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Confront Holographic QCD with Regge Trajectories of vectors and axial-vectors

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arxiv 0710.0988 v2 pith:GHVKUV5Z submitted 2007-10-04 hep-ph hep-thnucl-th

classification hep-phhep-thnucl-th
keywords modeldimensionmesonssoft-wallreggeaxial-vectorchiraldp-dq
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We derive the general 5-dimension metric structure of the $Dp-Dq$ system in type II superstring theory, and demonstrate the physical meaning of the parameters characterizing the 5-dimension metric structure of the \textit{holographic} QCD model by relating them to the parameters describing Regge trajectories. By matching the spectra of vector mesons $\rho_1$ with deformed $Dp-Dq$ soft-wall model, we find that the spectra of vector mesons $\rho_1$ can be described very well in the soft-wall $D3-Dq$ model, i.e, $AdS_5$ soft-wall model. We then investigate how well the $AdS_5$ soft-wall model can describe the Regge trajectory of axial-vector mesons $a_1$. We find that the constant component of the 5-dimension mass square of axial-vector mesons plays an efficient role to realize the chiral symmetry breaking in the vacuum, and a small negative $z^4$ correction in the 5-dimension mass square is helpful to realize the chiral symmetry restoration in high excitation states.

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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. Proton Structure from a Soft-Wall Holographic QCD Model: Mass Spectrum, Form Factors, and Mechanical Properties

    hep-ph 2025-12 conditional novelty 4.0 of 10

    A soft-wall holographic model reproduces proton spectroscopy, form factors, radii, and J/ψ photoproduction, though the gravitational form factor D is an input-dependent ansatz.

  2. The nucleon structure from an AdS/QCD model in the Veneziano limit

    nucl-th 2025-02 reject novelty 4.0 of 10

    Using the VQCD holographic model, the authors compute four sets of proton observables that match experiment and lattice data, but many inputs are fitted rather than predicted.

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