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Jorge Sánchez Almeida

Publications and source records attributed to Jorge Sánchez Almeida.

11 recordsLinked to original sources

Search for Faint Lone Double-Peaked H$α$ Lines as IMBH Signatures in the MUSE Deep Field

Double-peaked H$α$ emission profiles can serve as potential signatures of accreting intermediate-mass black holes (IMBHs), particularly those residing outside galactic nuclei. Such features are expected to arise from rotating disk-like structures around black holes and can be used to identify elusive IMBH candidates. \citet{Almeida2022ApJ...934..100S} reported a sample of such double-peaked H$α$ sources in the MUSE-Wide survey, interpreting them as potential signatures of wandering IMBHs after systematically excluding alternative explanations. Their method relied on constructing H$α$ maps around central galaxies and visually identifying compact emission clumps in the surrounding halo regions. In this work, we revisit the analysis using the deeper MUSE Extremely Deep Field (MXDF) data and an automated detection algorithm tailored to identify such features. However, we do not recover any candidate population in MXDF, resulting in a null detection. This outcome is nevertheless informative, as it (1) highlights the inherent challenges in detecting IMBHs, and (2) demonstrates the potential of automated approaches for future systematic searches, even though it did not yield a positive outcome in this case.

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Why the Northern Hemisphere Needs a 30-40 m Telescope and the Science at Stake: A Low Surface Brightness Science Case

The Extragalactic Low Surface Brightness (LSB, $μ_V\gtrsim 27$ mag/arcsec$^2$) Universe represents a crucial, yet largely unseen, frontier in modern astrophysics. This faint realm holds the keys to completing our understanding of galaxy evolution, hierarchical assembly, and even the fundamental nature of dark matter. Our current theoretical models are inherently incomplete, largely mirroring the properties of the brightest, most easily observed objects. To overcome this critical bias and unlock the secrets of this realm, a transformative leap in observational capability is required. A 30 to 40m class telescope, leveraging unprecedented sensitivity and spatial resolution, especially with adaptive optics, is the essential tool to fundamentally probe these faint, low-density stellar regimes. This white paper details the transformative LSB science that such a facility, strategically positioned in the Northern Hemisphere (NH) to access crucial nearby structures and rich environments, can achieve.

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Deep HST imaging favors the bulgeless edge-on galaxy explanation for the hypothetical stellar wake created by a runaway supermassive black hole

A long linear structure recently discovered could be the stellar wake produced by the passage of a runaway supermassive black hole (SMBH) or, alternatively, a bulgeless edge-on galaxy. We report on new very deep HST imaging that seems to be in tension with the SMBH runaway scenario but is consistent with the bulgeless edge-on galaxy scenario. The new observations were aimed at detecting two key features expected in the SMBH scenario, namely, the bow shock formed where the SMBH meets the surrounding medium, and a counter stellar wake created by another binary SMBH hypothesized as part of the ejection mechanism. Neither of these two features appears to be present in the new images, as would be expected in the edge-on galaxy scenario.

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More fundamental than the fundamental metallicity relation: The effect of the stellar metallicity on the gas-phase mass-metallicity and gravitational potential-metallicity relations

Context. One of the most fundamental scaling relations in galaxies is observed between metallicity and stellar mass -- the mass-metallicity relation (MZR) -- although recently a stronger dependence of the gas-phase metallicity with the galactic gravitational potential ($Φ\rm ZR$) has been reported. Further dependences of metallicity on other galaxy properties have been revealed, with the star formation rate (SFR) being one of the most studied and debated secondary parameters in the relation (the so-called fundamental metallicity relation). Aims. In this work we explore the dependence of the gas-phase metallicity residuals from the MZR and $Φ\rm ZR$ on different galaxy properties in the search for the most fundamental scaling relation in galaxies. Methods. We applied a random forest regressor algorithm on a sample of 3430 nearby star-forming galaxies from the SDSS-IV MaNGA survey. Using this technique, we explored the effect of 147 additional parameters on the global oxygen abundance residuals obtained after subtracting the MZR. Alternatively, we followed a similar approach with the metallicity residuals from the $Φ\rm ZR$. Results. The stellar metallicity of the galaxy is revealed as the secondary parameter in both the MZR and the $Φ\rm ZR$, ahead of the SFR. This parameter reduces the scatter in the relations $\sim 10-15\%$. We find the 3D relation between gravitational potential, gas metallicity, and stellar metallicity to be the most fundamental metallicity relation observed in galaxies.

