Latest Articles for Nuclear Physics

Research at VAMOS++ improves methods for accurate nuclear reaction studies.

Scientists investigate the unexpected gallium anomaly in neutrino detection.

Exploring the complexities of parity violation and its implications in particle physics.

Researching neutrino behavior helps uncover fundamental physics and cosmic mysteries.

Examining new insights into pion-nucleus interactions and their significance in physics.

Researching how parity violation affects proton structure and fundamental physics.

A look into skyrmions and their significance in understanding nuclear matter and neutron stars.

Study of neutron stars reveals secrets about matter under extreme conditions.

An overview of quarkyonic matter and its significance in high-density environments.

Neural networks enhance the accuracy of predicting nuclear masses, bridging gaps in theoretical models.

This article explores neutrinos' impacts on supernovae and neutron star mergers.

Research advances our understanding of neutron stars through updated models and gravitational wave observations.

Insights into nickel production enhance distance measurements in astronomy.

A new method enhances predictions of nuclear properties using machine learning.

Using quantum computing to study the neutron drip line in oxygen isotopes.

This article explores the various shapes and behaviors of atomic nuclei.

Study reveals unique rotational behavior of pear-shaped Ru nucleus and its implications.

A look into atomic behavior during excitation and decay.

This article discusses machine learning's role in analyzing nuclear reactions.

Examining neutron distribution in atomic nuclei through recent experimental findings.

Examining the role of charm quarks in understanding Quark-Gluon Plasma.

Insights into coherent and incoherent photoproduction processes in nuclear physics.

This paper discusses measuring nuclear charge radii in Calcium and Lead using muonic atoms.

IMSRG-Net uses machine learning to streamline complex nuclear physics calculations.

Exploring kaon pairs in heavy-ion collisions reveals complex particle behavior.

Researchers investigate proton spin behaviors using transverse single-spin asymmetries at RHIC.

Using machine learning to improve nuclear fusion predictions through better parameter optimization.

Recent developments in gamma-ray spectroscopy enhance study of fission fragments.

This article discusses the structure and properties of heavy nuclei.

A look at superheavy elements and their implications for ultradense matter.

A new method enhances quantum Monte Carlo simulations for complex systems.

Research highlights discrepancies in nucleosynthesis predictions compared to observed element abundances.

This study uses deep learning to improve nuclear property predictions.

Research offers key insights into heat treatments for superconducting radio-frequency cavities.

Exploring the significance of gluon production in high-energy physics.

Researching quark-gluon plasma behavior under extreme conditions in heavy-ion collisions.

MINERvA study sheds light on nucleon structure through antineutrino interactions.

A look at scalar mesons and kaon-induced reactions in particle physics.

Examining jets to enhance our understanding of the quark-gluon plasma.

Research reveals complexities of nucleon structures and interactions with photons.