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Register a new userStellar Chemical Abundances: In Pursuit of the Highest Achievable Precision
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The achievable level of precision on photospheric abundances of stars is a major limiting factor on investigations of exoplanet host star characteristics, the chemical histories of star clusters, and the evolution of the Milky Way and other galaxies. While model-induced errors can be minimized through the differential analysis of spectrally similar stars, the maximum achievable precision of this technique has been debated. As a test, we derive differential abundances of 19 elements from high-quality asteroid-reflected solar spectra taken using a variety of instruments and conditions. We treat the solar spectra as being from unknown stars and use the resulting differential abundances, which are expected to be zero, as a diagnostic of the error in our measurements. Our results indicate that the relative resolution of the target and reference spectra is a major consideration, with use of different instruments to obtain the two spectra leading to errors up to 0.04 dex. Use of the same instrument at different epochs for the two spectra has a much smaller effect (~0.007 dex). The asteroid used to obtain the solar standard also has a negligible effect (~0.006 dex). Assuming that systematic errors from the stellar model atmospheres have been minimized, as in the case of solar twins, we confirm that differential chemical abundances can be obtained at sub-0.01 dex precision with due care in the observations, data reduction and abundance analysis.
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We present high-resolution Magellan/MIKE spectroscopy of 42 red giant stars in seven stellar streams confirmed by the Southern Stellar Stream Spectroscopic Survey (S5): ATLAS, Aliqa Uma, Chenab, Elqui, Indus, Jhelum, and Phoenix. Abundances of 30 elements have been derived from over 10,000 individual line measurements or upper limits using photometric stellar parameters and a standard LTE analysis. This is currently the most extensive set of element abundances for stars in stellar streams. Three streams (ATLAS, Aliqa Uma, and Phoenix) are disrupted metal-poor globular clusters, although only weak evidence is seen for the light element anticorrelations commonly observed in globular clusters. Four streams (Chenab, Elqui, Indus, and Jhelum) are disrupted dwarf galaxies, and their stars display abundance signatures that suggest progenitors with stellar masses ranging from $10^6-10^7 M_odot$. Extensive description is provided for the analysis methods, including the derivation of a new method for including the effect of stellar parameter correlations on each stars abundance and uncertainty. This paper includes data gathered with the 6.5 meter Magellan Telescopes located at Las Campanas Observatory, Chile.
[ABRIDGED]We study the carbon abundances with a twofold objective. On the one hand, we want to evaluate the behaviour of carbon in the context of Galactic chemical evolution. On the other hand, we focus on the possible dependence of carbon abundances on the presence of planets and on the impact of various factors (such as different oxygen lines) on the determination of C/O elemental ratios. We derived chemical abundances of carbon from two atomic lines for 757 FGK stars in the HARPS-GTO sample. The abundances were derived with the code MOOG using automatically measured EWs and a grid of Kurucz ATLAS9 atmospheres. Oxygen abundances, derived using different lines, were taken from previous papers in this series and updated with the new stellar parameters. We find that thick- and thin-disk stars are chemically disjunct for [C/Fe] across the full metallicity range that they have in common. Moreover, the population of high-$alpha$ metal-rich stars also presents higher and clearly separated [C/Fe] ratios than thin-disk stars up to [Fe/H],$sim$,0.2,dex. The [C/O] ratios present a general flat trend as a function of [O/H] but this trend becomes negative when considering stars of similar metallicity. We find tentative evidence that stars with low-mass planets at lower metallicities have higher [C/Fe] ratios than stars without planets at the same metallicity, in the same way as has previously been found for $alpha$ elements. Finally, the elemental C/O ratios for the vast majority of our stars are below 0.8 when using the oxygen line at 6158A however, the forbidden oxygen line at 6300A provides systematically higher C/O values. Moreover, by using different atmosphere models the C/O ratios can have a non negligible difference for cool stars. Therefore, C/O ratios should be scaled to a common solar reference in order to correctly evaluate its behaviour.
The orbits, atmospheric parameters, chemical abundances, and ages of individual stars in the Milky Way provide the most comprehensive illustration of galaxy formation available. The Tycho-Gaia Astrometric Solution (TGAS) will deliver astrometric parameters for the largest ever sample of Milky Way stars, though its full potential cannot be realized without the addition of complementary spectroscopy. Among existing spectroscopic surveys, the RAdial Velocity Experiment (RAVE) has the largest overlap with TGAS ($gtrsim$200,000 stars). We present a data-driven re-analysis of 520,781 RAVE spectra using The Cannon. For red giants, we build our model using high-fidelity APOGEE stellar parameters and abundances for stars that overlap with RAVE. For main-sequence and sub-giant stars, our model uses stellar parameters from the K2/EPIC. We derive and validate effective temperature $T_{rm eff}$, surface gravity $log{g}$, and chemical abundances of up to seven elements (O, Mg, Al, Si, Ca, Fe, Ni). We report a total of 1,685,851 elemental abundances with a typical precision of 0.07 dex, a substantial improvement over previous RAVE data releases. The synthesis of RAVE-on and TGAS is the most powerful data set for chemo-dynamic analyses of the Milky Way ever produced.
We obtained spectra for two giants of Crater (Crater J113613-105227 and Crater J113615-105244) using X-Shooter at the VLT. The spectra have been analysed with the MyGIsFoS code using a grid of synthetic spectra computed from one dimensional, Local Thermodynamic Equilibrium (LTE) model atmospheres. Effective temperature and surface gravity have been derived from photometry measured from images obtained by the Dark Energy Survey. The radial velocities are 144.3+-4.0 km/s for Crater J113613-105227 and and 134.1+-4.0 km/s for Crater J113615-105244. The metallicities are [Fe/H]=-1.73 and [Fe/H]=-1.67, respectively. Beside the iron abundance we could determine abundances for nine elements: Na, Mg, Ca, Ti, V, Cr, Mn, Ni and Ba. For Na and Ba we took into account deviations from LTE, since the corrections are significant. The abundance ratios are similar in the two stars and resemble those of Galactic stars of the same metallicity. On the deep photometric images we could detect several stars that lie to the blue of the turn-off. conclusions heading (optional), leave it empty if necessary The radial velocities imply that both stars are members of the Crater stellar system. The difference in velocity between the two taken at face value, implies a velocity dispersion > 3.7 km/s at 95% confidence level. Our spectroscopic metallicities are in excellent agreement with that determined by previous investigations using photometry. Our deep photometry and the spectroscopic metallicity imply an age of 7 Gyr for the main population of the system. The stars to the blue of the turn-off can be interpreted as a younger population, of the same metallicity and an age of 2.2 Gyr. Finally, spatial and kinematical parameters support the idea that this system is associated to the galaxies Leo~IV and Leo~V. All the observations favour the interpretation of Crater as a dwarf galaxy. (Abridged).
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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