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Chapter 9 — Modeling Methods & Numerical Implementation
I. One-Sentence Goal
Provide an end-to-end numerical pathway from Catalog / Seeds to state evolution (Trajectory), then to spectroscopy L_nu / LC and propagation T_arr / Delta_T_arr—covering solver structure, step-size and convergence, thin/thick switching consistency tau_switch, concurrency and caching, benchmark suite and error semantics—so that implementations are auditable, reproducible, and comparable.
II. Scope & Non-Goals
- Covered: model expression and discretization strategy; time marching and event-driven updates (seed/trigger); spectral synthesis and propagation assembly; layered segmentation and corrections; consistency and error metrics (eta_T / tau_switch); concurrency and caching; benchmark tasks and pass criteria; logging and replayability.
- Not covered: re-deriving the equations of Chs. 3–6; replacing the uncertainty-propagation corpus of Ch. 12; instrument response and external observation pipelines.
III. Minimal Terms & Symbols
- Objects & state: Catalog, Seeds, Trajectory; state = { M, R, J, a_bh, SFR, Z, … }.
- Fields & environment: T_fil(x,t), Phi_T(x,t), grad_Phi_T(x,t); SeaProfile, Sigma_env.
- Propagation & path: n_eff(x,t,f) (dimensionless and ≥ 1), c_ref, path gamma(ell), measure d ell, endpoints { ell_i }.
- Luminosity & observables: L_nu(f), F_nu(f), LC(t), T_arr(f, gamma), Delta_T_arr(f1,f2, gamma).
- Consistency & thresholds: eta_T (two-form), tau_switch (thin/thick), eps_T (convergence), eta_w (thin-layer gate); energy closure R_env + T_trans + A_sigma = 1.
- Naming isolation: T_fil ≠ T_trans and n ≠ n_eff.
IV. End-to-End Modeling Roadmap
- Inputs: Catalog / Seeds, Phi_T / grad_Phi_T or T_fil + G(•), SeaProfile / Sigma_env, coords_spec / units_spec / metric_spec, c_ref (or CalibCref), f_grid, gamma.
- Time marching: advance state(t) on tgrid, applying Trigger updates at event times (Ch. 4).
- Spectral synthesis: from state(t) and params_sed, produce L_nu(f), then F_nu(f_obs) / LC(t) (Ch. 6).
- Propagation assembly: build n_eff = F(Φ_T, grad_Φ_T, ρ, f) + H_sea; detect { ell_i }; perform two-form segmented integrals for T_arr; compute Delta_T_arr.
- Audits: enforce T_arr ≥ L_path / c_ref; assert eta_T, tau_switch; check R_env + T_trans + A_sigma = 1; verify discretization convergence eps_T.
- Outputs: Trajectory / L_nu / F_nu / LC / T_arr / Delta_T_arr plus audit logs and a reproducibility bundle.
V. Solver Architecture & Pseudoflow
A. Unified main loop (object → spectrum → propagation)
for O in Catalog:
state = init_from_seed(O.Seed)
t = t0
while t < t_end:
state = advance_state(state, Phi_T, env, Δt) # S70-7…S70-10
if trigger_due(t): state = apply_trigger(state, event) # S70-2
L_nu = synthesize_spectrum(O, state, f_grid) # S70-10
n_eff = assemble_neff(Phi_T, grad_Phi_T, SeaProfile, f_grid)
ell_i = detect_interfaces(gamma, SeaProfile or Sigma_env)
T_arr = integrate_arrival(n_eff, gamma, ell_i, mode, c_ref)
ΔT_arr = arrival_delta(n_path_params, f1, f2, gamma, mode, c_ref)
audit_and_log(state, L_nu, n_eff, T_arr, ΔT_arr, ell_i)
t += Δt
B. Grid-first (field-first)
- Precompute Φ_T / grad_Φ_T and slowly varying n_common on a grid; interpolate n_eff(γ[k]) and integrate by segments.
- Note: use symmetric stencils near interfaces; forbid cross-interface interpolation; include { ell_i } explicitly in the integral.
C. Path-first
on thin layers.Delta_T_sigmaEvaluate Φ_T, grad_Φ_T along γ[k]; assemble n_eff(γ[k], f) per frequency; perform segmented integrals; invokeD. Hybrid
.accuracy vs throughputCache slow terms on a grid + refine in local path windows around layers/interfaces—balancingVI. Segmentation, Corrections & Multi-Path Composition
- Segmentation rule: γ(ell_i) ∈ (Sigma_env ∪ Sigma_sea); each segment stays within a single side-limit; include both endpoints; no cross-interface interpolation.
- Thin-layer correction: if Delta_k / L_char ≤ eta_w then Delta_T_sigma ≈ k_sigma • H(crossing); log trigger counts and amplitudes.
- Thick-layer volume integral: T_arr^{layer} = ∫_{layer} ( n_eff / c_ref ) d ell.
- Multi-path synthesis: T_arr_total = ∑_m w_m • T_arr[γ_m], with w_m normalized and derived from geometry and R_env, T_trans, A_sigma.
VII. Step-Size Control, Error Estimation & Convergence
- Three adaptive thresholds
Geometry curvature: ‖ d^2γ/dℓ^2 ‖ ≥ tau_geom
Medium variation: | d n_eff / dℓ | ≥ tau_medium
Layer strength: Xi_k(chi) ≥ tau_sea - Local error: per segment, use a two-order quadrature difference; count interface segments separately.
- Global convergence: | T_arr^{(fine)} − T_arr^{(coarse)} | ≤ eps_T; two-form eta_T within gate; thin/thick tau_switch within gate; lower bound holds at all times.
