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Spectrum of hadrons with strangeness

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arxiv 1204.2553 v1 pith:JVONSUTJ submitted 2012-04-11 nucl-th hep-lathep-phnucl-ex

classification nucl-thhep-lathep-phnucl-ex
keywords spectrumbaryonanalysisbaryonsfoundationhadronsmesonstrangeness
verification ladder T0 review T1 audit T2 compute T3 formal
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We describe a calculation of the spectrum of strange and nonstrange hadrons that simultaneously correlates the dressed-quark-core masses of meson and baryon ground- and excited-states within a single framework. The foundation for this analysis is a symmetry-preserving Dyson-Schwinger equation treatment of a vector-vector contact interaction. Our results exemplify and highlight the deep impact of dynamical chiral symmetry breaking on the hadron spectrum: an accurate description of the meson spectrum entails a similarly successful prediction of the spectrum of baryons, including those with strangeness. The analysis also provides numerous insights into baryon structure. For example, that baryon structure is largely flavour-blind, the first radial excitation of ground-state baryons is constituted almost entirely from axial-vector diquark correlations, and DCSB is the foundation for the ordering of low-lying baryon levels; viz., (1/2)^+, (1/2)^+, (1/2)^-.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Space- and time-like electromagnetic form factors of the $\mathbf{\Omega}$ baryon

    hep-ph 2026-06 unverdicted novelty 6.0 of 10

    Predictions for space- and time-like electromagnetic form factors of the Ω baryon obtained in rainbow-ladder DSE with vector⊗vector contact interaction and Poincaré-covariant Faddeev equation.

  2. Insights into the $\mathbf{\gamma^{(*)} + N(940)\frac{1}{2}^+ \to \Delta(1700)\frac{3}{2}^{-}}$ transition

    hep-ph 2025-02 accept novelty 6.0 of 10

    First SCI-DSE quark-diquark calculation of the gamma* N -> Delta(1700) transition form factors and helicity amplitudes, benchmarked against JLab and CLAS data.

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