Physicists Find Evidence for Superfluidity in Low-Density Neutron Matter

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts, according to a team of theoretical physicists led by Argonne National Laboratory’s Dr. Alessandro Lovato.

The inner crust of a neutron star is characterized by the presence of a neutron superfluid.

A superfluid is a fluid that has no viscosity. In a neutron star, this means the superfluid allows neutrons to flow without resistance.

To accurately predict the properties of neutron matter at its lowest energy levels in this low-density form, researchers make theoretical calculations that typically assume that neutrons join together to form Cooper pairs.

“Low-density nuclear matter found in the crust of neutron stars exhibits a complex and fascinating structure that varies significantly with density,” Dr. Lovato and his colleagues said.

“In the outer crust, nucleons are bound to fully ionized nuclei. As density increases within this region, these nuclei become increasingly neutron-rich, and consequently, terrestrial experiments can only directly determine the dominant nuclei species that are present at lower densities.”

The physicists used artificial neural networks to make accurate predictions without relying on this assumption.

They modified the standard ‘single-particle’ approach by introducing ‘hidden’ neutrons that facilitate interactions among the ‘real’ neutrons and encode quantum many-body correlations.

This allows Cooper pairs to emerge naturally during the calculation.

“Understanding neutron superfluidity provides important insights into neutron stars,” the researchers said.

“It sheds light on their cooling mechanisms, their rotation, and phenomena such as glitches — sudden changes in their rotation rate.”

“While we cannot directly access neutron star matter experimentally, the fundamental interactions that govern this matter’s behavior are the same as those that govern atomic nuclei on Earth.”

“Researchers are working to construct nuclear interactions that are simple, yet predictive.”

“Accurately solving the quantum many-body problem is a crucial part of assessing the quality of these interactions.”

“Our work uses simple interactions that agree well with previous calculations that assume much more complex interactions.”

Low-density neutron matter is characterized by fascinating emergent quantum phenomena, such as the formation of Cooper pairs and the onset of superfluidity.

“We used artificial neural networks alongside advanced optimization techniques to study this density regime,” the scientists said.

“Using a simplified model of the interactions between neutrons, we calculated the energy per particle and compared the results to those obtained from highly realistic interactions.”

“This approach is competitive with other computational methods at a fraction of the cost.”

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Bryce Fore et al. 2024. Investigating the crust of neutron stars with neural-network quantum states. arXiv: 2407.21207

Bryce Fore et al. 2023. Dilute neutron star matter from neural-network quantum states. Phys. Rev. Research 5 (3): 033062; doi: 10.1103/PhysRevResearch.5.033062