VIII. Thin/Thick Chain Selection & Consistency
- Criterion: Delta_k / L_char ≤ eta_w → thin; else thick.
- Debounce: dual-solve within the eta_w neighborhood and record tau_switch; if over gate, lock to thick and back-trace SeaProfile or endpoint tolerances.
- Implementation hint: cap sub-segment step length proportionally to Delta_k; symmetric sampling at endpoints reduces bias.
IX. Concurrency, Caching & Performance
- Axes of concurrency: object × frequency band × path; prioritize band and path parallelism.
- Caching policy: cache Φ_T / grad_Φ_T near paths; memoize { ell_i }, w_m, and Delta_T_sigma trigger statistics.
- I/O & persistence: store gridded fields as Zarr/NetCDF, trajectories & observations as JSONL/Parquet; hash-based content validation.
- Warm-start: reuse previous theta_hat and SeaProfile caches; skip cold-start where configurations are near-identical.
X. Benchmarks & Pass Criteria
- Benchmark 1 (uniform medium): n_eff ≡ 1 ⇒ T_arr = L_path / c_ref (dimension and lower-bound checks).
- Benchmark 2 (single thin band): tanh/logistic layer ⇒ | T_arr^{thick} − (T_arr^{thin}+ΔT_sigma) | = tau_switch within gate.
- Benchmark 3 (two concatenated layers): constant n_eff per layer + corrections; validate segmentation and endpoint inclusion.
- Benchmark 4 (directional channel, optional): enable b1 / b1_n; verify significance across azimuthal paths.
- Benchmark 5 (band dispersion): fit n_path polynomial; validate Delta_T_arr linear regime and OOB leakage.
- Pass conditions: all of eps_T, eta_T, tau_switch, energy closure, and the lower bound pass; logs complete.
XI. Error Semantics (aligned with the template error family)
- E-DIM-001 dimension inconsistency or missing units
- E-INTF-005 interface matching failure or parameter out of range
- E-QAD-006 quadrature fails to converge or eps_T unmet
- E-NEFF-003 n_eff < 1 or assembly failure
- E-CONSIST-008 two-form consistency failure (eta_T over gate)
- E-EO-010 thin/thick consistency failure (tau_switch over gate) or cross-interface interpolation
Handling: preserve intermediate logs and RNG seed; output a falsification sample and back-trace guidance (convention, segmentation, SeaProfile, step-size).
XII. Interfaces & Implementation Bindings (aligned with template I70-*)
- build_solver_config_EO(params) -> SolverCfg
- evolve_object_state(O, env, tgrid) -> Trajectory (I70-3)
- synthesize_spectrum(O, state, fgrid) -> L_nu (I70-4)
- predict_arrival_signature(n_eff, gamma, mode, c_ref) -> { T_arr, Delta_T_arr } (I70-6)
- detect_interfaces(gamma, Sigma_env or SeaProfile) -> { ell_i }
- segment_integrals(n_eff, gamma, { ell_i }, mode) -> { T_arr_i }, T_arr
- interface_correction_sea(gamma, SeaProfile, params) -> Delta_T_sigma
- consistency_dual_mode_EO(inputs) -> eta_T
- consistency_thin_vs_thick_EO(inputs) -> tau_report
- benchmark_suite_EO(runlist) -> Summary
- log_artifacts_EO(meta, hashes, metrics) -> Log
Constraints: entry dimension and lower-bound checks so dim(T_arr) = [T], dim(n_eff) = 1; record coords_spec / units_spec / metric_spec and thresholds.
XIII. Logging, Reproduction & Publication
- Minimal log: hash(Catalog/Seeds/Trajectory/SeaProfile/Phi_T/n_eff/gamma), coords_spec / units_spec / metric_spec, SolverCfg, mode, eps_T, eta_T, eta_w, tau_switch, interface_marks, Delta_T_sigma trigger stats, and R_env / T_trans / A_sigma summaries.
- Repro bundle: data + code + parameters + RNG seed + hash manifest + replay scripts.
- Publication: no external links in the main text; list references, hashes, and replay commands at the end of the report; attach falsification samples and back-trace handles.
XIV. Cross-References
- EFT.WP.Cosmo.EarlyObjects v1.0: Ch. 3 (minimal equations), Ch. 4 (seed/trigger), Ch. 5 (coupling & growth), Ch. 6 (radiation & propagation), Ch. 7 (metrology).
- EFT.WP.Cosmo.LayeredSea v1.0: segmentation, matching, and consistency.
- EFT.WP.Propagation.TensionPotential v1.0: two-form and differential workflows.
- EFT.WP.Core.Equations v1.1 / Metrology v1.0 / Errors v1.0: notation, metrology, and error families.
XV. Deliverables
- Solver implementation checklist & pseudoflow (with segmentation and correction norms).
- Convergence & consistency templates for eps_T, eta_T, eta_w, tau_switch and their audits.
- Benchmark scripts & reproducibility bundle layout: data, code, hashes, and replay instructions.
Copyright & License (CC BY 4.0)
Copyright: Unless otherwise noted, the copyright of “Energy Filament Theory” (text, charts, illustrations, symbols, and formulas) belongs to the author “Guanglin Tu”.
License: This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0). You may copy, redistribute, excerpt, adapt, and share for commercial or non‑commercial purposes with proper attribution.
Suggested attribution: Author: “Guanglin Tu”; Work: “Energy Filament Theory”; Source: energyfilament.org; License: CC BY 4.0.
First published: 2025-11-11|Current version:v5.1
License link:https://creativecommons.org/licenses/by/4.0/