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Published on: November 15, 2013
Parametrization of Generalized Parton Distributions from t-Channel String Exchange in AdS Spaces.
Kiminad A Mamo1, Ismail Zahed2
1Physics Department, <a href="https://ror.org/03hsf0573">College of William & Mary</a>, Williamsburg, Virginia 23187, USA.
We present a new string-based method for nucleon generalized parton distributions (GPDs) valid for all skewness. This approach improves empirical extraction and analysis of GPDs in exclusive processes.
Area of Science:
- Nuclear Physics
- Particle Physics
- Quantum Chromodynamics
Background:
- Generalized Parton Distributions (GPDs) are crucial for understanding nucleon structure.
- Current models often face limitations with skewness dependence.
- Accurate GPD parametrization is essential for interpreting exclusive deep inelastic scattering experiments.
Purpose of the Study:
- To introduce a novel, model-independent string-based parametrization for nucleon quark and gluon GPDs.
- To develop a framework valid across all skewness values.
- To enhance the empirical extraction and global analysis of GPDs.
Main Methods:
- Utilizing conformal moments and representing GPDs as sums of spin-j nucleon A- and D-form factors.
- Deriving form factors from t-channel string exchange in Anti-de Sitter (AdS) spaces, ensuring Lorentz invariance and unitarity.
- Employing Mellin moments from empirical data to estimate form factors within a polynomiality-satisfying framework.
- Using Mellin-Barnes integrals with five Regge slope parameters to generate GPDs.
Main Results:
- Accurate production of various nucleon quark GPD types and symmetric nucleon gluon GPDs.
- Isovector nucleon quark GPD results show agreement with existing lattice data.
- The method successfully avoids the deconvolution problem for GPDs at any skewness.
Conclusions:
- The string-based parametrization offers a robust and versatile tool for nucleon structure studies.
- This approach significantly advances the ability to analyze GPDs in exclusive processes.
- It provides a first-time solution for handling GPD deconvolution across all skewness regimes.
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