Gravitation & Nuclear · Physics & Astronomy
Nuclear Experiment
The newest papers in Nuclear Experiment that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
68 papers, from 8 September 2026 to 5 November 2026: 68 arXiv preprints.
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Newest papers, page 4
Machine-learning-based neutrino-event generation constrained by experimental measurements
We present a generative surrogate for charged-current \(ν_μ\)-nucleus scattering that can be calibrated to measured differential cross sections without event-level experimental samples.How Quantum Is Bottomonium in the Quark-Gluon Plasma?
We study how much quantum structure bottomonium retains during its evolution in the quark-gluon plasma.Infrared Subtraction with Artificial Intelligence
We present AI-developed local infrared subtraction, building on projection to Born and EFT matching.Physics-Informed Self-Supervised Learning for Joint Wire Calibration and Interaction Position Reconstruction in Multi-Wire Parallel Plate Avalanche Counters
Scientific instruments require accurate calibration to convert detector signals into reliable physical observables.Machine Learning for Invisible Dark Boson Searches at the Electron-Ion Collider
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…Learning Nuclear Structure with AI: Radii and Collectivity
Low-energy nuclear structure is encoded in a broad body of experimental information across the chart of nuclides.Automated Physics-Informed Neural-Networks-Based Calibration of Highly Segmented Silicon Telescopes
Transfer and multi-nucleon transfer reactions are essential tools for probing nuclear structure and reaction dynamics, requiring precise determination of the identity, energy, and emission angles of…Inclusive electron-nucleus cross section models from domain adaptation
We apply transfer learning (TL) to construct data-driven models of inclusive electron-nucleus cross sections.