Nuclear physicists test whether next generation artificial intelligence and machine learning tools can process experimental data in real time.
New results could significantly improve resonance ionization mass spectrometry ultra-trace analysis of plutonium isotopes.
Particles choose partners for short-range correlations differently when farther apart in light nuclei versus when packed closer together in heavy nuclei.
As machine learning tools gain momentum, a review of machine learning projects reveals these tools are already in use throughout nuclear physics.
The results of parity-violating electron scattering experiments PREX and CREX suggest a disagreement with global nuclear models.
A theoretical analysis of recent findings in neutron star research suggests the possibility of a phase transition in these stars’ interiors.
New measurements show the proton’s electromagnetic structure deviates from theoretical predictions.
Deblurring, practiced in optics, can reveal three-dimensional features of nuclear collisions.
Nuclear physicists find that the internal structures of protons and neutrons may be altered in different ways inside nuclei.
A first-of-its-kind measurement of the rare calcium-48 nucleus found a neutron-rich “thin skin” around a core of more evenly distributed protons and neutrons.
Colliding gold nuclei at various energies enables scientists to investigate phases of nuclear matter and their possible co-existence at a critical point.
Predictions for future measurements at the Electron-Ion Collider may help solve ‘proton spin’ mystery.
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