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Active Galactic Nucleus Jets: Axial Punch-Through and Alignment with the Cosmic Web Filament Skeleton
V33-33.8 · F 证据节 / 显影节 ·
33.8 turns AGN jets and the cosmic-web filament skeleton into a preregistered direction-field audit: jet–skeleton angles should bias toward small ψ, the most aligned systems should be longer, straighter, and more symmetric, and the signal should strengthen from void to filament to node; under V08-compatible retain, this stays a structure-genesis direction ledger rather than a standalone cosmology verdict.
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Keywords: AGN jets, axial punch-through, cosmic web filament skeleton, PA_jet, ψ, f_align, L_hat, S, Q, void-filament-node, permutation null, retain boundary
Section knowledge units
thesis
33.8 reframes AGN jets as probes of a local direction field rather than as isolated morphology anecdotes. If the filamentary backbone of the cosmic web shapes the medium through which jets propagate, the angle between the jet axis and the local filament-skeleton direction should not be uniform. It should be biased toward small values. Alignment is not the only demand. The aligned systems should also look more like axial punch-through cases: they should extend farther, stay straighter, and appear more two-sided. The chapter therefore asks for a three-part structure at once - an angle bias, morphology that strengthens with alignment, and an environment gradient that is strongest in filaments and nodes and weakest in voids. Hand-drawn filaments or post-hoc example selection do not count.
mechanism
The measurement sheet is explicit and preregistered. For each AGN, the projected jet position angle defines a jet-direction unit vector, while the local tangent of the cosmic-web filament skeleton defines a skeleton-direction unit vector in the same redshift slice and physical neighborhood. Their absolute dot product becomes the co-linearity angle ψ on a 0°–90° scale. The protocol then freezes a threshold ψ0 and computes the aligned fraction f_align, together with a nonparametric test of whether the full angle distribution departs from uniform. Morphology is scored through three normalized quantities: L_hat for jet reach relative to the environment scale, S for straightness, and Q for two-sided symmetry. Every system also receives both tiered and continuous environment labels so that angle bias and morphology synergy can be compared across void, filament, and node regimes under one shared aperture and resolution standard.
mechanism
The workflow is built to stop alignment from being painted in after the fact. Samples are matched or stratified in host mass, redshift, and radio brightness so that dense environments do not merely inherit the most powerful jets. The skeleton-extraction algorithm, smoothing scale, slice thickness, neighborhood size, and mask treatment are all frozen before the jet directions are seen. The jet-direction standard is frozen separately, including pixel thresholds, ridge-line fitting, bilateral combination rules, and treatment of bent or multi-component jets. The skeleton team and jet team work blind to each other’s outputs. After unblinding, a third party computes angle distributions, aligned fractions, and morphology–alignment relationships under fixed rules. The chapter also demands cross-probe verification from at least two skeleton types, such as galaxy-based and weak-lensing or shear-field skeletons, before alignment can count as supported.
evidence
False alignment is attacked directly. If the filament direction field is randomly rotated or host positions are resampled while preserving the survey footprint, the ψ distribution should return toward uniform and f_align should collapse to its random baseline. Matched control fields with similar depth and resolution but different environment grades test whether the signal follows observing depth rather than environment. Redshift permutation in tomography should also weaken a real environment-linked result. On the jet side, morphology artifacts are handled by reconstructing axes with an independent imaging or deconvolution pipeline. If the alignment bias or morphology synergy appears only in one pipeline, one band, or one sky region, the evidence is not allowed to stand. These are not optional robustness ornaments; they are part of the admissibility gate.
boundary
Passing requires three simultaneous outcomes. First, the full angle distribution must depart significantly from uniform and f_align must exceed its random baseline in the full sample and in independent subsamples, while collapsing under permutation nulls. Second, after controlling for host mass, redshift, and jet power, the most aligned systems must show stronger axial punch-through - larger L_hat, higher straightness, and higher symmetry - with the trend strongest in filaments and nodes and weakest in voids. Third, independent skeleton constructions must return the same-direction alignment bias within uncertainty. The chapter fails if alignment is indistinguishable from uniform, if morphology synergy disappears after controls, if the signal lives only in one pipeline or sky region, or if different skeleton standards give contradictory answers that cannot be reconciled by preregistered systematics. The named risks are projection ambiguity, skeleton-algorithm dependence, and selection-function coupling between survey depth, resolution, and environment distribution.
interface
33.8 ends with a narrow but usable success line: if jet–skeleton alignment is real and axial punch-through strengthens with alignment in filaments and nodes, the direction ledger passes. That retained result is important because it locks one direction-first account inside the broader structure-formation lane and hands a cleaner environment-stratified window forward to 33.9 and later jet breathing checks in 33.38. But the compat boundary remains in force. Even a strong retained alignment result is still one account among several; it does not by itself settle the total structure-formation or cosmology case.