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Register a new userAn artificial neural network to discover Hypervelocity stars: Candidates in Gaia DR1/TGAS
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The paucity of hypervelocity stars (HVSs) known to date has severely hampered their potential to investigate the stellar population of the Galactic Centre and the Galactic Potential. The first Gaia data release gives an opportunity to increase the current sample. The challenge is the disparity between the expected number of hypervelocity stars and that of bound background stars. We have applied a novel data mining algorithm based on machine learning techniques, an artificial neural network, to the Tycho-Gaia astrometric solution (TGAS) catalogue. With no pre-selection of data, we could exclude immediately $sim 99 %$ of the stars in the catalogue and find 80 candidates with more than $90%$ predicted probability to be HVSs, based only on their position, proper motions, and parallax. We have cross-checked our findings with other spectroscopic surveys, determining radial velocities for 30 and spectroscopic distances for 5 candidates. In addition, follow-up observations have been carried out at the Isaac Newton Telescope for 22 stars, for which we obtained radial velocities and distance estimates. We discover 14 stars with a total velocity in the Galactic rest frame > 400 km/s, and 5 of these have a probability $>50%$ of being unbound from the Milky Way. Tracing back their orbits in different Galactic potential models we find one possible unbound HVS with velocity $sim$ 520 km/s, 5 bound HVSs, and, notably, 5 runaway stars with median velocity between 400 and 780 km/s. At the moment, uncertainties in the distance estimates and ages are too large to confirm the nature of our candidates by narrowing down their ejection location, and we wait for future Gaia releases to validate the quality of our sample. This test successfully demonstrates the feasibility of our new data mining routine.
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Hypervelocity stars are intriguing rare objects traveling at speeds large enough to be unbound from the Milky Way. Several mechanisms have been proposed for producing them, including the interaction of the Galaxys super-massive black hole (SMBH) with a binary; rapid mass-loss from a companion to a star in a short-period binary; the tidal disruption of an infalling galaxy and finally ejection from the Large Magellanic Cloud. While previously discovered high-velocity early-type stars are thought to be the result of an interaction with the SMBH, the origin of high-velocity late type stars is ambiguous. The second data release of Gaia (DR2) enables a unique opportunity to resolve this ambiguity and determine whether any late-type candidates are truly unbound from the Milky Way. In this paper, we utilize the new proper motion and velocity information available from DR2 to re-evaluate a collection of historical data compiled on the newly-created Open Fast Stars Catalog. We find that almost all previously-known high-velocity late-type stars are most likely bound to the Milky Way. Only one late-type object (LAMOST J115209.12+120258.0) is unbound from the Galaxy. Performing integrations of orbital histories, we find that this object cannot have been ejected from the Galactic centre and thus may be either debris from the disruption of a satellite galaxy or a disc runaway.
Previous studies have found that the Galactic rotation velocity-metallicity (V-[Fe/H]) relations for the thin and thick disk populations show negative and positive slopes, respectively. The first Gaia Data Release includes the Tycho-Gaia Astrometric Solution (TGAS) information, which we use to analyze the V-[Fe/H] relation for a strictly selected sample with high enough astrometric accuracy. We aim to arrive at an explanation for the slopes of the V-[Fe/H] relationship. We measure the V-[Fe/H] relation for thin and thick disk stars classified on the basis of their [$alpha$/Fe] and [Fe/H] abundances. We find dV/d[Fe/H]= -18 +/- 2 km/s/dex for stars in the thin disk and dV/d[Fe/H]= +23 +/- 10 km/s/dex for thick disk stars, so we confirm the different signs for the slopes. The negative value of dV/d[Fe/H] for thick disk stars is consistent with previous studies, but the combination of TGAS and APOGEE data provide higher precision, even though systematic errors could exceed +/-5 km/s/dex . Our average measurement of dV/d[Fe/H] for local thick disk stars shows a somewhat flatter slope than the previous studies, but we confirm a significant spread and a dependence of the slope on the [alpha/Fe] ratio of the stars. Using a simple N-body model, we demonstrate that the observed trend for the thick and thin disk can be explained by the observed radial metallicity gradients and the correlation between orbital eccentricity and metallicity in the thick disk.
