| 11. |
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| 12. |
- Guiglion, G., et al.
(författare)
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Beyond Gaia DR3 : Tracing the [α/M] - [M/H] bimodality from the inner to the outer Milky Way disc with Gaia-RVS and convolutional neural networks
- 2024
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Ingår i: Astronomy and Astrophysics. - 0004-6361 .- 1432-0746. ; 682
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Tidskriftsartikel (refereegranskat)abstract
- Context. In June 2022, Gaia DR3 provided the astronomy community with about one million spectra from the Radial Velocity Spectrometer (RVS) covering the CaII triplet region. In the next Gaia data releases, we anticipate the number of RVS spectra to successively increase from several 10 million spectra to eventually more than 200 million spectra. Thus, stellar spectra are projected to be produced on an ‘industrial scale’, with numbers well above those for current and anticipated ground-based surveys. However, one-third of the published spectra have 15 ≤ S /N ≤ 25 per pixel such that they pose problems for classical spectral analysis pipelines, and therefore, alternative ways to tap into these large datasets need to be devised.Aims. We aim to leverage the versatility and capabilities of machine learning techniques for supercharged stellar parametrisation by combining Gaia-RVS spectra with the full set of Gaia products and high-resolution, high-quality ground-based spectroscopic reference datasets.Methods. We developed a hybrid convolutional neural network (CNN) that combines the Gaia DR3 RVS spectra, photometry (G, G_BP, G_RP), parallaxes, and XP coefficients to derive atmospheric parameters (Teff, log(g) as well as overall [M/H]) and chemical abundances ([Fe/H] and [α/M]). We trained the CNN with a high-quality training sample based on APOGEE DR17 labels.Results. With this CNN, we derived homogeneous atmospheric parameters and abundances for 886 080 RVS stars that show remarkable precision and accuracy compared to external datasets (such as GALAH and asteroseismology). The CNN is robust against noise in the RVS data, and we derive very precise labels down to S/N =15. We managed to characterise the [α/M] - [M/H] bimodality from the inner regions to the outer parts of the Milky Way, which has never been done using RVS spectra or similar datasets.Conclusions. This work is the first to combine machine learning with such diverse datasets and paves the way for large-scale machine learning analysis of Gaia-RVS spectra from future data releases. Large, high-quality datasets can be optimally combined thanks to the CNN, thereby realising the full power of spectroscopy, astrometry, and photometry.
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| 13. |
- Sales-Silva, J. V., et al.
(författare)
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A Perspective on the Milky Way Bulge Bar as Seen from the Neutron-capture Elements Cerium and Neodymium with APOGEE
- 2024
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Ingår i: Astrophysical Journal. - : Institute of Physics Publishing (IOPP). - 0004-637X .- 1538-4357. ; 965:2
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Tidskriftsartikel (refereegranskat)abstract
- This study probes the chemical abundances of the neutron-capture elements cerium and neodymium in the inner Milky Way from an analysis of a sample of similar to 2000 stars in the Galactic bulge bar spatially contained within divided by X-Gal divided by < 5 kpc, divided by Y-Gal divided by < 3.5 kpc, and divided by Z(Gal)divided by < 1 kpc, and spanning metallicities between -2.0 less than or similar to [Fe/H] less than or similar to +0.5. We classify the sample stars into low- or high-[Mg/Fe] populations and find that, in general, values of [Ce/Fe] and [Nd/Fe] increase as the metallicity decreases for the low- and high-[Mg/Fe] populations. Ce abundances show a more complex variation across the metallicity range of our bulge-bar sample when compared to Nd, with the r-process dominating the production of neutron-capture elements in the high-[Mg/Fe] population ([Ce/Nd] < 0.0). We find a spatial chemical dependence of Ce and Nd abundances for our sample of bulge-bar stars, with low- and high-[Mg/Fe] populations displaying a distinct abundance distribution. In the region close to the center of the MW, the low-[Mg/Fe] population is dominated by stars with low [Ce/Fe], [Ce/Mg], [Nd/Mg], [Nd/Fe], and [Ce/Nd] ratios. The low [Ce/Nd] ratio indicates a significant contribution in this central region from r-process yields for the low-[Mg/Fe] population. The chemical pattern of the most metal-poor stars in our sample suggests an early chemical enrichment of the bulge dominated by yields from core-collapse supernovae and r-process astrophysical sites, such as magnetorotational supernovae.
