Stromgren photometric metallicity map of the Magellanic Cloud stars using Gaia DR three-XP spectra

Stromgren photometric metallicity map of the Magellanic Cloud stars using Gaia DR three-XP spectra

ABSTRACT

Context. One key to understanding a galaxy's evolution is studying the consequences of its past dynamical interactions that have influenced its shape. By measuring the metallicity distribution of stellar populations with different ages, one can learn about these interactions. The Magellanic Clouds, being the nearest pair of interacting dwarf galaxies with a morphology characterised by different tidal and kinematic sub-structures as well as a vast range of stellar populations, represent an excellent place to study the consequences of dwarf-dwarf galaxy interactions and the interactions with their large host, the Milky Way.

Aims. We aim to determine the metallicities of red giant branch (old) and supergiant (young) stars covering the entire galaxies, estimate their radial metallicity gradients, and produce homogeneous metallicity maps.

Methods. We used the XP spectra from Gaia Data Release three to calculate synthetic Strömgren magnitudes from the application of the GaiaXPy tool and adopted calibration relations from the literature to estimate the photometric metallicities.

Results. We present photometric metallicity maps for approximately ninety thousand young stars and approximately two hundred seventy thousand old stars within approximately eleven degrees of the Small Magellanic Cloud and approximately twenty degrees of the Large Magellanic Cloud from a homogeneous dataset. We find that the overall radial metallicity gradients decrease linearly, in agreement with previous studies. Thanks to the large stellar samples, we could apply piecewise-regression fitting to derive the gradients within different radial regions. The catalogues containing the estimated photometric metallicities from this work are made available at the CDS.

Conclusions. The overall metallicity gradients, traced by young and old stars, decrease from the centre to the outskirts of both galaxies. However, they show multiple breakpoints, depicting regions following different and sometimes opposite trends. These are associated with the structure of the galaxies and their history of star formation and chemical evolution but may be influenced by a low number of sources, especially at the centre (due to crowding) and in the outermost regions.

One. Introduction

Galaxies are a multi-component (bar, bulge, disc, spiral arms, halo made of baryonic and dark matter) diverse class of objects with distinct structural, kinematical, and chemical properties. They are found both in isolation as well as in groups and clusters. Morphologically, they have been classified as ellipticals, spirals and irregulars. The low mass and less luminous counterparts of these objects are classified as dwarfs, which are the most abundant type of galaxies in the Universe. Observationally, groups and clusters of galaxies are ubiquitous. A cluster is dense, populous and typically consists of a few tens to hundreds of galaxies bound by gravity. Whereas, a galaxy group consists of a few massive galaxies surrounded by many satellites, mostly dwarfs that have not yet dissolved or merged with their host galaxy. In the environment of galaxy clusters and groups, dynamical processes such as tidal and ram-pressure stripping play a vital role in driving galaxy evolution. The cold dark matter model suggests that the dark matter halos grow hierarchically (bottom-up scenario); that is, larger halos are formed by the merging of smaller ones. A detailed exploration of how this physical process affects the host and satellite galaxy is required to understand galaxy evolution in general. A system involved in both dwarf-dwarf interactions and interactions with its host (a more massive galaxy) is then an excellent place to explore the implications of both phenomena.

One such pair of interacting galaxies is the Large Magellanic Cloud and the Small Magellanic Cloud, which are two prominent satellites of the Milky Way. They are both gas-rich dwarf irregulars and are collectively known as the Magellanic Clouds. The Large Magellanic Cloud is characterised by an inclined disc, a major spiral arm and an off-centred bar, along with having evidence of warps. It is located at a distance of fifty plus or minus two kiloparsecs and is in proximity of the Small Magellanic Cloud (sixty-two plus or minus one kiloparsecs). The Small Magellanic Cloud is characterised by an irregular shape, a wing towards the Large Magellanic Cloud and a large line-of-sight depth. Low-density stellar structures have been identified at the galaxy's front (Leading Arm) and trailing (Magellanic Stream) ends as well as between the Large Magellanic Cloud and Small Magellanic Cloud (Magellanic Bridge). These features are also prominent in HI maps. In addition, several stellar sub-structures have been found using various tracers, which exhibit themselves as signatures of dynamical interactions. Some of these sub-structures have also been associated with the influence of the Milky Way. Hence, the Magellanic Clouds (hereafter, 'the Clouds') can serve as an excellent laboratory to study dwarf-galaxy interactions utilising resolved stellar populations.

We expect the stellar structures that formed during the origin of the Bridge (approximately three hundred million years ago) and Stream (approximately one point five billion years ago) to show old stars stripped from the galaxies through dynamical interactions. Previous studies found intermediate-age or old stars (greater than two billion years old) around the Bridge, but the interpretation of their location is inconsistent. Some studies support a tidal origin for the presence of intermediate-age stars, while others suggest them as part of the overlapping stellar halos of the Clouds. Since the Stream is vastly spread in the sky, it is not trivial to identify any star associated with a tidally stripped population. Some Stream debris was discovered, and more recently, a sample of about forty very metal-poor stars were tentatively associated with the Stream.

