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

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

emergent_screening.py

Emergent Screening? Does Phi_s self-consistency turn the spherical-well shells into the atomic periodic table -- without injecting quantum chemistry?

CONTEXT (from benchmarks/emergent_shell_ordering.py): pure TNFR structure gives the (2l+1) angular degeneracy, a radial-sum filling order, and -- with the emergent radial nucleus of a solid ball -- the INFINITE SPHERICAL WELL closures 2, 8, 18, 20, 34 (the independent-particle / nuclear shell family). The SOLE residual to the CHEMICAL periodic table (2, 10, 18, 36, 54, 86) was identified as electron-electron SCREENING. This benchmark asks whether that screening EMERGES from TNFR self-consistency, with no foreign theory.

MECHANISM (canonical, TNFR-native -- NOT Hartree-Coulomb): The occupied structural eigenmodes are co-resident sub-EPIs (U5 nesting). Each is a DeltaNFR source; their aggregate structural potential is the CANONICAL Phi_s field

text
  Phi_s(i) = sum_j rho(j) / d(i,j)^2,   rho = sum_occupied |psi_k|^2

i.e. the SAME inverse-square (alpha=2) kernel as compute_structural_potential (grammar U6) and classify_nodal_topology. Iterating the loop

text
  occupy lowest modes -> Phi_s -> shift operator -> re-diagonalise

to self-consistency is just the nodal dynamics acting back on co-resident sub-EPIs. The mechanism is canonical; WHAT IT PRODUCES is measured, not tuned. The mean field is symmetrised radially about the emergent nucleus (a screening field is radial), isolating the l-dependent reordering from discretisation noise.

WHAT EMERGES / WHAT DOES NOT (measured below):

  • A screening-LIKE effect DOES emerge: self-consistency lifts the (n,l) degeneracy and reorders the levels (the spherical-well "20" closure dissolves as coupling grows).
  • The ATOMIC order does NOT emerge: at no coupling do the noble-gas numbers appear; the Ne-like "10" closure (1s 2s 2p) never forms -- the first two closures stay 2, 8. The structural back-reaction is REPULSIVE, pushing core-penetrating radial modes (2s) UP, the OPPOSITE of atomic screening (which modulates an ATTRACTIVE nuclear well, absent from a bare manifold).

Run: python benchmarks/emergent_screening.py

Theoretical anchor: AGENTS.md (nodal equation; Phi_s structural potential, U6; discrete-mode regime). Builds on benchmarks/emergent_shell_ordering.py (solid_ball_graph, the emergent nucleus). Status: RESEARCH (falsifier).

Source Code

python
"""
Emergent Screening? Does Phi_s self-consistency turn the spherical-well shells
into the atomic periodic table -- without injecting quantum chemistry?
============================================================================

CONTEXT (from benchmarks/emergent_shell_ordering.py): pure TNFR structure gives
the (2l+1) angular degeneracy, a radial-sum filling order, and -- with the
emergent radial nucleus of a solid ball -- the INFINITE SPHERICAL WELL closures
2, 8, 18, 20, 34 (the independent-particle / nuclear shell family). The SOLE
residual to the CHEMICAL periodic table (2, 10, 18, 36, 54, 86) was identified
as electron-electron SCREENING. This benchmark asks whether that screening
EMERGES from TNFR self-consistency, with no foreign theory.

MECHANISM (canonical, TNFR-native -- NOT Hartree-Coulomb):
  The occupied structural eigenmodes are co-resident sub-EPIs (U5
  nesting). Each is a DeltaNFR source; their aggregate structural
  potential is the CANONICAL Phi_s field

      Phi_s(i) = sum_j rho(j) / d(i,j)^2,   rho = sum_occupied |psi_k|^2

  i.e. the SAME inverse-square (alpha=2) kernel as
  compute_structural_potential (grammar U6) and classify_nodal_topology.
  Iterating the loop

      occupy lowest modes -> Phi_s -> shift operator -> re-diagonalise

  to self-consistency is just the nodal dynamics acting back on
  co-resident sub-EPIs. The mechanism is canonical; WHAT IT PRODUCES is
  measured, not tuned. The mean field is symmetrised radially about the
  emergent nucleus (a screening field is radial), isolating the
  l-dependent reordering from discretisation noise.

WHAT EMERGES / WHAT DOES NOT (measured below):
  - A screening-LIKE effect DOES emerge: self-consistency lifts the (n,l)
    degeneracy and reorders the levels (the spherical-well "20" closure
    dissolves as coupling grows).
  - The ATOMIC order does NOT emerge: at no coupling do the noble-gas numbers
    appear; the Ne-like "10" closure (1s 2s 2p) never forms -- the first two
    closures stay 2, 8. The structural back-reaction is REPULSIVE, pushing
    core-penetrating radial modes (2s) UP, the OPPOSITE of atomic screening
    (which modulates an ATTRACTIVE nuclear well, absent from a bare manifold).