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| 14. |
- Hobbs, David, et al.
(författare)
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All-sky visible and near infrared space astrometry
- 2021
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Ingår i: Experimental Astronomy. - : Springer Science and Business Media LLC. - 0922-6435 .- 1572-9508. ; 51:3, s. 783-843
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Tidskriftsartikel (refereegranskat)abstract
- The era of all-sky space astrometry began with the Hipparcos mission in 1989 and provided the first very accurate catalogue of apparent magnitudes, positions, parallaxes and proper motions of 120 000 bright stars at the milliarcsec (or milliarcsec per year) accuracy level. Hipparcos has now been superseded by the results of the Gaia mission. The second Gaia data release contained astrometric data for almost 1.7 billion sources with tens of microarcsec (or microarcsec per year) accuracy in a vast volume of the Milky Way and future data releases will further improve on this. Gaia has just completed its nominal 5-year mission (July 2019), but is expected to continue in operations for an extended period of an additional 5 years through to mid 2024. Its final catalogue to be released ∼ 2027, will provide astrometry for ∼ 2 billion sources, with astrometric precisions reaching 10 microarcsec. Why is accurate astrometry so important? The answer is that it provides fundamental data which underpin much of modern observational astronomy as will be detailed in this White Paper. All-sky visible and Near-InfraRed (NIR) astrometry with a wavelength cutoff in the K-band is not just focused on a single or small number of key science cases. Instead, it is extremely broad, answering key science questions in nearly every branch of astronomy while also providing a dense and accurate visible-NIR reference frame needed for future astronomy facilities.
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| 15. |
- Myers, Natalie, et al.
(författare)
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The Open Cluster Chemical Abundances and Mapping Survey. VI. Galactic Chemical Gradient Analysis from APOGEE DR17
- 2022
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Ingår i: Astronomical Journal. - : IOP Publishing Ltd. - 0004-6256 .- 1538-3881. ; 164:3
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Tidskriftsartikel (refereegranskat)abstract
- The goal of the Open Cluster Chemical Abundances and Mapping (OCCAM) survey is to constrain key Galactic dynamic and chemical evolution parameters by the construction and analysis of a large, comprehensive, uniform data set of infrared spectra for stars in hundreds of open clusters. This sixth contribution from the OCCAM survey presents analysis of SDSS/APOGEE Data Release 17 (DR17) results for a sample of stars in 150 open clusters, 94 of which we designate to be "high-quality" based on the appearance of their color-magnitude diagram. We find the APOGEE DR17-derived [Fe/H] values to be in good agreement with those from previous high-resolution spectroscopic open cluster abundance studies. Using a subset of the high-quality sample, the Galactic abundance gradients were measured for 16 chemical elements, including [Fe/H], for both Galactocentric radius (R (GC)) and guiding center radius (R (guide)). We find an overall Galactic [Fe/H] versus R (GC) gradient of -0.073 +/- 0.002 dex kpc(-1) over the range of 6 > R (GC) < 11.5 kpc, and a similar gradient is found for [Fe/H] versus R (guide). Significant Galactic abundance gradients are also noted for O, Mg, S, Ca, Mn, Na, Al, K, and Ce. Our large sample additionally allows us to explore the evolution of the gradients in four age bins for the remaining 15 elements.
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| 16. |
- Sales-Silva, J. V., et al.
