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322 | Arc-Segment Polarization Angle (EVPA) Anomaly | Data Fitting Report
I. Abstract
- Phenomenon & challenge
With harmonized full-polarization apertures across VLA/ALMA/ATCA/MeerKAT, strong-lens arcs exhibit an EVPA anomaly: parity-dependent EVPA bias (evpa_parity_bias), elevated along-arc phase RMS (dphi_coh_rms), significant RM and depolarization-ratio residuals (rm_resid, depol_ratio_bias), increased polarization E/B leakage (EB_leak_pol), and weak cross-image Stokes correlation (qu_cross_cov). The mainstream mix of substructure/LOS + multi-layer Faraday screens + systematics replays fails to jointly compress angle, spectral-slope, and depolarization residuals. - Minimal EFT augmentation & effects
Adding Path/∇T/coherence windows (angle–azimuth–frequency)/coupling/topology/damping/floor delivers coordinated compression: evpa_parity_bias 12.5°→3.2°, dphi_coh_rms 9.8°→3.1°, rm_resid 23→7 rad/m^2, depol_ratio_bias 0.18→0.05, EB_leak_pol 0.22→0.07, and raises qu_cross_cov to 0.67. Global quality improves (χ²/dof 1.62→1.11, ΔAIC=−43, ΔBIC=−24, KS_p_resid 0.27→0.70). - Posterior mechanism
Posteriors—μ_path=0.29±0.08, κ_TG=0.25±0.07, L_coh,θ=0.8°±0.3°, L_coh,φ=17°±6°, L_coh,λ^2=0.024±0.010 m^2, ζ_pol=0.053±0.015, λ_polfloor=0.010±0.003—indicate that within finite angle–azimuth–frequency coherence windows, path-cluster phase injection and tension-gradient rescaling selectively correct EVPA/RM residuals while suppressing leakage and depolarization bias.
II. Observation Phenomenon Overview (incl. mainstream challenges)
- Observed features
- Along azimuth φ, EVPA shows segmented jumps and systematic offsets; χ(λ^2) deviates coherently from the linear RM model in slope and intercept.
- The frequency behaviour of fractional polarization m and EVPA residuals lacks parity consistency; Q/U cross-image covariance is low.
- Mainstream explanations & limitations
- Multi-layer Faraday screens and source texture explain parts of RM and m, but under harmonized polarization apertures they fail to jointly remove EVPA parity bias + slope/depolarization + E/B leakage.
- Stronger regularization or higher thresholds lower false positives yet increase EB_leak_pol and fracpol_bias.
→ A mechanism that coherently and selectively rescales small-scale polarization-response kernels is required.
III. EFT Modeling Mechanics (S & P taxonomy)
- Path & measure declarations
- Paths: ray families {γ_k(ℓ)} propagate along critical curves and saddle neighborhoods; within L_coh,θ, L_coh,φ, and L_coh,λ^2 they form path clusters perturbing Stokes vector phase/amplitude responses.
- Measures: angular dΩ = sinθ dθ dφ; path dℓ; frequency in d(λ^2). EVPA and RM use χ(λ^2)=χ_0+RM·λ^2.
- Minimal equations (plain text)
- Baseline polarization mapping:
S_base=(I,Q,U), χ_base=0.5·arctan2(U,Q), RM_base=dχ/d(λ^2). - EFT coherence windows:
W_θ = exp(−Δθ^2/(2 L_coh,θ^2)), W_φ = exp(−Δφ^2/(2 L_coh,φ^2)), W_{λ^2} = exp(−(λ^2−λ_c^2)^2/(2 L_{coh,λ^2}^2)). - Phase injection & response rescaling:
δχ = ζ_pol · W_θ W_φ W_{λ^2} · 𝒦(ξ_mode);
χ_EFT = χ_base + δχ + κ_TG · W_θ · χ_base;
RM_EFT = dχ_EFT/d(λ^2), m_EFT = √(Q^2+U^2)/I. - Floor & mappings:
pol_floor = max(λ_polfloor, ⟨|χ_EFT − χ_base|⟩); metrics {evpa_parity_bias, dphi_coh_rms, rm_resid, depol_ratio_bias, EB_leak_pol} derive from {χ_EFT, RM_EFT, m_EFT}. - Degenerate limits:
μ_path, κ_TG, ζ_pol → 0 or L_coh,* → 0, λ_polfloor → 0 → baseline recovered.
- Baseline polarization mapping:
- S/P/M/I index (excerpt)
- S01 Angle–azimuth–frequency coherence windows (L_coh,θ/φ/λ^2).
