Accurate description of low-density nuclear matter is critical to explaining the physics of the neutron star’s crust, according to a team of theoretical physicists led by Argonne National Laboratory. Dr. Alessandro Lovato.
The inner crust of a neutron star is characteristic Due to the existence of neutron superfluid.
A superfluid is a fluid that has no viscosity. In a neutron star, this means that the superfluid allows neutrons to flow without resistance.
To accurately predict the properties of neutronic matter at the lowest energy levels in this low-density form, researchers typically perform theoretical calculations that assume that neutrons combine to form Cooper pairs.
“The low-density nuclear material found in the crust of neutron stars exhibits complex and interesting structures that vary greatly with density,” Lovato and colleagues said.
“In the outer shell, the nucleons are bound to fully ionized nuclei. As the density increases within this region, these nuclei become increasingly neutron-rich, so in ground-based experiments they are present at lower densities. It is only possible to directly determine the main nuclides that
physicist used Artificial neural networks do not rely on this assumption to make accurate predictions.
They modified the standard “single particle” approach by introducing “hidden” neutrons that facilitate interactions between “real” neutrons and encode quantum many-body correlations.
This allows Cooper pairs to appear naturally during calculations.
“Understanding neutron superfluidity provides important insights into neutron stars,” the researchers said.
“This reveals phenomena such as its cooling mechanisms, rotation, and sudden changes in rotational speed.”
“Although we cannot directly access neutron star material experimentally, the fundamental interactions that govern the behavior of this material are the same as those that govern the nuclei of atoms on Earth.”
“Researchers are working to create simple yet predictable nuclear interactions.”
“Solving the quantum many-body problem accurately is an important part of assessing the quality of these interactions.”
“Our study uses simple interactions that are in good agreement with previous calculations that assumed more complex interactions.”
Low-density neutronic matter is characterized by fascinating emergent quantum phenomena, such as the formation of Cooper pairs and the onset of superfluidity.
“We used a combination of artificial neural networks and advanced optimization techniques to study this dense region,” the scientists said.
“Using a simplified model of the interaction between neutrons, we calculated the energy per particle and compared the results with those obtained from very realistic interactions.”
“This approach is competitive compared to other computational techniques at a fraction of the cost.”
_____
Bryce Foer others. 2024. Investigating the crust of a neutron star with the quantum state of a neural network. arXiv: 2407.21207
Bryce Foer others. 2023. Diluting neutron star material from quantum states in neural networks. Physics. Rev. Research 5(3):033062;doi: 10.1103/PhysRevResearch.5.033062
Source: www.sci.news