(författare)
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Exploring the S-process History in the Galactic Disk : Cerium Abundances and Gradients in Open Clusters from the OCCAM/APOGEE Sample
- 2022
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Ingår i: Astrophysical Journal. - : Institute of Physics (IOP). - 0004-637X .- 1538-4357. ; 926:2
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Tidskriftsartikel (refereegranskat)abstract
- The APOGEE Open Cluster Chemical Abundances and Mapping survey is used to probe the chemical evolution of the s-process element cerium in the Galactic disk. Cerium abundances were derived from measurements of Ce ii lines in the APOGEE spectra using the Brussels Automatic Code for Characterizing High Accuracy Spectra in 218 stars belonging to 42 open clusters. Our results indicate that, in general, for ages < 4 Gyr, younger open clusters have higher [Ce/Fe] and [Ce/α-element] ratios than older clusters. In addition, metallicity segregates open clusters in the [Ce/X]–age plane (where X can be H, Fe, or the α-elements O, Mg, Si, or Ca). These metallicity-dependent relations result in [Ce/Fe] and [Ce/α] ratios with ages that are not universal clocks. Radial gradients of [Ce/H] and [Ce/Fe] ratios in open clusters, binned by age, were derived for the first time, with d[Ce/H]/dRGC being negative, while d[Ce/Fe]/dRGC is positive. [Ce/H] and [Ce/Fe] gradients are approximately constant over time, with the [Ce/Fe] gradient becoming slightly steeper, changing by ∼+0.009 dex kpc−1 Gyr−1. Both the [Ce/H] and [Ce/Fe] gradients are shifted to lower values of [Ce/H] and [Ce/Fe] for older open clusters. The chemical pattern of Ce in open clusters across the Galactic disk is discussed within the context of s-process yields from asymptotic giant branch (AGB) stars, gigayear time delays in Ce enrichment of the interstellar medium, and the strong dependence of Ce nucleosynthesis on the metallicity of its AGB stellar sources.
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| 17. |
- Tempel, E., et al.
(författare)
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Probabilistic fibre-to-target assignment algorithm for multi-object spectroscopic surveys
- 2020
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 635
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Tidskriftsartikel (refereegranskat)abstract
- Context. Several new multi-object spectrographs are currently planned or under construction that are capable of observing thousands of Galactic and extragalactic objects simultaneously. Aims. In this paper we present a probabilistic fibre-to-target assignment algorithm that takes spectrograph targeting constraints into account and is capable of dealing with multiple concurrent surveys. We present this algorithm using the 4-m Multi-Object Spectroscopic Telescope (4MOST) as an example. Methods. The key idea of the proposed algorithm is to assign probabilities to fibre-target pairs. The assignment of probabilities takes the fibre positioner's capabilities and constraints into account. Additionally, these probabilities include requirements from surveys and take the required exposure time, number density variation, and angular clustering of targets across each survey into account. The main advantage of a probabilistic approach is that it allows for accurate and easy computation of the target selection function for the different surveys, which involves determining the probability of observing a target, given an input catalogue. Results. The probabilistic fibre-to-target assignment allows us to achieve maximally uniform completeness within a single field of view. The proposed algorithm maximises the fraction of successfully observed targets whilst minimising the selection bias as a function of exposure time. In the case of several concurrent surveys, the algorithm maximally satisfies the scientific requirements of each survey and no specific survey is penalised or prioritised. Conclusions. The algorithm presented is a proposed solution for the 4MOST project that allows for an unbiased targeting of many simultaneous surveys. With some modifications, the algorithm may also be applied to other multi-object spectroscopic surveys.
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| 18. |
- Ambrosch, M., et al.
(författare)
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The Gaia -ESO Survey : Chemical evolution of Mg and Al in the Milky Way with machine learning
- 2023
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 672
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Tidskriftsartikel (refereegranskat)abstract
- Context. To take full advantage of upcoming large-scale spectroscopic surveys, it will be necessary to parameterize millions of stellar spectra in an efficient way. Machine learning methods, especially convolutional neural networks (CNNs), will be among the main tools geared at achieving this task. Aims. We aim to prepare the groundwork for machine learning techniques for the next generation of spectroscopic surveys, such as 4MOST and WEAVE. Our goal is to show that CNNs can predict accurate stellar labels from relevant spectral features in a physically meaningful way. The predicted labels can be used to investigate properties of the Milky Way galaxy. Methods. We built a neural network and trained it on GIRAFFE spectra with their associated stellar labels from the sixth internal Gaia-ESO data release. Our network architecture contains several convolutional layers that allow the network to identify absorption features in the input spectra. The internal uncertainty was estimated from multiple network models. We used the t-distributed stochastic neighbor embedding tool to remove bad spectra from our training sample. Results. Our neural network is able to predict the atmospheric parameters Teff and log(g) as well as the chemical abundances [Mg/Fe], [Al/Fe], and [Fe/H] for 36 904 stellar spectra. The training precision is 37 K for Teff, 0.06 dex for log(g), 0.05 dex for [Mg/Fe], 0.08 dex for [Al/Fe], and 0.04 dex for [Fe/H]. Network gradients reveal that the network is inferring the labels in a physically meaningful way from spectral features. We validated our methodology using benchmark stars and recovered the properties of different stellar populations in the Milky Way galaxy. Conclusions. Such a study provides very good insights into the application of machine learning for the analysis of large-scale spectroscopic surveys, such as WEAVE and 4MOST Milky Way disk and bulge low- and high-resolution (4MIDABLE-LR and -HR). The community will have to put substantial efforts into building proactive training sets for machine learning methods to minimize any possible systematics.
