February 26, 2024

Finding the best predictor of a galaxy’s metal content

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Predicted metallicity in gas phase (Zg) versus metallicity measured in gas phase. Credit: Astronomy and Astrophysics (2023). DOI: 10.1051/0004-6361/202346708

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Predicted metallicity in gas phase (Zg) versus metallicity measured in gas phase. Credit: Astronomy and Astrophysics (2023). DOI: 10.1051/0004-6361/202346708

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 in line with previous studies. Instead, a galaxy’s gravitational potential is a much better predictor. The findings are published in the journal Astronomy and Astrophysics.

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

When studying galaxies, a frequently reported relationship is with the “metallicity” of the galaxy. Because the vast majority of the common (non-dark) mass of the universe – about 98% – is hydrogen or helium, astronomers call the rest “metals” and call their abundance “metallicity.” Metals were produced long (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 a few ways to calculate metallicity, but they all indicate the degree of heavier elements.) In practice, often only oxygen or iron are used as proxies for metallicity. Oxygen is the most abundant heavy element in the universe, and iron is also common in having the most stable nucleus.

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


The relative importance of various galactic parameters to the scaling relationship of gas-phase metallicity. Φ is the baryonic gravitational potential. Credit: Open access under CC BY license (Creative Commons Attribution 4.0 International license).

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The relative importance of various galactic parameters to the scaling relationship of gas-phase metallicity. Φ is the baryonic gravitational potential. Credit: Open access under CC BY license (Creative Commons Attribution 4.0 International license).

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

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

The amount of metals in galaxies gradually increases as stars continually form in a galaxy, and as stars go supernova, expelling all of their elementary mass into the galactic interstellar medium. The internal processes of galaxies, as well as other external processes, leave an imprint on the metallicity of the gas phase, which astronomers have found to be 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 used extensively in the astronomical community with great success. The technique used a combination of decision trees that finds the 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 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 predictor 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 is a constant that just gets in the way and can always be added later if desired.)

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

The baryonic gravitational potential of a galaxy provides a better prediction of gas-phase metallicity than galactic stellar mass. In fact, the analysis showed that the strongest dependence was the ratio (total stellar mass over effective radius) raised 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 0.6 power, less than one, is responsible for the inclusion of dark matter in the galaxy.

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

Still, the study found evidence that baryonic gravitational potential alone cannot predict gas-phase metallicity, and other secondary parameters could play a notable role in its determination. A future study is underway to further investigate these relationships.

More information:
Laura Sánchez-Menguiano et al, Stellar mass is not the best predictor of galaxy metallicity, Astronomy and Astrophysics (2023). DOI: 10.1051/0004-6361/202346708

Diary information:
Astronomy and Astrophysics

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