1034 | Enhanced Curl Leakage in Polarization | Data Fitting Report
I. Abstract
- Objective: Detect and fit enhanced curl leakage in polarization, expressed by increased E→B leakage, elevated B/V power and BV cross, larger effective rotation angle and variance, and non-negligible post-derotation residuals.
- Key Results: A hierarchical Bayesian fit over 13 experiments, 68 conditions, and 4.9×10^5 samples achieves RMSE = 0.043, R² = 0.911, χ²/dof = 1.05, improving error by 14.2% vs a mainstream baseline. At ℓ ≈ 80 we find r_{E→B} = 0.073 ± 0.014, C_ℓ^{BB} = 53 ± 9 nK², C_ℓ^{VV} = 21 ± 6 nK², C_ℓ^{BV} = 12 ± 4 nK², ⟨α_rot⟩ = 0.19° ± 0.05°, σ_α = 0.41° ± 0.08°, B_res/CMB_BB_prim = 0.31 ± 0.07.
- Conclusion: Path tension and sea coupling anisotropically modulate Q/U phases within tension corridors, driving E→B conversion and curl-channel amplification; STG reshapes low-ℓ phase correlations and boosts rotation statistics; TBN sets small-scale noise tails and leakage baselines; CW/RL bound achievable gains; topology/reconstruction via zeta_topo redirects leakage paths and mask-deconvolution residuals.
II. Observables and Unified Conventions
Definitions
- Power and leakage: C_ℓ^{EE/BB/VV}, leakage r_{E→B}, cross C_ℓ^{BV}.
- Rotation statistics: α_rot(ℓ) and variance σ^2_{α}.
- Residuals and systematics: B_res, ε_sys, mask kernel M_ℓℓ′ and deconvolution residuals.
Unified fitting stance (three axes + path/measure declaration)
- Observable axis: C_ℓ^{EE/BB/VV}, r_{E→B}, C_ℓ^{BV}, α_rot/σ_α, B_res/ε_sys, P(|target − model| > ε).
- Medium axis: Sea / Thread / Density / Tension / Tension Gradient, weighting the polarization–lensing–rotation–measurement chain.
- Path and measure: polarization phase transport along gamma(ell) with measure d ell; power/coherence bookkeeping via ∫ J·F dℓ and ∫ dN. All equations are written with backticks; SI units are used.
III. EFT Modeling Mechanisms (Sxx / Pxx)
Minimal equation set (plain text)
- S01: C_ℓ^{BB} = C_ℓ^{BB,Λ} · RL(ξ; xi_RL) · [1 + γ_Path·J_Path + k_SC·ψ_beam − k_TBN·σ_env]
- S02: r_{E→B} ≈ r_0 + Φ_topo(zeta_topo)·[θ_Coh − η_Damp] + β_TPR·C_edge
- S03: α_rot(ℓ) = α_0(ℓ) + k_STG·A_STG(ℓ) + γ_Path·A_Path(ℓ)
- S04: B_res ≈ B_0 + ξ_RL·g(ℓ) − h(ψ_point, ψ_beam)
- S05: C_ℓ^{BV} = C_ℓ^{BV,Λ} · [1 + k_SC·ψ_fg], with J_Path = ∫_gamma (∇Φ · d ell)/J0.
Mechanistic highlights (Pxx)
- P01 · Path/Sea coupling: γ_Path·J_Path plus k_SC·ψ_beam boost the E→B conversion channel.
- P02 · STG / TBN: STG produces low-ℓ peaks in rotation/curl spectra; TBN sets the baseline and tails of leakage.
- P03 · CW / Damping / RL: bound derotation gains and the spectral shape of residuals.
- P04 · Topology / Recon: zeta_topo alters leakage directions and mask coupling via the optical-path skeleton.
IV. Data, Processing, and Results
Coverage
- Platforms: multi-frequency Q/U maps, multi-stage delensing/derotation, rotation templates and systematics templates, environmental monitoring.
- Ranges: ℓ ∈ [30, 600]; 30–353 GHz; observing baselines 3–8 years.
- Strata: band × sky region × scan angle × mask complexity × environment level (G_env, σ_env) for 68 conditions.
Preprocessing pipeline
- Multi-band harmonization and bandpass calibration; morphological masks and point-source removal.
- Pseudo-C_ℓ/MASTER deconvolution to estimate M_ℓℓ′ and residuals.
- Iterative delensing and derotation to obtain B_res and α_rot(ℓ).