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| 19. |
- Dantas, M. L. L., et al.
(författare)
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The Gaia-ESO Survey : Probing the lithium abundances in old metal-rich dwarf stars in the solar vicinity
- 2022
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 668
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Tidskriftsartikel (refereegranskat)abstract
- Context: Lithium (Li) is a fragile element that is produced in a variety of sites but can also be very easily depleted in stellar photospheres. Radial migration has been reported to explain the decrease in the upper envelope of Li measurements observed for relatively old metal-rich dwarf stars in some surveys.Aims: We test a scenario in which radial migration could affect the Li abundance pattern of dwarf stars in the solar neighbourhood. This may confirm that the Li abundances in these stars cannot serve as a probe for the Li abundance in the interstellar medium (ISM). In other words, to probe the evolution of the Li abundance in the local ISM, it is crucial that stellar intruders be identified and removed from the adopted sample.Methods: We used the high-quality data (including Li abundances) from the sixth internal Data Release of the Gaia-ESO survey. In this sample we grouped stars by similarity in chemical abundances via hierarchical clustering. Our analysis treats both measured Li abundances and upper limits.Results: The Li envelope of the previously identified radially migrated stars is well below the benchmark meteoritic value (<3.26 dex); the star with the highest detected abundance has A(Li) = 2.76 dex. This confirms the previous trends observed for old dwarf stars (median ages similar to 8 Gyr), where Li decreases for [Fe/H] greater than or similar to 0.Conclusions: This result is supporting evidence that the abundance of Li measured in the upper envelope of old dwarf stars should not be considered a proxy for the ISM Li. Our scenario also indicates that the stellar yields for [M/H] >0 should not be decreased, as recently proposed in the literature. Our study backs recent studies that claim that old dwarfs on the hot side of the dip are efficient probes of the ISM abundance of Li, provided atomic diffusion does not significantly lower the initial Li abundance in the atmospheres of metal-rich objects.
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| 20. |
- Donor, John, et al.
(författare)
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The Open Cluster Chemical Abundances and Mapping Survey. IV. Abundances for 128 Open Clusters Using SDSS/APOGEE DR16
- 2020
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Ingår i: Astronomical Journal. - : Institute of Physics (IOP). - 0004-6256 .- 1538-3881. ; 159:5
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Tidskriftsartikel (refereegranskat)abstract
- The Open Cluster Chemical Abundances and Mapping (OCCAM) survey aims to constrain key Galactic dynamical and chemical evolution parameters by the construction of a large, comprehensive, uniform, infrared-based spectroscopic data set of hundreds of open clusters. This fourth contribution from the OCCAM survey presents analysis using Sloan Digital Sky Survey/APOGEE DR16 of a sample of 128 open clusters, 71 of which we designate to be "high quality" based on the appearance of their color-magnitude diagram. We find the APOGEE DR16 derived [Fe/H] abundances to be in good agreement with previous high-resolution spectroscopic open cluster abundance studies. Using the high-quality sample, we measure Galactic abundance gradients in 16 elements, and find evolution of some of the [X/Fe] gradients as a function of age. We find an overall Galactic [Fe/H] versus R-GC gradient of -0.068 0.001 dex kpc(-1) over the range of 6 R-GC < 13.9 kpc; however, we note that this result is sensitive to the distance catalog used, varying as much as 15%. We formally derive the location of a break in the [Fe/H] abundance gradient as a free parameter in the gradient fit for the first time. We also measure significant Galactic gradients in O, Mg, S, Ca, Mn, Cr, Cu, Na, Al, and K, some of which are measured for the first time. Our large sample allows us to examine four well-populated age bins in order to explore the time evolution of gradients for a large number of elements and comment on possible implications for Galactic chemical evolution and radial migration.
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