Finding the best indicator of a galaxy’s metallic content

A team of astronomers has discovered that the total mass of stars in a galaxy is not a good indicator of the abundance of heavier elements in the galaxy, a surprising result according to previous studies. Instead, a galaxy’s gravitational potential is a much better indicator. The results are published in the journal Astronomy and astrophysics.

This is important because when studying and classifying galaxies, “scaling relationships” play an important role in understanding galaxy formations and evolutions. These are meaningful relationships that help predict other properties of a star, nebula and galaxy if some simpler properties are known, for example trends between properties such as mass, size, brightness and colors.

When studying galaxies, an often reported relationship concerns the “metallicity” of the galaxy. Because the vast majority of the ordinary (non-dark) mass in the universe – about 98% – is hydrogen or helium, astronomers call the rest of the “metals” and their abundance “metallicity.” Metals were produced a long time (relatively) after the Big Bang, so the degree of metallicity of an object is an indication of stellar activity after the Big Bang.

Metallicity is defined as the mass fraction of metals divided by the mass of the star, nebula or galaxy. (In practice, astronomers have several methods for calculating metallicity, but all indicate the degree of heavier elements.) In practice, only oxygen or iron are often used as indicators of metallicity. Oxygen is the most abundant heavy element in the universe, and iron is also common because it has the most stable nucleus.

In the current study, led by Laura Sánchez-Menguiano of the University of Granada in Spain, the group used data on more than 3,000 nearby star-forming galaxies from the Mapping Near Galaxies survey carried out at the Apache Point Observatory in New Mexico, United States. .

Using 148 parameters that describe some aspect of each galaxy in this set, the group used a computer algorithm called the “random forest regressor algorithm” to establish scaling relationships between the many galactic parameters, for this entire group of galaxies. , in order to find the one that best predicts the metallicity of the gas phase of the galaxy, which is the metallicity of the gases present in the interstellar medium of the galaxy.

For the metallicity of the gas phase, they used as an indicator the ratio between the abundance of oxygen – a chemical that traces the evolution of galaxies – and the mass of hydrogen, measured at a distance of one effective radius of the galaxy.

The amount of metals in galaxies gradually increases, as stars continually form within a galaxy and stars go supernova, dumping all their elemental mass into the galactic interstellar medium. The internal processes of galaxies, along with other external processes, leave an imprint on the metallicity of the gas phase, which astronomers believe is a very powerful tool for understanding the characteristics and development of galaxies.

The random forest algorithm is a supervised machine learning technique that astronomers have widely used with great success in the astronomical community. The technique used a combination of decision trees that search for input features that contain the most information about an output or target feature. Here, the input features were the many galactic properties, and the target feature was the metallicity of the gas phase.

Ultimately, the algorithm, through the many combinations of decision trees, creates a model to predict the target feature using a set of conditions on the values ​​of the many input features.

The regression showed that the best indicator of gas phase metallicity was the galaxy’s baryonic gravitational potential, the ratio of stellar mass to effective radius. (The gravitational constant G is not included, because it’s a constant that only gets in the way and could always be added later if desired.)

Baryons are particles, like the proton or neutron, made up of three constituents: quarks. These particles interact via the strong force, so the electron is not a baryon. (In any case, the mass of a proton and neutron is nearly 2,000 times that of an electron, so electrons contribute very little to stellar and interstellar mass.)

The baryonic gravitational potential of a galaxy gives a better prediction of the metallicity of the gas phase than the galactic stellar mass. In fact, the analysis showed that the strongest dependence was the ratio (total star mass to effective radius) to the power of 0.6. The result was good for galactic masses between 300 million and 300 billion times the mass of the sun. The group argues that the power 0.6, less than one, explains the inclusion of dark matter in the galaxy.

“Finding the closest, most fundamental relationships helps us improve our understanding of how galaxies work and is crucial for refining future simulations,” Sánchez-Menguiano said. “It is important now to study the role of this parameter on other processes undergone by a galaxy during its life in order to improve our understanding of the overall process of galaxy formation and evolution.”

Nevertheless, the study revealed that the baryonic gravitational potential alone cannot predict the metallicity of the gas phase, and that other secondary parameters could play a notable role in its determination. A future study is underway to explore these relationships further.

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