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Large Hadron Collider Jet In-Channel Coherence Under Event Congestion: Particle-Level Proxies for Spiral and Texture Channels
V33-33.18 · C 机制节 ·
33.18 turns LHC jet congestion into a blinded update audit: across channels and a frozen 3×3 suppression–grooming grid, Lund ridges, pull, substructure ratios, and H / Δφ1 Swirl Texture proxies must shift monotonically with congestion in one preregistered direction, with ρ_local ranking update strength better than μ or ρ; under V08/V09-compatible translation, texture-channel and road-network language stays at particle-level morphology and color-flow readout level rather than becoming new-particle ontology.
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Keywords: LHC jets, μ, ρ, ρ_local, Lund-plane ridge, Soft Drop, pull angle, D2, C2, tau21, tau32, ΔC, H, Δφ1, Swirl Texture
Section knowledge units
thesis
33.18 is not interested in whether one jet image looks smoother than another. The court asks whether congestion rewrites in-channel organization in a stable direction after pileup suppression and grooming are handled under one frozen protocol. If coherence really survives or sharpens under congestion, then Lund ridges, pull structure, splitting order, and particle-level morphology proxies should update together rather than wandering across algorithms and channels. If they do not, congestion remains noise. That is why the section is compat-adjudicated as translate rather than retain. It may certify a repeatable update protocol, but any texture-channel or energy-sea language must remain shorthand for particle-level organization and color-flow readout, not a new high-energy ontology.
mechanism
The measurement stack is deliberately broad so no single observable can dominate the verdict. Congestion is tracked globally with μ, ρ, and transverse-region activity, and locally with ρ_local plus track–vertex association and isolation in the near-jet annulus. Coherence is then read from Lund-plane ridge sharpness and ordering, Soft Drop observables such as zg and Rg, energy-correlation and substructure ratios like D2, C2, tau21, and tau32, pull-angle concentration, and same-direction soft-component counts. On top of that the chapter adds a morphology pair: a signed track-based H summary for swirl strength and a leading-mode phase proxy whose stability is measured through Δφ1. All of these are translated into up/flat/down grades under one preregistered sign rule and then collapsed into the composite update score ΔC.
mechanism
Execution is built around transferability, not around one favored reconstruction. Multiple pp datasets spanning different pileup conditions are reconstructed with anti-kT jets, splitting trees are cross-checked, and particle-flow, track-based, and simulation particle-level jets are compared. The core stress test is a 3×3 grid: three pileup-suppression routes—PUPPI, SoftKiller, and constituent subtraction—crossed with a preregistered grooming scan. Feed-forward cards are then written from congestion variables alone, the measurement team grades trends blindly, and adjudication scores hit, wrong-sign, and null-hit rates by channel, by algorithm cell, and by data-taking period. Matched controls also separate color-flow and geometry by comparing dijets with photon-plus-jet and Z-plus-jet channels, while jet momentum, pseudorapidity, jet radius, and quark/gluon enrichment bins test portability.
evidence
The null suite is aimed squarely at algorithmic and instrumental mirages. Minimum-bias overlays create a controlled congestion gradient, while random and shifted cones bound soft-background bias in coherence and swirl observables. Jet-axis rotations test whether the effect is definition-driven rather than channel-driven. Color-clean controls compare dijets with photon or Z plus jet samples; if the direction flips there, the claim loses transferability. Additional negatives are just as strict: a signal that appears only in simulation jets, only under one grooming choice, or only through track or vertex mis-association returns to subtraction bias. And if swirl phases lock to detector segmentation, readout time windows, or threshold settings, the court treats them as instrumental phase artifacts rather than physical support.
boundary
To pass, the update rule must remain coherent in more than one sense. At least two channels and two independent pipelines must show the same monotonic direction for the core coherence stack and for the H / Δφ1 morphology proxies, with feed-forward hit rates above random baselines. The strength ordering of those updates must be explained better by ρ_local than by the global congestion measures μ or ρ, and that ordering must persist across data-taking periods and across the full 3×3 grid. The result must also survive minimum-bias overlays, random or shifted cones, jet-axis rotations, and color-clean controls without sign flips. Failure is declared if coherence generally dilutes, if algorithms disagree, if controls reverse the direction, or if local versus global congestion cannot be distinguished. The main systematics are pileup and underlying-event modeling, trigger/selection-driven quark–gluon composition shifts, and detector timing or out-of-time pileup.
interface
So 33.18 leaves the court as a translated protocol, not as a new ontology block. If the congestion binning, sign rules, prediction cards, holdouts, and open-release materials all survive while core coherence indicators and the H / Δφ1 Swirl Texture proxies keep one direction across channels, periods, and algorithm cells, then the chapter certifies a particle-level morphology and color-flow update rule. If not, it falls back to pileup, grooming, phase-locking, or detector-coupling explanations. Even on a pass, texture-channel, road-network, and energy-sea wording stays at readout level. The route forward is into 33.19’s next boundary-laboratory window, not into a finished verdict on high-energy ontology.