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  • Too young to be so cool: lessons from three neutron stars

Too young to be so cool: lessons from three neutron stars

Written by  Thursday, 20 June 2024 08:00
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A neutron star

ESA’s XMM-Newton and NASA’s Chandra spacecraft have detected three young neutron stars that are unusually cold for their age. By comparing their properties to different neutron star models, scientists conclude that the oddballs’ low temperatures disqualify around 75% of known models. This is a big step towards uncovering the one neutron star ‘equation of state’ that rules them all, with important implications for the fundamental laws of the Universe.

Joining forces: four steps to discovery

The three oddball neutron stars being so cold makes them too dim for most X-ray observatories to see. “The superb sensitivity of XMM-Newton and Chandra made it possible not only to detect these neutron stars, but to collect enough light to determine their temperatures and other properties,” says Camille Diez, ESA research fellow who works on XMM-Newton data.

However, the sensitive measurements were only the first step towards being able to draw conclusions about what these oddballs mean for the neutron star equation of state. To this end, Nanda’s research team at ICE-CSIC combined the complementary expertise of Alessio Marino, Clara Dehman and Konstantinos Kovlakas.

Alessio led on determining the physical properties of the neutron stars. The team could deduce the temperatures of the neutron stars from the X-rays sent out from their surfaces, while the sizes and speeds of the surrounding supernova remnants gave an accurate indication of their ages.

Next, Clara took the lead on computing neutron star ‘cooling curves’ for equations of state that incorporate different cooling mechanisms. This entails plotting what each model predicts for how a neutron star’s luminosity – a characteristic directly related to its temperature – changes over time. The shape of these curves depends on several different properties of a neutron star, not all of which can be determined accurately from observations. For this reason, the team computed the cooling curves for a range of possible neutron star masses and magnetic field strengths.

Finally, a statistical analysis led by Konstantinos brought it all together. Using machine learning to determine how well the simulated cooling curves align with the oddballs’ properties showed that equations of state without a fast cooling mechanism have zero chance of matching the data.

“Neutron star research crosses many scientific disciplines, spanning from particle physics to gravitational waves. The success of this work demonstrates how fundamental teamwork is to advancing our understanding of the Universe,” concludes Nanda.


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