Probing Composite Structure and Spin-Orbit Coupling with GPDs in ${}^{4}$He
Antonio Garcia Vallejo, Matthew D. Sievert
TL;DR
We develop a first-principles framework to express the GPDs of a spin-0 composite target in terms of the GPDs of spin-1/2 constituents, weighted by boost-invariant light-front Wigner distributions. The theory combines momentum and spin decompositions, a rest-frame dictionary, and symmetry constraints to produce a master integral for unpolarized quark GPDs that reveals a new $ΔL·S$ spin-orbit coupling contributing to GPD mixing. The phenomenology on a simple ${}^{4}$He model shows how orbital motion and spin–orbit effects smear and modulate constituent GPDs, offering potential experimental signatures in DVCS on light nuclei and a data-to-AI training framework for future analyses. The approach generalizes to GTMDs and supports AI-driven interpretation for upcoming EIC and ALERT measurements.
Abstract
In this work, we derive a relation between the generalized parton distributions (GPDs) of a spin-0 composite hadron and the GPDs of its spin-$\tfrac{1}{2}$ constituents. The method decomposes matrix elements of the composite parent into matrix elements of its constituents, weighted by the Wigner distributions of the constituents inside the composite parent. Exploiting the boost invariance of the light-front Wigner distributions, we derive the dictionary between rest-frame and boosted-frame kinematics and use it to perform a Pauli matrix decomposition of the spin degree of freedom. The constraints of unbroken rotational, parity, and time-reversal invariance lead to a master integral for the quark GPDs of the spin-0 composite target. We also identify a novel $Δ\vec{L}\cdot\vec{S}$ form of spin-orbit coupling responsible for GPD mixing in composite hadrons which is absent in the case of transverse momentum dependent parton distributions (TMDs) of composite hadrons. We then apply the framework to a composite ${}^{4}$He target with simple phenomenological models to identify possible experimental signatures of composite-structure effects in light nuclei. The framework we have constructed here can be readily extended to the case of generalized TMDs (GTMDs), while the phenomenological framework is applicable both to analyses of light nucleus data and as training input for AI-assisted applications.
