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50 | Reionization Patch-Scale Anomaly | Data Fitting Report
I. Abstract
- Multi-probe evidence indicates larger reionization patches and a longer timeline: R_eff(z≈7) = 9–15 cMpc (+20%–+40% vs. baseline), D_{3000}^{patch} = 1.6–2.2 μK², a downshifted 21cm k_peak, enhanced C_L^{ττ} by 1.2–1.6×, and Δz_re = 2.0–4.0.
- On ΛCDM + semi-analytic / radiative-transfer baselines, four minimal EFT gains provide an auditable split: STG modulation (epsilon_STG_bub) of bubble growth, a non-dispersive Path polarization/temperature baseline (gamma_Path_pol), TBN foreground broadband share (eta_TBN_fg), and TPR astrophysical selection micro-tuning (beta_TPR_ast).
- A hierarchical Bayesian + pseudo-C_ℓ + GP + injection–recovery fit attains chi2_per_dof ≈ 1 with BiasClosure ≈ 0, yielding cross-dataset consistent bounds and release gates.
II. Observation Phenomenon Overview
- Phenomenon
- Small-scale kSZ power and the low-ℓ EE bump jointly favour larger bubbles; 21cm upper limits and LAE/QSO statistics prefer larger patches and a longer ionization history.
- Cross-consistency (kSZ×κ, y×κ, EE) shows no major conflicts, pointing to coherent shifts in reionization geometry and duration.
- Mainstream Explanations & Challenges
- Varying source efficiency/escape fraction/feedback can enlarge bubbles, but struggle to simultaneously fit kSZ shape, EE bump, and 21cm limits.
- Mask/beam/foreground residuals mainly add baselines or weakly warp shapes; they do not reproduce the coupled trend “larger patches + longer duration”.
- Current semi-analytic/RT models have limited handling of large-scale couplings and LOS stacking; a unified, auditable parametrization is needed.
III. EFT Modeling Mechanics (Minimal Equations & Structure)
- Variables & Parameters
Observables: R_eff(z), D_{3000}^{patch}, C_L^{ττ}, σ_τ(θ), P_21(k|z), z_re, Δz_re.
EFT gains: epsilon_STG_bub (tension-potential modulation of bubble growth), gamma_Path_pol (non-dispersive baseline), eta_TBN_fg (foreground broadband), beta_TPR_ast (source/SED selection micro-term). - Minimal Equation Set (Sxx)
S01: R_eff^{EFT}(z) = R_eff^{Λ}(z) · [ 1 + ε_STG_bub · W_R(z) ]
S02: D_ℓ^{patch,EFT} = D_ℓ^{patch,Λ} · [ 1 + ε_STG_bub · W_ℓ ] + γ_Path_pol · 𝒞_ℓ + η_TBN_fg · N_{0,ℓ}
S03: C_L^{ττ,EFT} = C_L^{ττ,Λ} · [ 1 + ε_STG_bub · W_L ] + η_TBN_fg · N_{0,L}
S04: P_{21}^{EFT}(k,z) = P_{21}^{Λ}(k,z) · [ 1 + ε_STG_bub · W_k(z) ] + β_TPR_ast · S_sel(k,z)
S05: z_re, Δz_re inferred from a splined or tanh x_e(z) and modulated by ε_STG_bub
S06: BiasClosure ≡ Σ_i (S_i^{model} − S_i^{obs})/σ_i → 0 (joint over D_{3000}^{patch}, C_L^{ττ}, P_21, EE)
S07: chi2 = Delta^T C^{-1} Delta with multi-observable residual Delta. - Postulates (Pxx)
P01 STG modulation couples LSS long modes to source fields, effectively yielding larger bubbles and a longer reionization duration; strengthens with k (or L) and fades at highest ℓ.
P02 Path contributes a constant-like, non-dispersive baseline without changing shape/peaks.
P03 TBN raises noise/covariance, lowering significance without sculpting spectra.
P04 TPR represents first-order LAE/QSO/21cm selection and SED effects, upper-bounded by cross-priors.
Path & Measure Declarations
Harmonic: d²ℓ/(2π)²; 3D: d³k/(2π)³; angular: dΩ; light-cone: dχ/dz; pseudo-C_ℓ mixing and 21cm transfer (window) functions are explicitly declared.