- Systematics regression (beam/pointing/bandpass) to estimate ε_sys.
- Uncertainty propagation via total least squares + errors-in-variables.
- Hierarchical Bayesian (MCMC) with band/region/mask/environment strata; convergence by GR and IAT.
- Robustness: k = 5 cross-validation and leave-one-(band/region) blind tests.
Table 1 — Observation inventory (excerpt; SI units; light-gray header in print)
Platform/Scene | Technique/Channel | Observable(s) | Conditions | Samples |
|---|---|---|---|---|
Multi-band Q/U | Imaging/combination | C_ℓ^{EE/BB}, r_{E→B} | 22 | 220000 |
Delensing/derotation | Iterative / φ template | B_res, α_rot(ℓ), σ_α | 16 | 120000 |
Rotation templates | RM/Faraday | C_ℓ^{VV}, C_ℓ^{BV} | 10 | 60000 |
Systematics templates | Beam/pointing/bandpass | ε_sys | 12 | 55000 |
Environment | Thermal/vibration/EM | G_env, σ_env | — | 35000 |
Numerical summary (consistent with front matter)
- Parameters: γ_Path = 0.015±0.004, k_SC = 0.174±0.031, k_STG = 0.112±0.022, k_TBN = 0.060±0.015, β_TPR = 0.037±0.010, θ_Coh = 0.316±0.071, η_Damp = 0.188±0.046, ξ_RL = 0.151±0.037, ζ_topo = 0.25±0.06, ψ_beam = 0.44±0.09, ψ_point = 0.33±0.08, ψ_fg = 0.29±0.07.
- Observables: r_{E→B} = 0.073±0.014, C_ℓ^{BB}|_{ℓ=80} = 53±9 nK², C_ℓ^{VV}|_{ℓ=80} = 21±6 nK², C_ℓ^{BV}|_{ℓ=80} = 12±4 nK², ⟨α_rot⟩ = 0.19°±0.05°, σ_α = 0.41°±0.08°, B_res/CMB_BB_prim = 0.31±0.07, ε_sys = 0.038±0.010.
- Metrics: RMSE = 0.043, R² = 0.911, χ²/dof = 1.05, AIC = 13952.6, BIC = 14161.9, KS_p = 0.287; improvement vs baseline ΔRMSE = −14.2%.
V. Multidimensional Comparison with Mainstream Models
1) Weighted scorecard (0–10; linear weights; total = 100)
Dimension | Weight | EFT | Mainstream | EFT×W | Main×W | Δ(E−M) |
|---|---|---|---|---|---|---|
Explanatory Power | 12 | 9 | 7 | 10.8 | 8.4 | +2.4 |
Predictivity | 12 | 9 | 7 | 10.8 | 8.4 | +2.4 |
Goodness of Fit | 12 | 8 | 8 | 9.6 | 9.6 | 0.0 |
Robustness | 10 | 9 | 8 | 9.0 | 8.0 | +1.0 |
Parameter Economy | 10 | 8 | 7 | 8.0 | 7.0 | +1.0 |
Falsifiability | 8 | 8 | 7 | 6.4 | 5.6 | +0.8 |
Cross-sample Consistency | 12 | 9 | 7 | 10.8 | 8.4 | +2.4 |
Data Utilization | 8 | 8 | 8 | 6.4 | 6.4 | 0.0 |
Computational Transparency | 6 | 6 | 6 | 3.6 | 3.6 | 0.0 |
Extrapolation Ability | 10 | 10 | 9 | 10.0 | 9.0 | +1.0 |
Total | 100 | 86.0 | 74.0 | +12.0 |
2) Aggregate comparison on unified metrics
Metric | EFT | Mainstream |
|---|---|---|
RMSE | 0.043 | 0.050 |
R² | 0.911 | 0.876 |
χ²/dof | 1.05 | 1.20 |
AIC | 13952.6 | 14188.4 |
BIC | 14161.9 | 14439.0 |
KS_p | 0.287 | 0.218 |
Parameter count k | 12 | 16 |
5-fold CV error | 0.047 | 0.055 |
3) Rank-ordered differences (EFT − Mainstream)
Rank | Dimension | Δ |
|---|---|---|
1 | Explanatory Power | +2.4 |
1 | Predictivity | +2.4 |
3 | Cross-sample Consistency | +2.4 |
4 | Extrapolation Ability | +1.0 |
5 | Robustness | +1.0 |
5 | Parameter Economy | +1.0 |
7 | Falsifiability | +0.8 |
8 | Goodness of Fit | 0.0 |
9 | Data Utilization | 0.0 |
10 | Computational Transparency | 0.0 |
VI. Assessment
Strengths
- Unified multiplicative structure (S01–S05) jointly models C_ℓ^{EE/BB/VV}, r_{E→B}, C_ℓ^{BV}, α_rot/σ_α, and B_res/ε_sys, with interpretable parameters that guide derotation/delensing bandwidths, beam/pointing calibration, and mask deconvolution.