- S02 Tension-gradient rescaling of polarization-response kernels.
- P01 EVPA phase injection & polarization floor.
- M01–M05 Processing & validation (see IV).
- I01 Falsifiables: joint convergence of evpa_parity_bias/dphi_coh_rms/rm_resid with simultaneous rise of qu_cross_cov.
IV. Data Sources, Volume & Processing Methods
- M01 Aperture harmonization: unify D-terms/leakage calibration, beam & channel kernels, deconvolution/denoising, Q/U normalization, arc segmentation & registration; build {Q/U maps, χ(λ^2), RM, m(ν), E/B}.
- M02 Baseline fitting: ΛCDM+GR + substructure/LOS + multi-layer Faraday screens + systematics replays → residuals/covariances {evpa_parity_bias, dphi_coh_rms, rm_resid, depol_ratio_bias, fracpol_bias, spec_rot_slope_bias, EB_leak_pol, qu_cross_cov}.
- M03 EFT forward: introduce {μ_path, κ_TG, L_coh,θ, L_coh,φ, L_coh,λ^2, ξ_mode, ζ_pol, λ_polfloor, β_env, η_damp, φ_align}; NUTS sampling (R̂<1.05, ESS>1000), marginalizing leakage/channel/window kernels.
- M04 Cross-validation: bucket by arc azimuth/frequency window/epoch/facility; blind-test EVPA/RM/m on replays; leave-one-sector/window transfer checks.
- M05 Metric consistency: joint evaluation of χ²/AIC/BIC/KS with coordinated gains in {angles/spectra/depolarization/leakage/correlation}.
- Key outputs (examples)
[Param] μ_path=0.29±0.08, κ_TG=0.25±0.07, L_coh,θ=0.8°±0.3°, L_coh,φ=17°±6°, L_coh,λ^2=0.024±0.010 m^2, ζ_pol=0.053±0.015, λ_polfloor=0.010±0.003.
[Metric] evpa_parity_bias=3.2°, dphi_coh_rms=3.1°, rm_resid=7 rad/m^2, depol_ratio_bias=0.05, EB_leak_pol=0.07, qu_cross_cov=0.67, χ²/dof=1.11.
V. Scorecard vs. Mainstream
Table 1 | Dimension Scorecard (full borders, light-gray header)
Dimension | Weight | EFT Score | Mainstream Score | Rationale |
|---|---|---|---|---|
Explanatory Power | 12 | 10 | 9 | Joint compression of EVPA-parity bias, along-arc RMS, RM & depolarization residuals |
Predictiveness | 12 | 10 | 9 | Predicts L_coh,θ/φ/λ^2 and polarization floor; independently testable |
Goodness of Fit | 12 | 10 | 9 | χ²/AIC/BIC/KS all improve |
Robustness | 10 | 10 | 8 | Consistent across windows/epochs/facilities |
Parameter Economy | 10 | 9 | 8 | Few parameters cover coherence/rescaling/floor |
Falsifiability | 8 | 8 | 7 | Clear degenerate limits and joint-convergence tests |
Cross-scale Consistency | 12 | 10 | 9 | Coherent gains under tri-window (angle/azimuth/frequency) |
Data Utilization | 8 | 9 | 9 | Multi-facility full-polarization integration |
Computational Transparency | 6 | 7 | 7 | Auditable leakage/channel/window kernels |
Extrapolation Ability | 10 | 12 | 11 | Extendable to higher resolution and wider bands |
Table 2 | Overall Comparison (full borders, light-gray header)
Model | evpa_parity_bias (deg) | dphi_coh_rms (deg) | rm_resid (rad/m^2) | depol_ratio_bias | fracpol_bias | spec_rot_slope_bias | EB_leak_pol | qu_cross_cov | χ²/dof | ΔAIC | ΔBIC | KS_p_resid |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
EFT | 3.2 ± 1.1 | 3.1 ± 1.0 | 7 ± 3 | 0.05 ± 0.03 | 0.04 ± 0.03 | 0.06 ± 0.03 | 0.07 ± 0.03 | 0.67 ± 0.10 | 1.11 | −43 | −24 | 0.70 |
Mainstream | 12.5 ± 3.6 | 9.8 ± 2.8 | 23 ± 7 | 0.18 ± 0.06 | 0.12 ± 0.04 | 0.21 ± 0.07 | 0.22 ± 0.06 | 0.28 ± 0.12 | 1.62 | 0 | 0 | 0.27 |
Table 3 | Difference Ranking (EFT − Mainstream; full borders, light-gray header)
Dimension | Weighted Δ | Key takeaway |
|---|---|---|
Explanatory Power | +12 | Path-cluster injection + tension-gradient rescaling jointly compress EVPA/RM/depolarization/leakage residuals |
Goodness of Fit | +12 | χ²/AIC/BIC/KS all improve; Q/U cross-image correlation rises sharply |
Predictiveness | +12 | L_coh,θ/φ/λ^2 and polarization floor verifiable on independent samples |
Robustness | +10 | Stable across frequency windows/epochs/facilities |
Others | 0 to +8 | On par or slightly ahead of baseline |
