Method Comparison for Hadron Spectroscopy Using Regge Trajectories and Hypergraph Features

A pilot dataset from 2026 integrates standard particle listings with hypergraph-based decay features to compare baryon and meson spectra. The dataset, authored by Julia Gao and published on figshare, employs orthogonal distance regression with bootstrap resampling to quantify uncertainties in Regge trajectory fits. It includes hypergraph-derived structural invariants as predictors of spectroscopic regularity and introduces a confidence framework for missing resonance predictions.

Use Cases

• Comparing linearity of Regge trajectories for baryons and mesons based on integrated particle listings.
• Predicting spectroscopic regularity using hypergraph-derived structural invariants like community purity and motif z-scores.
• Quantifying uncertainties in slope and intercept estimates for trajectory fits using bootstrap resampling methods.
• Generating confidence metrics for predictions of missing resonances based on structural decay coherence.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• Analysis includes a strong linear correlation (R² = 0.90) for 20 baryon resonances.
• Demonstrates a strong correlation (r = 0.88, p < 0.001) between scatter in fits and resonance width.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.5 KB, indicating limited scope.

Provenance

Source

figshare

Collection Method

Data framework integrating standard particle listings with hypergraph-based decay features, analyzed with orthogonal distance regression and bootstrap resampling.

Time Range

Pilot dataset from 2026.

Freshness

Last updated 2026-04-17 20:02:11; freshness should be verified.

Geography

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