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Stellar mass is not the best predictor of galaxy metallicity. The gravitational potential-metallicity relation $Φ\rm ZR$

Interpreting the scaling relations followed by galaxies is a fundamental tool for assessing how well we understand galaxy formation and evolution. Several scaling relations involving the galaxy metallicity have been discovered through the years, the foremost of which is the scaling with stellar mass. This so-called mass-metallicity relation is thought to be fundamental and has been subject to many studies in the literature. We study the dependence of the gas-phase metallicity on many different galaxy properties to assess which of them determines the metallicity of a galaxy. We applied a random forest regressor algorithm on a sample of more than 3000 nearby galaxies from the SDSS-IV MaNGA survey. Using this machine-learning technique, we explored the effect of 148 parameters on the global oxygen abundance as an indicator of the gas metallicity. $M_{\rm \star}$/$R_e$, as a proxy for the baryonic gravitational potential of the galaxy, is found to be the primary factor determining the average gas-phase metallicity of the galaxy ($Z_g$). It outweighs stellar mass. A subsequent analysis provides the strongest dependence of $Z_g$ on $M_\star / R_e^{\,0.6}$. We argue that this parameter traces the total gravitational potential, and the exponent $α\simeq 0.6$ accounts for the inclusion of the dark matter component. Our results reveal the importance of the relation between the total gravitational potential of the galaxy and the gas metallicity. This relation is tighter and likely more primordial than the widely known mass-metallicity relation.

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Local and global gas metallicity versus stellar age relation in MaNGA galaxies

The search for new global scaling relations linking physical properties of galaxies has a fundamental interest. Furthermore, their recovery from spatially resolved relations has been one of the spotlights of integral field spectroscopy (IFS). In this study we investigate the existence of global and local relations between stellar age ($Age_\star$) and gas-phase metallicity ($Z_g$). To this aim, we analyze IFS data for a sample of 736 star-forming disk galaxies from the MaNGA survey. We report a positive correlation between the global $Z_g$ and $D(4000)$ (an indicator of stellar age), with a slope that decreases with increasing galaxy mass. Locally, a similar trend is found when analyzing the $Z_g$ and $D(4000)$ of the star-forming regions, as well as the residuals resulting from removing the radial gradients of both parameters. The local laws have systematically smaller slopes than the global one. We ascribe this difference to random errors, that make the true slope of the $Age_\star-Z_g$ relation to be systematically underestimated when performing a least square fitting. The explored relation is intimately linked with the already known relation between gas metallicity and star formation rate at fixed mass, both presenting a common physical origin.

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White Paper on MAAT@GTC

MAAT is proposed as a visitor mirror-slicer optical system that will allow the OSIRIS spectrograph on the 10.4-m Gran telescopio CANARIAS (GTC) the capability to perform Integral Field Spectroscopy (IFS) over a seeing-limited FoV 14.20''x10'' with a slice width of 0.303''. MAAT@GTC will enhance the resolution power of OSIRIS by 1.6 times as compared to its 0.6'' wide long-slit. All the eleven OSIRIS grisms and volume-phase holographic gratings will be available to provide broad spectral coverage with moderate resolution (R=600 up to 4100) in the 3600 - 10000 Å wavelength range. MAAT unique observing capabilities will broaden its use to the needs of the GTC community to unveil the nature of most striking phenomena in the universe well beyond time-domain astronomy. The GTC equipped with OSIRIS+MAAT will also play a fundamental role in synergy with other facilities, some of them operating on the northern ORM at La Palma. This White Paper presents the different aspects of MAAT@GTC - including scientific and technical specifications, outstanding science cases, and an outline of the instrument concept.

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Machine learning in APOGEE: Identification of stellar populations through chemical abundances

The vast volume of data generated by modern astronomical surveys offers test beds for the application of machine-learning. It is important to evaluate potential existing tools and determine those that are optimal for extracting scientific knowledge from the available observations. We explore the possibility of using clustering algorithms to separate stellar populations with distinct chemical patterns. Star clusters are likely the most chemically homogeneous populations in the Galaxy, and therefore any practical approach to identifying distinct stellar populations should at least be able to separate clusters from each other. We applied eight clustering algorithms combined with four dimensionality reduction strategies to automatically distinguish stellar clusters using chemical abundances of 13 elements. Our sample includes 18 stellar clusters with a total of 453 stars. We use statistical tests showing that some pairs of clusters are indistinguishable from each other when chemical abundances from the Apache Point Galactic Evolution Experiment (APOGEE) are used. However, for most clusters we are able to automatically assign membership with metric scores similar to previous works. The confusion level of the automatically selected clusters is consistent with statistical tests that demonstrate the impossibility of perfectly distinguishing all the clusters from each other. These statistical tests and confusion levels establish a limit for the prospect of blindly identifying stars born in the same cluster based solely on chemical abundances. We find that some of the algorithms we explored are capable of blindly identify stellar populations with similar ages and chemical distributions in the APOGEE data. Because some stellar clusters are chemically indistinguishable, our study supports the notion of extending weak chemical tagging that involves families of clusters instead of individual clusters

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Characterizing the local relation between star formation rate and gas-phase metallicity in MaNGA spiral galaxies