Run:
    python benchmarks/emergent_screening.py

Theoretical anchor: AGENTS.md (nodal equation; Phi_s structural potential, U6;
discrete-mode regime). Builds on benchmarks/emergent_shell_ordering.py
(solid_ball_graph, the emergent nucleus). Status: RESEARCH (falsifier).
"""

from __future__ import annotations

import pathlib
import sys

import networkx as nx
import numpy as np

_SRC = pathlib.Path(__file__).resolve().parents[1] / "src"
if str(_SRC) not in sys.path:
    sys.path.insert(0, str(_SRC))
_BENCH = pathlib.Path(__file__).resolve().parent
if str(_BENCH) not in sys.path:
    sys.path.insert(0, str(_BENCH))

from emergent_shell_ordering import solid_ball_graph  # noqa: E402
from tnfr.physics.emergent_chemistry import (  # noqa: E402
    structural_eigenmodes,
)
from tnfr.physics.fields import classify_nodal_topology  # noqa: E402

ATOMIC_NOBLE = [2, 10, 18, 36, 54, 86]
SPHERICAL_WELL = [2, 8, 18, 20, 34, 40, 58]


def phi_s_kernel(G: nx.Graph, nodes: list) -> np.ndarray:
    """Canonical Phi_s Green's function K(i,j) = 1/d(i,j)^2 (alpha=2)."""
    idx = {node: i for i, node in enumerate(nodes)}
    n = len(nodes)
    K = np.zeros((n, n))
    for node, dd in dict(nx.all_pairs_shortest_path_length(G)).items():
        i = idx[node]
        for j_node, d in dd.items():
            if d > 0:
                K[i, idx[j_node]] = 1.0 / (float(d) ** 2)
    return K


def radial_bins(G: nx.Graph, nodes: list) -> np.ndarray:
    """Graph-hop radius of each node from the emergent center (node 0)."""
    rad_of = nx.single_source_shortest_path_length(G, nodes[0])
    return np.array([rad_of[node] for node in nodes])


def _symmetrise(rho: np.ndarray, rvec: np.ndarray) -> np.ndarray:
    """Average a density within each radial shell (a radial mean field)."""
    out = np.zeros_like(rho)
    for r in np.unique(rvec):
        mask = rvec == r
        out[mask] = rho[mask].mean()
    return out


def _shell_mults(w: np.ndarray, ntop: int = 40, gap_factor: float = 4.0):
    """Group the lowest eigenvalues into degenerate shells; return sizes."""
    ev = np.sort(w)[:ntop]
    gaps = np.diff(ev)
    pos = gaps[gaps > 1e-9]
    typ = float(np.median(pos)) if pos.size else 1e-9
    thr = gap_factor * typ
    groups = [[ev[0]]]
    for i, e in enumerate(ev[1:]):
        if gaps[i] > thr:
            groups.append([e])
        else:
            groups[-1].append(e)
    return [len(g) for g in groups]


def scf_closed_shells(
    L: np.ndarray,
    K: np.ndarray,
    rvec: np.ndarray,
    g: float,
    *,
    z_modes: int = 30,
    iters: int = 20,
) -> list[int]:
    """Self-consistent Phi_s back-reaction; return cumulative closed-shell
    counts (running sum of mode capacities 2*mult after each shell)."""
    Leff = L.copy()
    for _ in range(iters):
        _, V = np.linalg.eigh(Leff)
        rho = (V[:, :z_modes] ** 2).sum(axis=1)
        rho = _symmetrise(rho, rvec)
        Leff = L + g * np.diag(K @ rho)
    w, _ = np.linalg.eigh(Leff)
    cum, total = [], 0
    for m in _shell_mults(w):
        total += 2 * m
        cum.append(total)
    return cum


def leading_overlap(seq: list[int], ref: list[int]) -> int:
    count = 0
    for a, b in zip(seq, ref):
        if a != b:
            break
        count += 1
    return count


def main() -> None:
    print("=" * 70)
    print("EMERGENT SCREENING? (Phi_s self-consistency; no QM injected)")
    print("=" * 70)

    G = solid_ball_graph(4, 16, 8)
    nodes = list(G.nodes())
    # NOTE: the base manifold operator here is the imposed combinatorial Laplacian
    # D - A; the canonical EMERGENT structural operator is L_rw = I - D^-1 W
    # (symmetric twin L_sym). A fully-emergent re-derivation of this screening
    # study on L_sym is future work; the Phi_s back-reaction kernel K below IS
    # canonical (U6).
    L = nx.laplacian_matrix(G, nodelist=nodes).toarray().astype(float)
    K = phi_s_kernel(G, nodes)
    rvec = radial_bins(G, nodes)

    print("\n[M1] Back-reaction kernel is the canonical Phi_s (alpha=2):")
    print("     V(i) = sum_j rho(j)/d(i,j)^2  (canonical U6 kernel)")
    print(f"     ball nucleus manifold: {len(nodes)} nodes, kernel {K.shape}")
    assert K.shape == (len(nodes), len(nodes))
    assert np.allclose(K, K.T), "Phi_s kernel must be symmetric"
    print("     -> PASS: mechanism = nodal dynamics on co-resident sub-EPIs.")

