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Mar 14 – 16, 2025
US/Pacific timezone

Machine Learning approach to determine the transverse single spin assymetry in J/ψ production in SpinQuest experiment

Not scheduled
20m
parallel

Speaker

Dr Chatura Kuruppu (New Mexico State University)

Description

The transverse single-spin asymmetry (TSSA) measures the asymmetry in particle production relative to the plane defined by the transverse spin axis and the momentum direction of a polarized hadron. TSSAs have emerged as a powerful tool for exploring Quantum Chromodynamics (QCD), offering insights into the dynamics of initial-state hadrons and the hadronization process. In J/ψ production, which involves initial-state gluons, TSSA measurements provide valuable information about gluon dynamics within the nucleon. The SpinQuest experiment (E1039) at Fermilab utilizes a 120 GeV unpolarized proton beam impinging on a polarized fixed target composed of NH$_3$ or ND$_3$. The primary goal is to extract the Sivers functions for light sea quarks in the kinematic range $0.1 < x_B < 0.5$. The analysis employs an event-mixing method to estimate combinatorial backgrounds and leverages machine learning techniques, including Gaussian Process Regressors (GPR), to efficiently model backgrounds using sidebands. We also use Bayesian iterative unfolding, in addition to GPR to correct detector inefficiencies. These measurements are critical for constraining the gluon Sivers function and provide a unique kinematic bridge between valence quark studies and the parameter space accessible in future Electron-Ion Collider (EIC) experiments. This talk will present the current status of the SpinQuest experiment and preliminary findings from beam commissioning data.

This work was supported in part by US DOE grant DE-FG02-94ER40847.

Primary author

Dr Chatura Kuruppu (New Mexico State University)

Presentation materials

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