Open clusters have long been used to gain insights into the structure, composition, and evolution of the Galaxy. With the large amount of stellar data available for many clusters in the Gaia era, new techniques must be developed for analyzing open clusters, as visual inspection of cluster color-magnitude diagrams is no longer feasible. An automatic tool will be required to analyze large samples of open clusters. We seek to develop an automatic isochrone-fitting procedure to consistently determine cluster membership and the fundamental cluster parameters. Our cluster characterization pipeline first determined cluster membership with precise astrometry, primarily from TGAS and HSOY. With initial cluster members established, isochrones were fitted, using a chi-squared minimization, to the cluster photometry in order to determine cluster mean distances, ages, and reddening. Cluster membership was also refined based on the stellar photometry. We used multiband photometry, which includes ASCC-2.5 BV, 2MASS JHK_s, Gaia G band. We present parameter estimates for all 24 clusters closer than 333 pc as determined by the Catalogue of Open Cluster Data and the Milky Way Star Clusters catalog. We find that our parameters are consistent to those in the Milky Way Star Clusters catalog. We demonstrate that it is feasible to develop an automated pipeline that determines cluster parameters and membership reliably. After additional modifications, our pipeline will be able to use Gaia DR2 as input, leading to better cluster memberships and more accurate cluster parameters for a much larger number of clusters.
Hypervelocity stars (HVSs) are amongst the fastest objects in our Milky Way. These stars are predicted to come from the Galactic center (GC) and travel along unbound orbits across the Galaxy. In the coming years, the ESA satellite Gaia will provide the most complete and accurate catalogue of the Milky Way, with full astrometric parameters for more than $1$ billion stars. In this paper, we present the expected sample size and properties (mass, magnitude, spatial, velocity distributions) of HVSs in the Gaia stellar catalogue. We build three Gaia mock catalogues of HVSs anchored to current observations, exploring different ejection mechanisms and GC stellar population properties. In all cases, we predict hundreds to thousands of HVSs with precise proper motion measurements within a few tens of kpc from us. For stars with a relative error in total proper motion below $10 %$, the mass range extends to ~$10 M_{odot}$ but peaks at ~$1$ $M_odot$. The majority of Gaia HVSs will therefore probe a different mass and distance range compared to the current non-Gaia sample. In addition, a subset of a few hundreds to a few thousands of HVSs with $M$ ~ $3$ $M_odot$ will be bright enough to have a precise measurement of the three-dimensional velocity from Gaia alone. Finally, we show that Gaia will provide more precise proper motion measurements for the current sample of HVS candidates. This will help identifying their birthplace narrowing down their ejection location, and confirming or rejecting their nature as HVSs. Overall, our forecasts are extremely encouraging in terms of quantity and quality of HVS data that can be exploited to constrain both the Milky Way potential and the GC properties.
The low-metallicity, kinematically interesting dwarf stars studied by Stephens & Boesgaard (2002, SB02) are re-examined using Gaia DR2 astrometry, and updated model atmospheres and atomic line data. New stellar parameters are determined based on the Gaia DR2 parallactic distances and Dartmouth Stellar Evolution Database isochrones. These are in excellent agreement with spectroscopically determined stellar parameters for stars with [Fe/H]$>-2$; however, large disagreements are found for stars with [Fe/H]$le-2$, with offsets as large as $Delta$T$_{rm eff}sim+500$ K and $Delta$log,$gsim+1.0$. A subset of six stars (test cases) are analysed ab initio using high resolution spectra with Keck HIRES and Gemini GRACES. This sub-sample is found to include two $alpha$-challenged dwarf stars, suggestive of origins in a low mass, accreted dwarf galaxy. The orbital parameters for the entire SB02 sample are re-determined using textit{Gaia} DR2 data. We find 11 stars that are dynamically coincident with the textit{Gaia}-Sausage accretion event and another 17 with the textit{Gaia}-Sequoia event in action space. Both associations include low-mass, metal-poor stars with isochrone ages older than 10 Gyr. Two dynamical subsets are identified within textit{Gaia}-Sequoia. When these subsets are examined separately, a common knee in [$alpha$/Fe] is found for the textit{Gaia}-Sausage and low orbital energy textit{Gaia}-Sequoia stars. A lower metallicity knee is tentatively identified in the textit{Gaia}-Sequoia high orbital energy stars. If the metal-poor dwarf stars in these samples are true members of the textit{Gaia}-Sausage and textit{Gaia}-Sequoia events, then they present a unique opportunity to probe the earlier, more pristine, star formation histories of these systems.
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