An interpretable multitask deep learning framework maps transverse momentum distributions from coherent J/ψ photoproduction in 96Zr+96Zr ultra-peripheral collisions to multiple nuclear-structure indicators while identifying the kinematic regions driving each inference.
Massacrier [ALICE], [arXiv:2407.09707 [nucl-ex]]
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Predictions for J/Ψ photoproduction in peripheral OO collisions at the LHC indicate experimental feasibility and that combining results with PbPb data can constrain models of photon-induced processes.
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Ultra-Peripheral Collisions as a Nuclear-Structure Interferometer with Interpretable Multitask Deep Learning
An interpretable multitask deep learning framework maps transverse momentum distributions from coherent J/ψ photoproduction in 96Zr+96Zr ultra-peripheral collisions to multiple nuclear-structure indicators while identifying the kinematic regions driving each inference.
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Photoproduction of $J/\Psi$ in peripheral Oxygen-Oxygen collisions
Predictions for J/Ψ photoproduction in peripheral OO collisions at the LHC indicate experimental feasibility and that combining results with PbPb data can constrain models of photon-induced processes.