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Machine Learning for Invisible Dark Boson Searches at the Electron-Ion Collider

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

We investigate whether adding $t$, the positive magnitude of the squared nuclear four-momentum transfer, enables boosted decision trees (BDTs) to improve invisible-dark-boson selection relative to optimized rectangular cuts at the Electron-Ion Collider. We model coherent exclusive scalar and vector production at generator level in electron-gold collisions at 18 GeV by 100 GeV per nucleon. Both methods use identical weighted samples, inputs, preselection, and optimization objectives. Using only electron information, the BDT provided no consistent advantage over optimized cuts for signal selecti

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First collected: 2026-09-23T12:01:45.602Z. This is not the publication date.