    cum0 = scf_closed_shells(L, K, rvec, 0.0)
    cum1 = scf_closed_shells(L, K, rvec, 1.0)
    print("\n[M2] Does self-consistency lift degeneracy / reorder?")
    print(f"     g=0.0 (independent particle): {cum0[:6]}")
    print(f"     g=1.0 (self-consistent)     : {cum1[:6]}")
    assert cum1 != cum0, "self-consistency had no effect"
    assert 20 in cum0 and 20 not in cum1, "spherical-well 20 not reordered"
    print("     -> PASS: a screening-LIKE effect emerges -- the")
    print("        spherical-well '20' closure dissolves; levels reorder.")

    print("\n[M3] Scan coupling g -- does the ATOMIC order ever emerge?")
    print("     g      cumulative closed-shell counts")
    best_atomic = 0
    ten_ever = False
    for g in [0.0, 0.5, 1.0, 2.0, 4.0]:
        cum = scf_closed_shells(L, K, rvec, g)
        best_atomic = max(best_atomic, leading_overlap(cum, ATOMIC_NOBLE))
        ten_ever = ten_ever or (10 in cum[:6])
        print(f"     {g:<5}  {cum[:7]}")
    print(f"     atomic noble gases          : {ATOMIC_NOBLE}")
    print(f"     spherical well (g=0 family) : {SPHERICAL_WELL}")
    print(f"\n     max leading atomic match: {best_atomic}/6; "
          f"Ne-like '10' closure seen: {ten_ever}")
    assert best_atomic <= 1, "atomic order unexpectedly emerged"
    assert not ten_ever, "the atomic '10' closure appeared"
    print("     -> PASS: NO coupling reproduces the atomic table; the '10'")
    print("        (1s 2s 2p) closure never forms. First closures stay 2, 8.")

    # -- M4: does the COMPLEMENT -- an attractive center -- emerge? ----------
    topo = classify_nodal_topology(G)
    center = topo["centers"][0]
    cphi = topo["centrality"][center]
    cvals = np.array(list(topo["centrality"].values()))
    mults = [s.multiplicity for s in
             structural_eigenmodes(G, max_modes=40, gap_factor=4.0)[:6]]
    print("\n[M4] Does an ATTRACTIVE center (DeltaNFR sink) emerge instead?")
    print(f"     nucleus Phi_s = {cphi:.1f}  (max {cvals.max():.1f}, "
          f"mean {cvals.mean():.1f})")
    print(f"     ball spectrum multiplicities : {mults}")
    assert abs(cphi - cvals.max()) < 1e-9, "nucleus is not the Phi_s maximum"
    assert mults[:3] == [1, 3, 5], "spectrum is not spherical-well"
    print("     -> PASS: the nucleus is the Phi_s MAXIMUM (repulsive for")
    print("        +DeltaNFR, NOT an attractive sink); the spectrum is the")
    print("        spherical WELL (2l+1), NOT hydrogenic (Coulomb 2n^2).")

    print("\n" + "=" * 70)
    print("VERDICT")
    print("=" * 70)
    print(
        "A screening-LIKE effect EMERGES: the canonical Phi_s\n"
        "  self-consistency (occupied sub-EPIs -> 1/d^2 potential ->\n"
        "  reshifted modes, iterated) lifts the (n,l) degeneracy and\n"
        "  reorders the levels. The mechanism is TNFR-native -- the nodal\n"
        "  dynamics acting back on co-resident sub-EPIs (U5), no quantum\n"
        "  chemistry injected.\n"
        "BUT the ATOMIC table does NOT emerge: at no coupling do the\n"
        "  noble-gas numbers appear; the Ne-like '10' closure never forms\n"
        "  (first closures stay 2, 8). The structural back-reaction is\n"
        "  REPULSIVE, pushing core-penetrating radial modes (2s) UP -- the\n"
        "  OPPOSITE of atomic screening, which modulates an ATTRACTIVE\n"
        "  nuclear Coulomb well (low-l penetrate -> see more unscreened\n"
        "  charge -> pulled DOWN). A bare repulsive coherence manifold has\n"
        "  no attractive nucleus, so the sign is wrong for atoms.\n"
        "IDENTIFICATION: BOTH atomic ingredients are measured NON-emergent\n"
        "  here: (M3) self-consistent screening has the REPULSIVE sign, and\n"
        "  (M4) the emergent nucleus is a Phi_s MAXIMUM (repulsive), not an\n"
        "  attractive DeltaNFR sink -- the spectrum is a box/spherical well,\n"
        "  not a Coulomb 2n^2 well. The periodic table needs a charged\n"
        "  many-body Coulomb system (attractive nucleus + screening that\n"
        "  modulates it); a single relaxing coherence manifold carries\n"
        "  neither. So the (n+l) postulate in emergent_chemistry stands."
    )


if __name__ == "__main__":
    main()