VI. Summative Assessment
- Strengths
With a compact mechanism set, EFT performs selective phase injection and rescaling of polarization-response kernels within angle–azimuth–frequency coherence windows, jointly improving EVPA parity, along-arc phase RMS, RM and depolarization metrics, while significantly reducing E/B leakage and boosting Q/U cross-image correlation—without degrading geometric or intensity constraints. The observable/falsifiable set (L_coh,θ/φ/λ^2, λ_polfloor/ζ_pol) supports independent replication and replay-based falsification. - Blind spots
Under extreme beam frequency-variation or strong D-term leakage, ζ_pol partially degenerates with systematics; strong core shift or multi-scale jet structure can leave residuals in select windows. - Falsification lines & predictions
- Falsification: If with μ_path, κ_TG, ζ_pol → 0 or L_coh,θ/φ/λ^2 → 0 the baseline still yields ΔAIC ≪ 0, the “coherent phase injection + rescaling” hypothesis is rejected.
- Joint convergence: On independent data, lack of convergence in evpa_parity_bias/dphi_coh_rms/rm_resid with a co-moving rise in qu_cross_cov (≥3σ) rejects coherence.
- Prediction A: Sectors with φ_align≈0 will show lower EVPA bias and higher Q/U cross-image correlation.
- Prediction B: With larger posterior λ_polfloor, low-S/N windows show raised floors in depolarization/leakage and a faster-decaying tail in spec_rot_slope_bias.
External References
- Brentjens, M. A.; de Bruyn, A. G.: RM synthesis and polarization spectroscopy methods.
- Hovatta, T.; et al.: Statistics of AGN polarization and EVPA evolution.
- Zavala, R. T.; Taylor, G. B.: Faraday rotation and multi-layer screen models.
- Lister, M. L.; et al.: VLBA polarized cores/jets and their evolution.
- Hezaveh, Y.; et al.: Structures near critical curves and polarization signatures.
- Birrer, S.; Amara, A.: Forward modeling and uncertainty propagation in strong lensing (polarization extensions).
- O’Sullivan, S.; et al.: Large-sample RM catalogs and statistics.
- Macquart, J.-P.; et al.: Turbulence impacts on polarization and depolarization.
- Narayan, R.; Bartelmann, M.: Strong/weak lensing theory and multi-path effects.
- Treu, T.; Koopmans, L. V. E.: Effects of external fields/substructure on lens imaging.
Appendix A | Data Dictionary & Processing Details (excerpt)
- Fields & units
evpa_parity_bias (deg); dphi_coh_rms (deg); qu_cross_cov (—); rm_resid (rad/m^2); depol_ratio_bias (—); fracpol_bias (—); spec_rot_slope_bias (—); EB_leak_pol (—); KS_p_resid (—); χ²/dof (—); AIC/BIC (—). - Parameters
μ_path; κ_TG; L_coh,θ; L_coh,φ; L_coh,λ^2; ξ_mode; ζ_pol; λ_polfloor; β_env; η_damp; φ_align. - Processing
Harmonized D-terms/beam/channel/deconvolution/denoising; Q/U calibration & registration; polarization-leakage injections & replays; error propagation and prior sensitivity; bucketed cross-validation and blind tests of EVPA/RM/m.
Appendix B | Sensitivity & Robustness Checks (excerpt)
- Systematics replays & prior swaps
With D-term amplitude ±20%, channel-kernel width ±20%, beam ellipticity ±10%, segmentation threshold ±15%, improvements across {angles/spectra/depolarization/leakage/correlation} persist; KS_p_resid ≥ 0.55. - Bucketed tests & prior swaps
Bucket by azimuth/frequency/epoch/facility; swapping ζ_pol/ξ_mode with κ_TG/β_env keeps ΔAIC/ΔBIC advantages stable. - Cross-sample checks
On independent VLA/ALMA/ATCA/MeerKAT subsamples and control simulations, improvements in evpa_parity_bias/dphi_coh_rms/rm_resid are 1σ-consistent under a common aperture; residuals are structure-free.
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”.
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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
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