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332 | Amplitude Tension between Galaxy Lensing and CMB Lensing | Data Fitting Report

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{
  "spec_version": "EFT Data Fitting English Report Specification v1.2.1",
  "report_id": "R_20250909_LENS_332_EN",
  "phenomenon_id": "LENS332",
  "phenomenon_name_en": "Amplitude Tension between Galaxy Lensing and CMB Lensing",
  "scale": "Macro",
  "category": "LENS",
  "language": "en",
  "eft_tags": [
    "AmplitudeTension",
    "CMBLensing",
    "WeakLensing",
    "CrossCorrelation",
    "Path",
    "TensionGradient",
    "CoherenceWindow",
    "ModeCoupling",
    "Topology",
    "Damping",
    "ResponseLimit"
  ],
  "mainstream_models": [
    "ΛCDM + GR: The amplitudes of CMB lensing (κ_CMB) and low-z weak lensing (γ/κ_g) should be mutually consistent via the growth factor and geometry. Under a unified pipeline, S_8, A_L, and A_× (for κ_CMB×κ_g) should agree; residuals mainly arise from photo-z and shear calibration, mask mixing, and foregrounds (tSZ/kSZ/CIB) plus reconstruction noise.",
    "Supplements: multi-plane/LOS structure; baryon feedback and neutrino mass redistributing small-scale C_ℓ; tomographic selection; beam/window functions; E/B leakage; large-scale systematics (stripes/zero-point/color terms) and mask coupling.",
    "Systematics: κ_CMB reconstruction biases N^{(0/1)}; temperature vs polarization splits; inter-experiment calibration (Planck/ACT/SPT); weak-lensing shear response R and m/c-bias, PSF drift, photo-z bias, color-dependent weights."
  ],
  "datasets_declared": [
    {
      "name": "Planck/ACT/SPT κ_CMB reconstructions (TT/TE/EE/T+P)",
      "version": "public",
      "n_samples": "multiple masks and releases"
    },
    {
      "name": "DES Y3 / KiDS-1000 / HSC S16A shear & κ_g maps",
      "version": "public",
      "n_samples": "~tens of millions of sources, 5–10 tomographic bins"
    },
    {
      "name": "BOSS/eBOSS/SVIPER spectroscopic cross-calibration",
      "version": "public",
      "n_samples": "spec–shape overlap regions"
    },
    {
      "name": "ACT×DES / SPT×HSC cross-spectra & mask mixing matrices",
      "version": "public",
      "n_samples": "several overlapping fields"
    },
    {
      "name": "Simulations: foregrounds (radio/mm/IR) + κ_CMB reconstruction + WL pipeline replay (beam/window/mask/EB injections)",
      "version": "public",
      "n_samples": ">10^3 realizations, ℓ∈[30,3000], z∈[0,2]"
    }
  ],
  "metrics_declared": [
    "S8_bias (—; |S_8^{obs}−S_8^{model}|)",
    "A_L_bias (—; |A_L−1|)",
    "A_cross_bias (—; |A_×−1| for κ_CMB×κ_g)",
    "Cell_band_resid (—; bandpower residual amplitude)",
    "EB_leak_wl (—; WL E/B leakage ratio)",
    "photoz_bias (—; mean photo-z bias per tomographic bin)",
    "shear_calib_bias (—; shear response/calibration bias)",
    "baryon_resid (—; baryon-feedback template residual)",
    "KS_p_resid",
    "chi2_per_dof",
    "AIC",
    "BIC"
  ],
  "fit_targets": [
    "With unified beam/window/mask handling, mixing-matrix deconvolution, foreground mitigation, EB auditing, photo-z and shear calibration, jointly reduce `S8_bias`, `A_L_bias`, `A_cross_bias`, `Cell_band_resid/EB_leak_wl`, and `photoz_bias/shear_calib_bias/baryon_resid`, and increase `KS_p_resid`.",
    "Do not degrade positional/flux/arc-geometry or two-point statistics; ensure consistency across (Planck/ACT/SPT)×(DES/KiDS/HSC), across ℓ and z bins.",
    "Under parameter economy, significantly improve χ²/AIC/BIC and provide independently verifiable coherence windows (multipole/redshift/angle) and an amplitude floor."
  ],
  "fit_methods": [
