15 Quasar Polarization Group Alignments and “Filament-Mesh Synergy”

Home ／ Appendix-Prediction and Falsification

This chapter follows the publication template for the falsification program. It uses plain language, avoids equations, and keeps the structure fixed. For general readers: we study whether quasar linear-polarization angles align in groups and whether those alignments co-orient with the local cosmic-filament skeleton. At first mention we expand abbreviations—Electric Vector Position Angle (EVPA), Rotation Measure (RM)—and then use the abbreviations thereafter.

I. One-Sentence Goal

Test large quasar samples for grouped alignments in linear polarization and for co-orientation with the nearby cosmic-filament principal axis. Evaluate whether the signal is band-insensitive (no dispersion), monotonically stronger in filament/node environments than in voids, and robust to instruments and pipelines. If environment-forward predictions of direction and strength succeed and the effect replicates across bands and surveys, the result supports a path-term contribution in Energy Filament Theory (EFT). If Galactic foreground polarization, Faraday rotation, or instrument zero points explain the pattern—or no environmental link appears—the claim is disfavored.

II. What to Measure

• Grouped-alignment statistics: Within predefined angular cells and redshift slices, grade the EVPA distribution’s concentration vs isotropy (strong / moderate / near-uniform). Also measure the angle offset between each cell’s mean EVPA and the local filament principal axis; test for a small-offset excess.
• Filament-mesh synergy and directionality: Compare alignment strength in parallel-to-filament windows versus orthogonal windows to detect directional anisotropy. Contrast near-node versus far-from-node regions.
• Cross-band consistency (non-dispersion): Across optical, near-infrared, millimeter/radio subsets, compare alignment direction and strength ranking. Where multi-frequency data exist, verify that EVPAs do not flip or scale with wavelength in a law-like way.
• Spatial scale and environmental gradients: Track alignment strength qualitatively (enhance / plateau / decay) versus angular or comoving scale, and compare with environment proxies: void fraction, filament strength, distance to nodes, external convergence.
• Separation from foregrounds and pipelines: Where available, compare to stellar polarization fields, dust maps, and RM maps to ensure quasar alignments do not rotate with Galactic foreground orientation and do not follow an RM λ² law. Evidence of such tracking is classified as foreground/medium, not target signal.

III. How to Do It

1. Samples and environment skeleton:
   • Quasar sample: Compile measurements with reliable EVPA and polarization fraction over optical, near-infrared, and millimeter/radio bands. Record EVPA zero-point, polarization calibration, and RM / de-RM status.
   • Cosmic-filament skeleton: From public surveys, construct a filament–node–void skeleton and label each sky cell with filament axis, distance to nearest node, local density, and void/filament metrics.
   • Binning and matching: Partition by redshift slice and sky cell. Match stellar foregrounds, dust intensity, and survey depth to build target–control pairs.
2. Forward predictions and blinding:
   • Environment team (forward): Using only filament orientation, node proximity, and external-convergence information, issue a prediction card per cell: expected alignment direction (more along-filament / more across-filament / none), strength tier (strong / medium / weak), and scale trend (enhance / plateau / decay).
   • Measurement team (independent pipelines):
     1. Unify EVPA zero points and absolute angle calibration; compute concentration and directional anisotropy under both de-RM and raw EVPA conventions.
     2. Produce cross-band direction-consistency and strength-ranking summaries.
     3. Share only cell IDs and data-quality flags; do not access prediction cards.
   • Arbitration: A third party aligns prediction cards with measurement summaries, computes hit, wrong, and null rates, and stratifies results by environment grade, spatial scale, and band.

IV. Controls and Artifact Removal

• Rotation/label-shuffle controls: Randomly rotate the filament skeleton or permute cell labels; any persistent “alignment” under these operations indicates method or selection bias.
• Foreground baseline controls: Compare with stellar polarization fields, dust maps, and RM maps. If quasar EVPAs track foreground orientation or follow RM frequency laws, classify as foreground/medium coupling.
• Instrument/survey controls: Repeat the analysis in independent instruments and survey subsets. Signals that appear only in a single instrument or pipeline are treated as pipeline artifacts.

V. Reporting Metrics (Plain-Language Tiers)

• Alignment strength: strong concentration / moderate concentration / near-uniform.
• Directional relation: along-filament enhanced / across-filament enhanced / no significant directionality.
• Cross-band consistency: consistent / partly consistent / inconsistent.
• Environment gradient: monotonic with filament–node strength / plateau / uncorrelated.
• Spatial-scale behavior: enhance / plateau / decay over registered scale tiers.

VI. Systematics and Safeguards (Three Items)

• Interstellar polarization contamination (ISP): Stellar/dust alignment can project onto quasar EVPAs. Safeguard: local regression to stellar polarization fields and dust maps, masking high-contamination zones; re-report results in low E(B–V) regions.
• Faraday rotation and frequency dependence: RM rotates EVPA with λ². Safeguard: multi-frequency de-RM, sub-band consistency checks, and down-weight/hold-out high-RM beams; report direction consistency before and after de-RM.
• Instrumental polarization and angle zero point: Leakage (D-terms) and zero-point drift can fake alignment. Safeguard: multi-source angle calibration, swap polarization-calibration order and reprocess, use closure polarization / cross-hand checks; down-weight cells with unstable zero points.

VII. Execution and Transparency

Pre-register skeleton construction, cell partitioning and matching rules, text-grade metrics for alignment and directionality, positive/negative controls, and stratified statistics. Keep hold-out cells in each environment grade and band for final confirmation. Arrange cross-team reprocessing and independent review. Publicly release the filament-axis catalog, prediction cards, alignment/direction text grades, cross-band consistency tables, and foreground/de-RM processing summaries, plus key intermediate artifacts. This chapter forms a closed loop with Chapters 8 (axial perforation and jet–filament co-alignment), 1 (frequency-independent common terms across probes), and 22 (co-window brightness–polarization changes at jet bases); mutual cross-references are required.

VIII. Pass/Fail Criteria

1. Support (passes):
   • In two or more bands and two or more environment grades, environment-forward predictions of alignment direction and strength achieve significantly above-chance hit rates.
   • Alignment is stronger in filament/node corridors and weaker in voids, with cells co-oriented with the filament axis enriched in strong-alignment outcomes.
   • Cross-band direction consistency holds and de-RM/raw results agree in sign; findings are robust to instruments and pipelines; rotation/label-shuffle and foreground-equivalent controls do not reproduce the signal.
2. Refutation (fails):
   • Hit rates hover near chance, or alignment shows no monotonic relation with environment.
   • Alignment flips with wavelength or scales with λ² / 1/ν laws, or closely follows Galactic foreground orientation.
   • Signals are confined to one band / one pipeline / one team, and fail cross-team replication.