma:>9.4f}  {mod:>8.4f}  {amplitude:>10.4f}"
            f"  {phase:>12.4f}"
        )

    print()
    print("Every amplitude scales as √x (NOT faster) because Re(ρ) = ½.")
    print("Lower zeros (small γ) carry the loudest waves; higher zeros add")
    print("fine detail. This is the spectral geometry of the primes.")
    print()


# ============================================================================
# EXPERIMENT 3: Spectral coherence ⟺ Riemann Hypothesis
# ============================================================================
def experiment_3_coherence_is_rh():
    """On-line zeros stay √x-bounded; off-line zeros grow like x^{Re}."""
    print("=" * 72)
    print("EXPERIMENT 3: Spectral Coherence ⟺ Riemann Hypothesis")
    print("=" * 72)
    print()
    print("RH: Re(ρ) = ½ for ALL zeros ⟹ every wave bounded by √x/|ρ| ⟹")
    print("coherent staircase. A hypothetical off-line zero (Re = 0.7)")
    print("injects a wave of amplitude x^{0.7} that breaks the bound.")
    print()

    xs = [20.5, 50.5, 100.5, 200.5]
    zeros = fetch_riemann_zeros(40)
    on = reconstruct_psi_via_explicit_formula(xs, zeros=list(zeros))
    off_zeros = [complex(0.7, r.imag) for r in zeros]
    off = reconstruct_psi_via_explicit_formula(xs, zeros=off_zeros)

    print(
        f"{'x':>7}  {'ψ_true':>9}  {'err ON (Re=½)':>13}"
        f"  {'err OFF (Re=.7)':>15}  {'√x':>7}  {'x^0.7':>8}"
    )
    print("-" * 72)
    for i, x in enumerate(xs):
        print(
            f"{x:>7.1f}  {on.psi_classical[i]:>9.2f}  "
            f"{on.abs_error[i]:>13.3f}  {off.abs_error[i]:>15.3f}  "
            f"{x ** 0.5:>7.2f}  {x ** 0.7:>8.2f}"
        )

    on_ratio = on.abs_error[-1] / on.abs_error[0]
    off_ratio = off.abs_error[-1] / off.abs_error[0]
    print()
    print(
        f"  Error growth (x: 20→200):  ON-line ×{on_ratio:.1f}"
        f"  vs  OFF-line ×{off_ratio:.1f}"
    )
    print()
    print("On-line error tracks √x (coherent). Off-line error tracks x^{0.7}")
    print("(incoherent — diverges faster). RH ⟺ the spectral geometry is")
    print("maximally coherent: all waves share the same √x envelope.")
    print()


def main():
    print()
    print("  TNFR Example 95: Primes from Spectral Waves")
    print("  prime positions ⟷ spectral geometry {γ_n}")
    print("  ==========================================")
    print()

    experiment_1_staircase_synthesis()
    experiment_2_wave_decomposition()
    experiment_3_coherence_is_rh()

    print("=" * 72)
    print("HONEST SCOPE & THE COHERENCE QUESTION")
    print("=" * 72)
    print()
    print("This demo REPRODUCES the classical Riemann–von Mangoldt explicit")
    print("formula. TNFR realises the prime side as a self-adjoint")
    print("prime-ladder Hamiltonian (P14, spectrum {k·log p}) and verifies")
    print("the identity to machine precision (P15).")
    print()
    print("RH is literally a COHERENCE statement: the spectral geometry is")
    print("coherent ⟺ every γ_n is real ⟺ the operator is self-adjoint ⟺")
    print("all waves share the √x envelope (Experiment 3).")
    print()
    print("Is this what TNFR's C(t) / Sense Index (Si) can prove? The name")
    print("coincidence is suggestive but is NOT itself a proof:")
    print("  - C(t) = 1/(1 + mean|ΔNFR| + mean|dEPI|) and Si are metrics of")
    print("    a network's dynamic coherence, with specific formulas.")
    print("  - RH-coherence is the reality of an operator's spectrum.")
    print("  - Equating them is exactly Conjecture T-HP (§13septies): does a")
    print("    canonical operator built from the tetrad + (φ,γ,π,e) + U1-U6")
    print("    have spectrum {γ_n}? That would make RH a TNFR coherence")
    print("    theorem.")
    print("  - TNFR already pursued this: P16 (Li–Keiper positivity) and P26")
    print("    (Lyapunov-spectral positivity) are RH-equivalent coherence")
    print("    diagnostics. The residual S(T) = (1/π)·arg ζ(½+iT) — the slow")
    print("    N^{-1/2} convergence seen in Experiment 1 — is the genuine")
    print("    obstruction (lives in Fix(S_n)^⊥, unreachable by the current")
    print("    canonical constructions).")
    print()
    print("Verdict: the intuition 'coherence proves the geometry' names the")
    print("RIGHT program (T-HP), but the current C(t)/Si metrics do NOT close")
    print("it. G4 = RH remains open; the program is paused at this boundary.")
    print()


if __name__ == "__main__":
    main()