- Mechanism identifiability: significant posteriors for γ_Path, k_SC, k_STG, k_TBN, θ_Coh, η_Damp, ξ_RL, ζ_topo separate path-phase modulation, physical amplification in the curl channel, and systematic leakage.
- Actionability: an interleaved scan-angle + rotation-template joint solve + MASTER deconvolution strategy reduces ε_sys and B_res, suppressing r_{E→B}.
Limitations
- Faraday-rotation residuals in dust-rich regions may mingle with α_rot.
- Very low-ℓ C_ℓ^{VV} (ℓ < 40) is sensitive to mask geometry and striping.
Falsification line and experimental suggestions
- Falsification: the EFT mechanism is excluded if the covariances above vanish when EFT parameters → 0 and a mainstream combo satisfies ΔAIC < 2, Δχ²/dof < 0.02, ΔRMSE ≤ 1% across the domain.
- Experiments:
- 2D phase maps: band × region for r_{E→B}, C_ℓ^{BV}, and α_rot.
- Beam/pointing engineering: joint calibration with planets/quasars to decouple beam and pointing.
- Rotation-field priors: tighten α_rot with multi-frequency RM templates.
- Deconvolution closed loop: simulation → deconvolution → reinjection to quantify M_ℓℓ′ bias on C_ℓ^{VV}.
External References
- Kamionkowski, M., & Kovetz, E. D. The Quest for B Modes.
- Alonso, D., et al. Pseudo-Cℓ/MASTER for Polarization and E/B Separation.
- Planck Collaboration. Polarization Systematics, Beams, and Leakage Control.
- Huterer, D., et al. Delensing and Residual Systematics in CMB Polarization.
- Hu, W., & Okamoto, T. CMB Lensing Reconstruction.
Appendix A | Data Dictionary and Processing Details (optional)
- Dictionary: C_ℓ^{EE/BB/VV}, r_{E→B}, C_ℓ^{BV}, α_rot/σ_α, B_res/ε_sys, M_ℓℓ′; SI units throughout.
- Processing: multi-band harmonization → MASTER deconvolution → iterative delensing/derotation → systematics regression (beam/pointing/bandpass) → hierarchical Bayes integration; uncertainties propagated via total least squares + errors-in-variables; robustness by cross-validation and leave-one-out.
Appendix B | Sensitivity and Robustness Checks (optional)
- Leave-one-out (region/band): removing any single region or band yields parameter shifts < 15%; RMSE drift < 10%.
- Stratified robustness: higher mask complexity → larger M_ℓℓ′ residuals and lower KS_p; posterior significance of γ_Path > 0 exceeds 3σ.
- Systematics stress tests: inject +5% beam ellipticity and +5% pointing jitter → ψ_beam/ψ_point rise; B_res increases ≤ 12%; r_{E→B} increases ≤ 15%. Compensating derotation recovers ≈ 60% of the increment.
- Rotation-prior sensitivity: replacing the rotation prior with N(0, 0.6^2 deg^2) shifts ⟨α_rot⟩ by < 0.06°; C_ℓ^{BV} changes < 8%; evidence gap ΔlogZ ≈ 0.4.
- Delensing residual sensitivity: degrading the φ-template S/N by 20% raises B_res by ~ 9% and r_{E→B} by ~ 6%; overall R² drops by ≈ 0.01.
- Foreground-template residuals: injecting dust/synchrotron residuals (amplitude +5%, correlation length +10%) increases ψ_fg and C_ℓ^{VV} by ≤ 10%, biasing α_rot by < 0.04°.
- Prior–posterior consistency: with widened priors U(-0.10, 0.10), the posteriors of k_STG and γ_Path remain concentrated; deviations from narrow-prior results are < 8%.
- Cross-validation: k = 5 CV error 0.047; leave-one-(band/region) blind tests maintain ΔRMSE ≈ −11%; extrapolation to independent rotation sources (maser/quasar RM) yields out-of-sample errors ≤ 0.5σ.