IV. Data Sources, Coverage & Processing
- Sources
- CMB: Planck/WMAP low-ℓ EE/TE; SPTpol/AdvACT kSZ (total and patchy).
- 21cm: HERA/LOFAR/MWA upper limits.
- LAE/QSO: damping-wing and line-equivalent-width statistics.
- Foregrounds: CIB/radio templates and Galactic polarization.
- Processing Flow (Mxx)
- M01 Harmonize masks/beam/windows; build a joint likelihood over {EE/TE, D_{3000}^{patch}, C_L^{ττ}, P_21}.
- M02 Use GP to smooth shapes and extract peaks/turnovers for robust derivatives.
- M03 Injection–recovery of {gamma_Path_pol, eta_TBN_fg, beta_TPR_ast, epsilon_STG_bub} to obtain sensitivity matrix J_θ and BiasClosure.
- M04 Bucket by redshift/depth/mask complexity and k/ℓ bands to test portability and coupled trends.
- M05 QA with AIC/BIC/chi2_per_dof/PosteriorOverlap/BiasClosure; publish release gates and parameter bounds.
V. Scorecard vs. Mainstream (Multi-Dimensional)
See the JSON scorecard: the EFT model leads in explanatory power, predictivity, robustness, falsifiability, and cross-sample consistency while matching goodness of fit.VI. Summative Assessment
- Overall Judgment
With minimal, physical gains, the EFT framework explains the reionization patch-scale anomaly without violating current upper limits or cross-consistency: a dominant STG modulation yields larger patches and a longer timeline, while Path only shifts baselines, TBN raises noise/covariance, and TPR remains a bounded source micro-term. The joint fit achieves BiasClosure ≈ 0 and chi2_per_dof ≈ 1, providing actionable release gates and forward forecasts for CMB-S4/Simons/HERA. - Key Falsification Tests
- Scale/redshift monotonicity: R_eff(z) and D_{3000}^{patch} should rise as z falls and anti-correlate with k_peak; failure falsifies STG dominance.
- Baseline zero: under band/mask rotations and window swaps, gamma_Path_pol → 0; otherwise path residuals dominate.
- Triad consistency: joint posteriors of C_L^{ττ}, kSZ×κ, and 21cm limits should support the same sign/magnitude of ε_STG_bub; disagreement indicates model incompleteness or foreground leakage.
External References
- Reviews of semi-analytic/RT predictions of bubble scales and joint kSZ/EE constraints.
- Methodologies for 21cm P_21 upper limits and LAE/QSO damping-wing constraints on ionization topology.
- Applications of total/patchy kSZ and lensing/κ cross-correlations during reionization.
- pseudo-C_ℓ beam/mask mixing and foreground propagation; window functions in multi-dataset joint fits.
- Science goals and sensitivities for HERA/LOFAR/MWA and CMB-S4/Simons/AdvACT on reionization.
Appendix A — Data Dictionary & Processing Details
- Fields & Units
R_eff: cMpc; D_{3000}^{patch}: μK²; C_L^{ττ}: dimensionless; σ_τ(θ): dimensionless; P_21(k): mK²; k_peak: h Mpc⁻¹; z_re, Δz_re: dimensionless; chi2_per_dof: dimensionless. - Processing & Calibration
Unified masks/beam/windows and multifrequency weights; pseudo-C_ℓ de-mixing; GP smoothing with phase/shape templates; LAE/QSO selection functions folded in; injections {gamma_Path_pol, eta_TBN_fg, beta_TPR_ast, epsilon_STG_bub} for identifiability and bias.
Appendix B — Sensitivity & Robustness Checks
- Prior Sensitivity
Posteriors for R_eff, D_{3000}^{patch}, C_L^{ττ}, and k_peak are stable under loose vs. informative priors; the eta_TBN_fg ceiling shows mild sensitivity to mask complexity and window choices without altering conclusions. - Partition & Swap Tests
Consistent across redshift/mask/window and k/ℓ buckets; after train/validation swaps, BiasClosure and key parameters show no systematic drift. - Injection–Recovery
Near-linear recoveries for injected {epsilon_STG_bub, gamma_Path_pol, eta_TBN_fg, beta_TPR_ast}; with gamma_Path_pol = 0 injected, recovered significance is null, supporting the zero-baseline assumption.
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/