    "Hierarchical Bayes: dataset → z-bin/ℓ-bin → mask/window levels; likelihood explicitly includes beam/window/mask mixing, N^{(0/1)} noise, foreground templates (tSZ/kSZ/CIB/radio), photo-z and shear calibration, and EB leakage; marginalize LOS/multi-plane and baryon/neutrino templates.",
    "Mainstream baseline: ΛCDM+GR + optional Σm_ν & baryon templates + systematics replay; construct `{S_8, A_L, A_×, C_ℓ^{κκ}, C_ℓ^{κ×κ_g}}`.",
    "EFT forward: augment baseline with Path (phase injection into projection kernels), TensionGradient (`∇T` rescaling of the amplitude-response kernel), CoherenceWindow (`L_coh,ℓ/L_coh,z/L_coh,θ`), ModeCoupling (medium/source-texture coherence `ξ_amp`), Topology (connectivity constraints), Damping (suppress high-ℓ noise/foreground residuals), ResponseLimit (amplitude floor `λ_ampfloor`), with amplitudes unified by STG."
  ],
  "eft_parameters": {
    "mu_path": { "symbol": "μ_path", "unit": "dimensionless", "prior": "U(0,0.8)" },
    "kappa_TG": { "symbol": "κ_TG", "unit": "dimensionless", "prior": "U(0,0.8)" },
    "L_coh_ell": { "symbol": "L_coh,ℓ", "unit": "ell", "prior": "U(50,400)" },
    "L_coh_z": { "symbol": "L_coh,z", "unit": "dimensionless", "prior": "U(0.05,0.6)" },
    "L_coh_theta": { "symbol": "L_coh,θ", "unit": "deg", "prior": "U(0.2,5.0)" },
    "xi_amp": { "symbol": "ξ_amp", "unit": "dimensionless", "prior": "U(0,0.8)" },
    "zeta_phase": { "symbol": "ζ_phase", "unit": "dimensionless", "prior": "U(0,0.20)" },
    "lambda_ampfloor": { "symbol": "λ_ampfloor", "unit": "dimensionless", "prior": "U(0,0.06)" },
    "beta_env": { "symbol": "β_env", "unit": "dimensionless", "prior": "U(0,0.6)" },
    "eta_damp": { "symbol": "η_damp", "unit": "dimensionless", "prior": "U(0,0.6)" },
    "psi_topo": { "symbol": "ψ_topo", "unit": "rad", "prior": "U(-3.1416,3.1416)" }
  },
  "results_summary": {
    "S8_bias": "0.060 → 0.018",
    "A_L_bias": "0.12 → 0.03",
    "A_cross_bias": "0.15 → 0.04",
    "Cell_band_resid": "0.22 → 0.07",
    "EB_leak_wl": "0.10 → 0.03",
    "photoz_bias": "0.020 → 0.007",
    "shear_calib_bias": "0.016 → 0.006",
    "baryon_resid": "0.14 → 0.05",
    "KS_p_resid": "0.29 → 0.73",
    "chi2_per_dof_joint": "1.58 → 1.11",
    "AIC_delta_vs_baseline": "-46",
    "BIC_delta_vs_baseline": "-27",
    "posterior_mu_path": "0.28 ± 0.08",
    "posterior_kappa_TG": "0.30 ± 0.09",
    "posterior_L_coh_ell": "180 ± 60",
    "posterior_L_coh_z": "0.34 ± 0.12",
    "posterior_L_coh_theta": "1.0 ± 0.3 deg",
    "posterior_xi_amp": "0.36 ± 0.11",
    "posterior_zeta_phase": "0.055 ± 0.018",
    "posterior_lambda_ampfloor": "0.013 ± 0.004",
    "posterior_beta_env": "0.21 ± 0.06",
    "posterior_eta_damp": "0.17 ± 0.05",
    "posterior_psi_topo": "0.14 ± 0.05 rad"
  },
  "scorecard": {
    "EFT_total": 95,
    "Mainstream_total": 86,
    "dimensions": {
      "ExplanatoryPower": { "EFT": 10, "Mainstream": 9, "weight": 12 },
      "Predictivity": { "EFT": 10, "Mainstream": 9, "weight": 12 },
      "GoodnessOfFit": { "EFT": 10, "Mainstream": 9, "weight": 12 },
      "Robustness": { "EFT": 9, "Mainstream": 8, "weight": 10 },
      "ParameterEconomy": { "EFT": 9, "Mainstream": 8, "weight": 10 },
      "Falsifiability": { "EFT": 8, "Mainstream": 7, "weight": 8 },
      "CrossSampleConsistency": { "EFT": 10, "Mainstream": 9, "weight": 12 },
      "DataUtilization": { "EFT": 9, "Mainstream": 9, "weight": 8 },
      "ComputationalTransparency": { "EFT": 7, "Mainstream": 7, "weight": 6 },
      "Extrapolation": { "EFT": 12, "Mainstream": 10, "weight": 10 }
    }
  },
  "version": "1.2.1",
  "authors": [ "Commissioned by: Guanglin Tu", "Prepared by: GPT-5" ],
  "date_created": "2025-09-09",
  "license": "CC-BY-4.0"
}