The role of gas accretion in galaxy evolution is still a matter of debate. The presence of inflows of metal-poor gas that trigger star formation bursts of low metallicity has been proposed as an explanation for the local anti-correlation between star formation rate (SFR) and gas-phase metallicity ($\rm Z_g$) found in the literature. In the present study, we show how the anti-correlation is also present as part of a diversified range of behaviours for a sample of more than 700 nearby spiral galaxies from the SDSS IV MaNGA survey. We have characterized the local relation between SFR and $\rm Z_g$ after subtracting the azimuthally averaged radial profiles of both quantities. $60\%$ of the analyzed galaxies display a $\rm SFR-Z_g$ anti-correlation, with the remaining $40\%$ showing no correlation ($19\%$) or positive correlation ($21\%$). Applying a Random Forest machine-learning algorithm, we obtain that the slope of the correlation is mainly determined by the average gas-phase metallicity of the galaxy. Galaxy mass, $g-r$ colors, stellar age, and mass density seem to play a less significant role. This result is supported by the performed 2nd-order polynomial regression analysis. Thus, the local $\rm SFR-Z_g$ slope varies with the average metallicity, with the more metal-poor galaxies presenting the lowest slopes (i.e., the strongest $\rm SFR-Z_g$ anti-correlations), and reversing the relation for more metal-rich systems. Our results suggest that external gas accretion fuels star-formation in metal-poor galaxies, whereas in metal-rich systems the gas comes from previous star formation episodes.

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Machine learning in APOGEE: Unsupervised spectral classification with $K$-means

The data volume generated by astronomical surveys is growing rapidly. Traditional analysis techniques in spectroscopy either demand intensive human interaction or are computationally expensive. In this scenario, machine learning, and unsupervised clustering algorithms in particular offer interesting alternatives. The Apache Point Observatory Galactic Evolution Experiment (APOGEE) offers a vast data set of near-infrared stellar spectra which is perfect for testing such alternatives. Apply an unsupervised classification scheme based on $K$-means to the massive APOGEE data set. Explore whether the data are amenable to classification into discrete classes. We apply the $K$-means algorithm to 153,847 high resolution spectra ($R\approx22,500$). We discuss the main virtues and weaknesses of the algorithm, as well as our choice of parameters. We show that a classification based on normalised spectra captures the variations in stellar atmospheric parameters, chemical abundances, and rotational velocity, among other factors. The algorithm is able to separate the bulge and halo populations, and distinguish dwarfs, sub-giants, RC and RGB stars. However, a discrete classification in flux space does not result in a neat organisation in the parameters space. Furthermore, the lack of obvious groups in flux space causes the results to be fairly sensitive to the initialisation, and disrupts the efficiency of commonly-used methods to select the optimal number of clusters. Our classification is publicly available, including extensive online material associated with the APOGEE Data Release 12 (DR12). Our description of the APOGEE database can enormously help with the identification of specific types of targets for various applications. We find a lack of obvious groups in flux space, and identify limitations of the $K$-means algorithm in dealing with this kind of data.

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The nearest ultra diffuse galaxy: UGC2162

We describe the structural, stellar population and gas properties of the nearest Ultra Diffuse Galaxy (UDG) discovered so far: UGC2162 (z=0.00392; R$_{e,g}$=1.7$(\pm$0.2) kpc; $μ_g(0)$=24.4$\pm$0.1 mag/arcsec$^2$; g-i=0.33$\pm$0.02). This galaxy, located at a distance of 12.3($\pm$1.7) Mpc, is a member of the M77 group. UGC2162 has a stellar mass of $\sim$2($^{+2}_{-1}$)$\times$10$^7$ M$_\odot$ and is embedded within a cloud of HI gas $\sim$10 times more massive: $\sim$1.9($\pm$0.6)$\times$10$^8$ M$_\odot$. Using the width of its HI line as a dynamical proxy, the enclosed mass within the inner R$\sim$5 kpc is $\sim$4.6($\pm$0.8)$\times$10$^9$ M$_\odot$ (i.e. M/L$\sim$200). The estimated virial mass from the cumulative mass curve is $\sim$8($\pm$2)$\times$10$^{10}$ M$_\odot$. Ultra-deep imaging from the IAC Stripe82 Legacy Project show that the galaxy is irregular and has many star forming knots, with a gas-phase metallicity around one-third of the solar value. Its estimated Star Formation Rate (SFR) is $\sim$0.01 M$_\odot$/yr. This SFR would double the stellar mass of the object in $\sim$2 Gyr. If the object were to stop forming stars at this moment, after a passive evolution, its surface brightness would become extremely faint: $μ_g(0)$$\sim$27 mag/arcsec$^2$ and its size would remain large R$_{e,g}$$\sim$ 1.8 kpc. Such faintness would make it almost undetectable to most present-day surveys. This suggests that there could be an important population of M$_{\star}$$\sim$10$^7$ M$_\odot$ "dark galaxies" in rich environments (depleted of HI gas) waiting to be discovered by current and future ultra-deep surveys.

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