A Refined Variational Framework for Proton Structure: Resolving Spin Dynamics, Calibration, and Deep QCD Observables
Year: 2025
Type: dissertation
Abstract: RETRACTED BY THE AUTHOR — 26 August 2026 This work is retracted in full. All numerical results and all claimed agreements with experimental values are withdrawn and should not be cited or reused. The retraction is self-initiated following an adversarial re-audit. Grounds: the mass calibration is circular (κ = M_target/M_model forces the reported agreement by definition); Figure 1 shows a run in which the mass was never fitted, contradicting the results table in Section 10; two of the four references do not exist; the axial-charge definition is mathematically bounded below the value reported; and the objects named GPDs, TMDs and energy-momentum tensor components do not satisfy the defining properties of those quantities. Full retraction notice with reproducible evidence: doi:10.5281/zenodo.22115453 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- We present a refined variational framework for modeling the proton’s internal structure, integrating low-energy observables (mass, charge radius) with high-energy partonic distributions (GPDs, TMDs), spindependent interactions, and energy-momentum tensor diagnostics. The model uses a composite wavefunction with physically motivated basis functions, optimized via analytic gradients and JAX autodifferentiation. Unit calibration enables direct comparison to experimental data, while neutron and baryon extensions validate generalizability. We explicitly define the Hamiltonian, loss function, and regularization terms to avoid circular reasoning and ensure reproducibility. The model achieves 1–7% agreement with experimental values and offers a scalable alternative to lattice QCD.
Author: Rora, Alexandru
Language: English
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7083193870
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