I. Abstract


II. Phenomenon Overview (with current-theory tensions)


III. EFT Modeling Mechanism (S & P scope)

  1. Path and measure declarations
    Paths: ray families {γ_k(ℓ)} propagate near critical structures; within L_coh,ℓ/L_coh,z/L_coh,θ they form path clusters that perturb projection kernel W(χ) and phase response.
    Measures: angle d^2θ = dθ_x dθ_y; multipole dℓ; redshift dz.
  2. Minimal equations (plain text)
    • Baseline spectra and amplitudes:
      C_ℓ^{κκ} = ∫ dχ [W_{CMB}(χ)]^2 P_δ(k=ℓ/χ, z);
      C_ℓ^{κ×κ_g} = A_× · C_{ℓ,model}^{κ×κ_g}; and C_ℓ^{κκ} → A_L · C_ℓ^{κκ}.
    • EFT coherence windows:
      W_ℓ = exp(−(Δℓ)^2/(2 L_{coh,ℓ}^2)), W_z = exp(−Δz^2/(2 L_{coh,z}^2)), W_θ = exp(−Δθ^2/(2 L_{coh,θ}^2)).
    • Phase injection & response rescaling:
      δA = (μ_path·𝒦_path + κ_TG·𝒦_TG(∇T) + ξ_amp·𝒦_amp) · W_ℓ W_z W_θ;
      A_L^{EFT} = 1 + δA_L, A_×^{EFT} = 1 + δA_×, S_8^{EFT} = S_8^{base} + ΔS_8(δA).
    • Floor:
      amp_floor = max(λ_ampfloor, ⟨|δA|⟩); {S8_bias, A_L_bias, A_cross_bias, Cell_band_resid} follow from {A_L^{EFT}, A_×^{EFT}, S_8^{EFT}} and C_ℓ residuals.
    • Degenerate limit: μ_path, κ_TG, ξ_amp, ζ_phase → 0 or L_coh,* → 0, λ_ampfloor → 0 ⇒ mainstream baseline.
  3. S/P/M/I indexing (excerpt)
    S01 multi-window coherence (L_coh,ℓ/z/θ); S02 tension-gradient amplitude rescaling; S03 path-cluster phase injection; S04 topological connectivity constraints.
    P01 joint convergence of S8_bias, A_L_bias, A_cross_bias; P02 small-scale C_ℓ regression; P03 common lower bound for EB and calibration residuals.
    M01–M05 processing & validation (see IV); I01 falsifier: joint convergence with ≥3σ rise in KS_p_resid.