Metallicity and abundance estimates are key parameters to determining the chemical composition and also hint at the formation history and evolution of galaxies. Recent studies have significantly advanced our understanding of the metallicity distribution in Clouds by using both photometry and spectroscopy. Photometric metallicity maps of the Large Magellanic Cloud (approximately four degrees from the center) and the Small Magellanic Cloud (approximately two point five degrees from the center) have been produced using the slope of the red giant branch as an indicator of the average metallicity of a sub-region and calibrated using spectroscopic data. Building upon this work, another study extended the analysis to a larger area of the Small Magellanic Cloud (approximately four degrees from the center) and the Large Magellanic Cloud (approximately five degrees from the center). Grady et al. chemically mapped the entire Clouds using data from Gaia Data Release Two. They utilized machine learning methods and obtained photometric metallicity estimates for the selected red giant branch stars using the spectroscopic metallicities from the Apache Point Observatory Galactic Evolution Experiment as training samples. More recently, Frankel et al. used Gaia Data Release Three data to construct mono-age and mono-abundance maps of the Large Magellanic Cloud, while Li et al. used the tip of the red giant branch stars, which has less sensitivity to interstellar reddening, to create metallicity maps of the Clouds.

Spectroscopic metallicities are available for only a few thousand giant stars, and for other young populations, metallicities are available for even fewer stars. These measurements were also obtained using various facilities and from different instruments with varying spectral resolutions that may collectively introduce systematic uncertainties in the study of metallicity distributions. For example, Dobbie et al. estimated the metallicity gradient from the observation of red giant branch stars to be negative zero point zero seven five plus or minus zero point zero one one dex per degree out to five degrees from the center of the Small Magellanic Cloud. Choudhury et al. obtained a gradient of negative zero point zero three one plus or minus zero point zero zero five dex per degree in the inner two point five degree region, flattening to four degrees. De Bortoli et al. investigated the metallicities of Small Magellanic Cloud stellar clusters and surrounding field stars, finding that there is a bimodal distribution comprising metal-poor and metal-rich group of clusters, which is contrary to the unimodal metallicity for the Small Magellanic Cloud field stars. In addition, various studies have used different calibration relations to estimate the metallicities of similar and other stellar tracers in the Clouds. In general, there is a lack of homogeneous and spatially extended metallicity samples that represent both the young and old stellar populations of the Clouds. These samples are essential for studying the sub-structural features in the outskirts, which will help in determining their origins and mutual association.

Gaia Data Release Three provides low-resolution (R equals twenty to eighty) spectrophotometry for around two hundred twenty million sources, in the ranges three hundred thirty to six hundred eighty nanometers (BP) and six hundred forty to one thousand fifty nanometers (RP), which together are referred to as XP. A recent study by Andrae et al. used these spectra to obtain data-driven stellar metallicities of approximately one hundred seventy-five million sources, including sources in the Clouds. They estimated the metallicities of the stars using the XGBoost algorithm utilizing the infrared photometric data from the ALLWISE programme and Gaia parallaxes by training their algorithm also on the Apache Point Observatory Galactic Evolution Experiment sample. In their work, the addition of the parallaxes as one of the input parameters improved the metallicity estimates by approximately ten percent. They presented a vetted sample with just the red giant branch stars after applying quality cuts mainly using the parity values to remove the most distant sources, especially those in the Clouds. The potential of this full-spectrum fitting method will further improve with subsequent data releases from Gaia by fixing the systematics in the spectra and aspects of the modeling. Another way of estimating the stellar metallicities from the XP spectra is by using synthetic photometry, where the transmission curve of the chosen photometric bands are completely covered by the Gaia Data Release Three-XP realm, to obtain the magnitudes and color indices from GaiaXPy and then by using relevant calibration relations to estimate the photometric metallicities. This has also been demonstrated in Gaia Collaboration. Although this is an indirect way of inferring the metallicities of stars, it does have advantages over traditional spectroscopic metallicities. It is less time-consuming, and hence the metallicity estimates can be made for a large sample using the same method. Bellazzini et al. used this method and the available calibration relations from the literature to estimate photometric metallicities for six hundred ninety-four thousand two hundred thirty-three Galactic giant stars from Gaia Data Release Three synthetic Strömgren photometry. The advantage of this method is that it can also be expanded and applied to young stars, such as supergiant stars, by using appropriate calibration relations from the literature to estimate their metallicities. This is especially useful in the case of the Clouds, where there are stellar populations of different ages and where a comparison of their metallicities can provide details about the chemical enrichment process within the galaxies.

In this work, we utilize the homogeneous data sample from the Gaia Data Release Three-XP spectra, encompassing the entire Large Magellanic Cloud and Small Magellanic Cloud, to estimate their photometric metallicities (iron to hydrogen) of both young and old stars, therefore expanding the method utilized by Bellazzini et al. We compare these metallicities with the Apache Point Observatory Galactic Evolution Experiment estimates to validate our method, and we also estimate the metallicity gradients. In Section Two, we provide details on the selection of our data sample. In Section Three, we discuss the synthetic photometry method, and in Section Four, we explain the estimation of the photometric metallicities. In Section Five, we present our results, and we discuss their interpretation in Section Six, which concludes our study.