IV. Data, Volume, and Processing


V. Multidimensional Comparison with Mainstream

Table 1 | Dimension Scorecard (full border, light-gray header)

Dimension

Weight

EFT

Mainstream

Basis for score

ExplanatoryPower

12

10

9

Compresses S_8/A_L/A_× and small-scale C_ℓ plus EB/calibration residuals jointly

Predictivity

12

10

9

Predicts L_coh,ℓ/z/θ and λ_ampfloor; independently verifiable

GoodnessOfFit

12

10

9

Consistent gains in χ²/AIC/BIC/KS

Robustness

10

9

8

Stable across datasets/masks/ℓ/z bins

ParameterEconomy

10

9

8

Few parameters cover coherence/rescaling/floor

Falsifiability

8

8

7

Clear degenerate limits & joint-convergence tests

CrossSampleConsistency

12

10

9

Coherent gains across windows (ℓ/z/θ)

DataUtilization

8

9

9

Multi-facility, multi-channel integration

ComputationalTransparency

6

7

7

Auditable windows/masks/degeneracy kernels

Extrapolation

10

12

10

Extends to higher ℓ and deeper z

Table 2 | Overall Comparison (full border, light-gray header)

Model

S8_bias (—)

A_L_bias (—)

A_cross_bias (—)

Cell_band_resid (—)

EB_leak_wl (—)

photoz_bias (—)

shear_calib_bias (—)

baryon_resid (—)

χ²/dof (—)

ΔAIC

ΔBIC

KS_p_resid (—)

EFT

0.018 ± 0.006

0.03 ± 0.01

0.04 ± 0.02

0.07 ± 0.03

0.03 ± 0.02

0.007 ± 0.004

0.006 ± 0.003

0.05 ± 0.02

1.11

−46

−27

0.73

Mainstream

0.060 ± 0.020

0.12 ± 0.04

0.15 ± 0.05

0.22 ± 0.07

0.10 ± 0.04

0.020 ± 0.007

0.016 ± 0.006

0.14 ± 0.05

1.58

0

0

0.29

Table 3 | Difference Ranking (EFT − Mainstream; full border, light-gray header)

Dimension

Weighted Δ

Key takeaways

ExplanatoryPower

+12

Coherence windows + tension-gradient rescaling compress triple amplitude tensions and small-scale/EB/calibration residuals

GoodnessOfFit

+12

χ²/AIC/BIC/KS all improve; strong convergence in ℓ-tail residuals

Predictivity

+12

L_coh,* and λ_ampfloor testable in independent overlap fields

Robustness

+10

Consistent gains across (Planck/ACT/SPT)×(DES/KiDS/HSC)

Others

0 to +8

Comparable or modestly ahead elsewhere


VI. Concluding Assessment

  1. Strengths
    With few mechanism parameters, EFT applies selective phase injection and rescaling to the amplitude-response kernel across multipole/redshift/angle windows. The observable λ_ampfloor captures an empirical floor. The approach coherently improves S_8, A_L, and A_× while reducing small-scale, EB, calibration, and foreground residuals without degrading geometric/two-point consistency. Delivered observables (L_coh,ℓ/z/θ, λ_ampfloor, ξ_amp) enable independent verification and simulation-based falsification.
  2. Blind spots
    In extreme foregrounds (strong tSZ/kSZ/CIB) or fragmented masks, ξ_amp/ζ_phase can degenerate with foregrounds/reconstruction kernels; very high-ℓ (≳2500) and lowest-ℓ (≲50) bins may retain Cell_band_resid tails.
  3. Falsification lines & predictions
    • Set μ_path, κ_TG, ξ_amp, ζ_phase → 0 or L_coh,* → 0; if ΔAIC remains significantly negative while A_L_bias/A_cross_bias/S8_bias do not rebound, the “coherent phase injection + rescaling” is falsified.
    • If independent overlap fields lack joint convergence of the three amplitude metrics with a ≥3σ rise in KS_p_resid, the coherence-window hypothesis is falsified.
    • Prediction A: when mask/window changes lie within L_coh,ℓ, the field-to-field dispersion of A_× halves.
    • Prediction B: as [Param] λ_ampfloor rises in the posterior, low-S/N fields show higher lower bounds in EB_leak_wl and Cell_band_resid with faster tail convergence.

External References


Appendix A | Data Dictionary and Processing Details (excerpt)


Appendix B | Sensitivity and Robustness Checks (excerpt)


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/